TY - JOUR ID - ahamed2011 AU - Ahamed, T. AU - Tian, L. AU - Zhang, Y. AU - Ting, K. C. TI - A review of remote sensing methods for biomass feedstock production UR - ://WOS:000292849200002 DO - 10.1016/j.biombioe.2011.02.028 T2 - Biomass & Bioenergy PY - 2011 DA - Jul SN - 0961-9534 VL - 35 IS - 7 SP - 2455-2469 N1 - ISI Document Delivery No.: 793UK Times Cited: 0 Cited Reference Count: 141 Ahamed, T. Tian, L. Zhang, Y. Ting, K. C. Pergamon-elsevier science ltd Oxford AB - Monitoring and maximization of bioenergy yield from biomass feedstock has recently become a critically important goal for researchers. Remote sensing represents a potential method to monitor and estimate biomass so as to increase biomass feedstock production from energy crops. This paper reviews the biophysical properties of biomass and remote sensing methods for monitoring energy crops for site-specific management. While several research studies have addressed the agronomic dimensions of this approach, more research is required on perennial energy crops in order to maximize the yield of biomass feedstock. Assessment of established methods could lead to a new strategy to monitor energy crops for the adoption of site-specific management in biomass feedstock production. In this article, satellite, aerial and ground-based remote sensing's were reviewed and focused on the spatial and temporal resolutions of imagery to adopt for site-specific management. We have concluded that the biomass yield prediction, the ground-based sensing is the most suitable to establish the calibration model and reference for aerial and satellite remote sensing. The aerial and satellite remote sensing are required for wide converge of planning and policy implementations of biomass feedstock production systems. (C) 2011 Elsevier Ltd. All rights reserved. KW - Perennial energy crops KW - Site-specific management KW - Vegetative indices KW - Leaf area index KW - Satellite imagery KW - Remote sensing KW - tropical forest biomass KW - landsat tm data KW - unmanned aerial vehicle KW - leaf-area index KW - aboveground biomass KW - radar backscatter KW - vegetation KW - index KW - water-stress KW - biophysical properties KW - image segmentation ER - TY - CPAPER ID - apan2003 AU - Apan, Armando AU - Held, Alex AU - Phinn, Stuart AU - Markley, John TI - Formulation and assessment of narrow-band vegetation indices from EO-1 hyperion imagery for discriminating sugarcane disease UR - http://eprints.usq.edu.au/8061/ PR - Spatial Sciences Institute T2 - 2003 Spatial Sciences Institute Conference: Spatial Knowledge Without Boundaries (SSC2003) CY - Canberra, Australia PY - 2003 SP - 1-13 N1 - No evidence of copyright restrictions. AB - The increasing commercial availability of hyperspectral image data promotes growing interests in the development of application-specific narrow-band spectral vegetation indices (SVIs). However, the selection of the optimum SVIs for a particular purpose is not straightforward, due to the wide choice of band combinations and transformations, combined with specific application purposes and conditions. Thus, the aim of this study was to develop an approach for formulating and assessing narrow-band vegetation indices, particularly those from EO-1 Hyperion imagery. The focus of SVI development was for discriminating sugarcane areas affected by 'orange rust' (Puccinia kuehnii) disease in Mackay, Queensland, Australia. After a series of pre-processing and post-atmospheric correction techniques, an empirical-statistical approach to SVI development was designed and implemented. This included the following components: a) selection of sample pixels of diseased and nondiseased areas, b) visual examination of spectral plots to identify bands of maximum spectral separability, c)generation of SVIs, d) use of multiple discriminant function analysis, and e) result interpretation and validation. From the forty existing and newly developed vegetation indices, the output discriminant function (i.e. a linear combination of three indices) attained a classification accuracy of 96.9% for the hold-out sample pixels. The statistical analyses also produced a list of function coefficients and correlation rankings that indicate the predictive potential of each SVI. The newly formulated 'Disease-Water Stress Indices' (DSWI) produced the highest correlations. The approach designed for this study provided a systematic framework in the formulation and assessment of SVIs for sugarcane disease detection. KW - hyperspectral remote sensing, spectral vegetation indices, sugarcane disease, Hyperion ER - TY - JOUR ID - aparicio2004 AU - Aparicio, N. AU - Villegas, D. AU - Royo, C. AU - Casadesus, J. AU - Araus, J. L. TI - Effect of sensor view angle on the assessment of agronomic traits by ground level hyper-spectral reflectance measurements in durum wheat under contrasting Mediterranean conditions UR - http://dx.doi.org/10.1080/0143116031000116967 DO - 10.1080/0143116031000116967 T2 - International Journal of Remote Sensing PY - 2004 DA - 2004/03/01 SN - 0143-1161 VL - 25 IS - 6 SP - 1131-1152 AB - The objective of this work is to study the effect of changing the sensor view angle on spectral reflectance indices and their relationships with yield and other agronomic traits. Canopy reflectance spectra of 25 durum wheat genotypes were measured with a field spectroradiometer at two view angles, nadir and 30°, from anthesis to maturity in two years and two water regimes. Nine spectral reflectance indices were calculated from reflectance measurements for correlation with yield and several agronomic traits. At off-nadir position more reflected radiation was collected, associated with the reflective characteristics of stems. The performance of the indices predicting the yield and the agronomic traits varied as a function of sensor view angle, and were moreover affected by leaf area index (LAI) value. At high LAI, simple ratio (SR) and normalized difference vegetation index (NDVI), calculated at off-nadir position, were better predictors of traits related to the density of stems and poorer predictors of traits related to green area. On the other hand, at low LAI the indices normalized pigment chlorophyll index (NPCI) and water index (WI) were better predictors of yield and all the other traits when the sensor view angle was at nadir, whereas no differences due to sensor angle were accounted for the other three indices. The different performance of indices at low and high LAI is discussed. ER - TY - JOUR ID - bannari1995 AU - Bannari, A. AU - Morin, D. AU - Bonn, F. AU - Huete, A. R. TI - A review of vegetation indices UR - http://dx.doi.org/10.1080/02757259509532298 DO - 10.1080/02757259509532298 PR - Taylor & Francis T2 - Remote Sensing Reviews PY - 1995 DA - 1995/08/01 SN - 0275-7257 VL - 13 IS - 1-2 SP - 95-120 AB - Abstract In the field of remote sensing applications, scientists have developed vegetation indices (VI) for qualitatively and quantitatively evaluating vegetative covers using spectral measurements. The spectral response of vegetated areas presents a complex mixture of vegetation, soil brightness, environmental effects, shadow, soil color and moisture. Moreover, the VI is affected by spatial?temporal variations of the atmosphere. Over forty vegetation indices have been developed during the last two decades in order to enhance vegetation response and minimize the effects of the factors described above. This paper summarizes, refers and discusses most of the vegetation indices found in the literature. It presents different existing classifications of indices and proposes to group them in a new classification. ER - TY - JOUR ID - baret1991 AU - Baret, F. AU - Guyot, G. TI - Potentials and limits of vegetation indices for LAI and APAR assessment UR - http://www.sciencedirect.com/science/article/B6V6V-48BK8FF-1B/2/44379b7ec48e94418f4bd5657f05ec0e T2 - Remote Sensing of Environment PY - 1991 SN - 0034-4257 VL - 35 IS - 2-3 SP - 161-173 ER - TY - GEN ID - baret1989 AU - Baret, F. AU - Guyot, G. AU - Major, D. TI - TSAVI: a vegetation index which minimizes soil brightness effects on LAI and APAR estimation T2 - Proceedings of 12th Canadian Symposium on Remote Sensing and IGARSS’89 PY - 1989 SP - 1355–1358 ER - TY - GEN ID - baret1989-2 AU - Baret, F. AU - Guyot, G. AU - Major, D. J. TI - Crop biomass evaluation using radiometric measurements UR - http://www.sciencedirect.com/science/article/pii/003186638990001X DO - 10.1016/0031-8663(89)90001-x T2 - Photogrammetria PY - 1989 SN - 0031-8663 VL - 43 IS - 5 SP - 241-256 AB - Crop biomass can be evaluated from radiometric measurements either by relating biomass to instantaneous measurements or by relating an integral of biomass to a radiometric value integrated over the corresponding portion of the growth period. In this study, the success obtained by using these two methods is discussed. A simple radiative transfer model was used in conjunction with experimental results to demonstrate the universality of the relationship between the normalized difference vegetation index (ND) and leaf area index (LAI) or the photosynthetically active radiation (PAR) absorbed by the crop. It shows that the relationship between ND and absorbed PAR is less dependent on leaf orientation than the relationship between ND and LAI. A remaining problem is the sensitivity of those two relationships to soil optical properties. Nevertheless, temporal integration of radiometric data using the absorbed PAR concept appears to be a more promising approach than one-time measurements. ER - TY - CPAPER ID - barnes2000 AU - Barnes, E.M. AU - Clarke, T.R. AU - Richards, S.E. AU - Colaizzi, P.D. AU - Haberland, J. AU - Kostrzewski, M. AU - Waller, P. AU - Choi, C., Riley, E. AU - Thompson, T. AU - Lascano, R.J. AU - Li, H. AU - Moran, M.S. TI - Coincident detection of crop water stress, nitrogen status and canopy density using ground based multispectral data T2 - Proc. 5th Int. Conf. Precis Agric PY - 2000 ER - TY - JOUR ID - barnes1992 AU - Barnes, J. D. AU - Balaguer, L. AU - Manrique, E. AU - Elvira, S. AU - Davison, A. W. TI - A Reappraisal of the Use of Dmso for the Extraction and Determination of Chlorophylls-a and Chlorophylls-B in Lichens and Higher-Plants UR - ://WOS:A1992HR32900001 DO - 10.1016/0098-8472(92)90034-y T2 - Environmental and Experimental Botany PY - 1992 SN - 0098-8472 VL - 32 IS - 2 SP - 85-100 AB - The use of DMSO for the extraction and determination of chlorophylls a and b in lichens and higher plants was reevaluated. Because of differences between the absorption spectra of pure chlorophylls a and b in DMSO and 80% acetone, formulae to calculate the individual concentrations of chlorophyll a, chlorophyll b and total (a + b) chlorophyll in pigment extracts were redetermined for specific use with DMSO. In lichens, the problem of chlorophyll degradation resulting from the presence of acidic lichen substances was specifically addressed. Repeated washing of thalli with carbonate-saturated 100% acetone followed by extraction in DMSO containing PVP(i) minimized the conversion of chlorophylls to phaeophytin during extraction of chlorophylls from lichens for which the content of lichen substances was characterized. In lichens containing significant quantities of acidic compounds, the modified DMSO assay proved superior to 80% acetone for the extraction and determination of chlorophyll a and b concentrations. In a range of higher plants, determinations of chlorophyll a and b concentrations were virtually identical when the modified DMSO assay was compared with the traditional method of chlorophyll extraction using 80% acetone. Moreover, DMSO extracts could be cold-stored for up to 7 days with no significant loss of chlorophylls a or b, or changes in the a/b ratio. Potential eco-physiological applications of the modified DMSO assay, which eliminates the necessity for grinding plant material and centrifuging plant extracts, are discussed. KW - dimethylsulfoxide dmso, dimethyl-sulfoxide, pigments, algae, n,n-dimethylformamide, identification, products ER - TY - JOUR ID - baroni2004 AU - Baroni, F. AU - Boscagli, A. AU - Di Lella, L. A. AU - Protano, G. AU - Riccobono, F. TI - Arsenic in soil and vegetation of contaminated areas in southern Tuscany (Italy) UR - http://www.sciencedirect.com/science/article/pii/S0375674203002085 DO - 10.1016/s0375-6742(03)00208-5 T2 - Journal of Geochemical Exploration PY - 2004 SN - 0375-6742 VL - 81 IS - 1–3 SP - 1-14 AB - Arsenic contents of soils and higher plants were surveyed in two former Sb-mining areas and in an old quarry once used for ochre extraction. Total As in the soils ranged from 5.3 to 2035.3 mg kg-1, soluble and extractable As from 0.01 to 8.5 and from 0.04 to 35.8 mg kg-1, respectively. The As concentrations in the different fractions of soil were correlated significantly or very significantly. Sixty-four plant species were analyzed. The highest As contents were found in roots and leaves of Mentha aquatica (540 and 216 mg kg-1, respectively) and in roots of Phragmites australis (688 mg kg-1). In general, the As contents of plants were low, especially in crops and in the most common wild species. In the analyzed species, roots usually showed the highest content followed by leaves and shoots. Arsenic levels in soils and plants were positively correlated, while the ability of the plants to accumulate the element (expressed by their Biological Accumulation Coefficients and Concentration Factors) was independent of the soil As content. Comparison with the literature data, relationships between the As contents in plants and soils, and biogeochemical and environmental aspects of these results are discussed. KW - Arsenic KW - Plant accumulation KW - Mining area KW - Soil contamination ER - TY - JOUR ID - bastiaanssen2000 AU - Bastiaanssen, Wim G. M. AU - Molden, David J. AU - Makin, Ian W. TI - Remote sensing for irrigated agriculture: examples from research and possible applications UR - http://www.sciencedirect.com/science/article/pii/S0378377400000809 DO - 10.1016/s0378-3774(00)00080-9 T2 - Agricultural Water Management PY - 2000 SN - 0378-3774 VL - 46 IS - 2 SP - 137-155 AB - Researchers in various international programs have studied the potential use of remotely sensed data to obtain accurate information on land surface processes and conditions. These studies have demonstrated that quantitative assessment of the soil-vegetation-atmosphere-transfer processes can lead to a better understanding of the relationships between crop growth and water management. Information on land surface can now be obtained at a wide range of spatial (5–5000 m) and temporal resolutions (0.5–24 days). However, even though considerable progress has been made over the past 20 years in research applications, remotely sensed data remain underutilized by practicing water resource managers. This paper seeks to bridge the gap between researchers and practitioners, first, by illustrating where research tools and techniques have practical applications and, second, by identifying real problems that remote sensing could solve, albeit with additional research and development. As freshwater becomes an increasingly scarce resource, all opportunities to better manage water uses, particularly in irrigated agriculture, must be taken. An important challenge in the field of water resources is to utilize the timely, objective and accurate information provided by remote sensing. KW - Remote sensing KW - Irrigated farming KW - Land management KW - Water resources management KW - Crop yield KW - Water use efficiency KW - Water rights ER - TY - ABST ID - bausch1993 AU - Bausch, Walter C. TI - Soil background effects on reflectance-based crop coefficients for corn DO - 10.1016/0034-4257(93)90096-G T2 - Remote Sensing of Environment PY - 1993 VL - 46 SP - 213-222 ER - TY - JOUR ID - birth1968 AU - Birth, G. S. AU - McVey, G. TI - Measuring the Color of Growing Turf with a Reflectance Spectrophotometer T2 - Agronomy Journal PY - 1968 DA - 0000-00-00 VL - 60 SP - 640–643 ER - TY - GEN ID - blackburn1998 AU - Blackburn, G. A. TI - Spectral indices for estimating photosynthetic pigment concentrations: A test using senescent tree leaves UR - http://dx.doi.org/10.1080/014311698215919 DO - 10.1080/014311698215919 PR - Taylor & Francis T2 - International Journal of Remote Sensing PY - 1998 DA - 1998/01/01 SN - 0143-1161 VL - 19 IS - 4 SP - 657-675 AB - Abstract The possibility of estimating the concentration of individual photosynthetic pigments within vegetation from reflectance spectra offers great promise for the use of remote sensing to assess physiological status, species type and productivity. This study evaluates a number of spectral indices for estimating pigment concentrations at the leaf scale, using samples from deciduous trees at various stages of senescence. Two new indices (PSSR and PSND) are developed which have advantages over previous techniques. The optimal individual wavebands for pigment estimation are identified empirically as 680nm for chlorophyll a, 635nm for chlorophyll b and 470nm for the carotenoids. These wavebands are justified theoretically and are shown to improve the performance of many of the spectral indices tested. Strong predictive models are demonstrated for chlorophyll a and b, but not for the carotenoids and the paper explores the reasons for this. ER - TY - JOUR ID - blackburn2007 AU - Blackburn, George Alan TI - Hyperspectral remote sensing of plant pigments UR - http://jxb.oxfordjournals.org/content/58/4/855.abstract DO - 10.1093/jxb/erl123 T2 - Journal of Experimental Botany PY - 2007 DA - March 1, 2007 VL - 58 IS - 4 SP - 855-867 AB - The dynamics of pigment concentrations are diagnostic of a range of plant physiological properties and processes. This paper appraises the developing technologies and analytical methods for quantifying pigments non-destructively and repeatedly across a range of spatial scales using hyperspectral remote sensing. Progress in deriving predictive relationships between various characteristics and transforms of hyperspectral reflectance data are evaluated and the roles of leaf and canopy radiative transfer models are reviewed. Requirements are identified for more extensive intercomparisons of different approaches and for further work on the strategies for interpreting canopy scale data. The paper examines the prospects for extending research to the wider range of pigments in addition to chlorophyll, testing emerging methods of hyperspectral analysis and exploring the fusion of hyperspectral and LIDAR remote sensing. In spite of these opportunities for further development and the refinement of techniques, current evidence of an expanding range of applications in the ecophysiological, environmental, agricultural, and forestry sciences highlights the growing value of hyperspectral remote sensing of plant pigments. ER - TY - ABST ID - boochs1990 AU - Boochs, F. AU - Kupfer, G. AU - Dockter, K. AU - Kühbauch, W. TI - Shape of the red edge as vitality indicator for plants DO - 10.1080/01431169008955127 PR - Taylor & Francis T2 - International Journal of Remote Sensing PY - 1990 SN - 0143-1161 VL - 11 IS - 10 SP - 1741-1753 ER - TY - ABST ID - broge2000 AU - Broge, N. H. AU - Leblanc, E. TI - Comparing prediction power and stability of broadband and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density DO - 10.1016/s0034-4257(00)00197-8 T2 - Remote Sensing of Environment PY - 2000 SN - 0034-4257 VL - 76 IS - 2 SP - 156-172 AB - Hyperspectral reflectance data representing a wide range of canopies were simulated using the combined PROSPECT+SAIL model. The simulations were used to study the stability of recently proposed vegetation indices (VIs) derived from adjacent narrowband spectral reflectance data across the visible (VIS) and near infrared (NIR) region of the electromagnetic spectrum. The prediction power of these indices with respect to green leaf area index (LAI) and canopy chlorophyll density (CCD) was compared, and their sensitivity to canopy architecture, illumination geometry, soil background reflectance, and atmospheric conditions were analyzed. The second soil-adjusted vegetation index (SAVI2) proved to be the best overall choice as a greenness measure. However, it is also shown that the dynamics of the VIs are very different in terms of their sensitivity to the different external factors that affects the spectral reflectance signatures of the various modeled canopies. It is concluded that hyperspectral indices are not necessarily better at predicting LAI and CCD, but that selection of a VI should depend upon (1) which parameter that needs to be estimated (LAI or CCD), (2) the expected range of this parameter, and (3) a priori knowledge of the variation of external parameters affecting the spectral reflectance of the canopy. ER - TY - JOUR ID - brown2000 AU - Brown, Daniel G. AU - Duh, Jiunn-Der AU - Drzyzga, Scott A. TI - Estimating Error in an Analysis of Forest Fragmentation Change Using North American Landscape Characterization (NALC) Data UR - http://www.sciencedirect.com/science/article/pii/S003442579900070X DO - 10.1016/s0034-4257(99)00070-x T2 - Remote Sensing of Environment PY - 2000 SN - 0034-4257 VL - 71 IS - 1 SP - 106-117 AB - We describe an approach for estimating measurement error in an analysis of forest fragmentation dynamics. We classified North American Landscape Characterization (NALC) images in four path-row locations in the Upper Midwest to characterize changing patterns of forest cover. To estimate error, we calculated the differences in values of forest fragmentation metrics for overlapping scene pairs from the same time frame (or epoch). The overlapping image areas were subdivided into landscape partitions. We tested the effects of amount of forest cover, landscape phenology, atmospheric variability (e.g., haze and clouds), and alternative processing approaches on the consistency of metric values calculated for the same place and approximate time but from different images. Two of the metrics tested (average patch size and number of patches) were more sensitive to image characteristics and contained more measurement error in a change detection analysis than the others (percent forest cover and edge density). Increasing the landscape partition size moderately reduced the amount of error in landscape change analysis, but at the cost of reduced spatial resolution. Processes used to generalize the forest map, such as small-polygon sieving and majority filtering, were not found to consistently decrease measurement error in metric values and in some cases increased error. Predictive models of error in a forest fragmentation change analysis were developed and significantly explained up to 50% of the variation in error. We demonstrate how, in a change analysis, predicted error can be used to identify locations that exhibit change substantially greater than the error in value estimation. ER - TY - CONF ID - brunn2003 AU - Brunn, A. AU - Busch, W. AU - Dittmann, C. AU - Fischer, C. AU - Vosen, P. TI - Monitoring Mining Induced Plant Alteration and Change Detection in a German Coal Mining Area using Airborne Hyperspectral Imagery T2 - Spectral Remote Sensing of Vegetation Conference at the U.S. EPA Environmental Sciences Div. CY - Las Vegas, Nevada PY - 2003 DA - March 12-14th, 2003 ER - TY - GEN ID - buschmann1993 AU - Buschmann, C. AU - Nagel, E. TI - In vivo spectroscopy and internal optics of leaves as basis for remote sensing of vegetation DO - 10.1080/01431169308904370 PR - Taylor & Francis T2 - International Journal of Remote Sensing PY - 1993 SN - 0143-1161 VL - 14 IS - 4 SP - 711-722 AB - Abstract In vivo reflection spectra of intact bean leaves (Phaseolus vulgaris) were measured between 400 and 800  nm under remote sensing conditions (illumination with white light, detection of a narrow angle of the reflected light) using the VIRAF spectrometer. The leaves with colours from yellow to green were chosen at different times during light-induced greening. The colours of the leaves were characterized by the chromaticity coordinates according to CIE 1931 calculated from the reflection spectra. The influence of the absorption of chlorophyll?the main pigment of green leaves?on the reflection spectrum of leaves is outlined. The shape of the in vivo reflection spectra is interpreted taking into account (a)the formation of pigment-protein complexes, (b) the sieve effect and the detour effect, as well as (c) the reflection, refraction and scattering of light inside the leaf tissue. Reflection signals at several distinct wavelengths and their ratios as well as the inflection point of the reflection rise from the far red towards the near-infrared were checked for linear correlation with the chlorophyll content per leaf area. The normalized difference vegetation index (NDVI) exhibited a relatively bad correlation with the chlorophyll content. The best correlation was found for the logarithm of the ratio of the reflection signals at 800 and 550 nm. We suggest that this parameter is used, in combination with the detection of the inflection point, for remotely-detecting vegetation and for the estimation of its chlorophyll content. ER - TY - JOUR ID - buschmann1993-2 AU - Buschmann, Claus TI - Fernerkundung von Pflanzen - Ausbreitung, Gesundheitszustand und Produktivitfit T2 - Naturwissenschaften PY - 1993 VL - 80 SP - 439-453 ER - TY - JOUR ID - carlson1997 AU - Carlson, T. N. AU - Ripley, David A. TI - On the relation between NDVI, fractional vegetation cover, and leaf area index UR - http://sfx.hbz-nrw.de/sfx_ubo?sid=google&auinit=TN&aulast=Carlson&atitle=On%20the%20relation%20between%20NDVI%2C%20fractional%20vegetation%20cover%2C%20and%20leaf%20area%20index&id=doi%3A10.1016%2FS0034-4257%2897%2900104-1&title=Remote%20sensing%20of%20en T2 - Remote Sensing of Environment PY - 1997 SN - 0034-4257 VL - 62 IS - 3 SP - 241-241 AB - We use a simple rudiative transfer model with vegetation, soil, and atmospheric components to illustrate hoW the normalized diflerence vegetation index @DVl), leaf area index (LAZ), and fractional vegetation cover are dependent. In particular, we suggest that LA1 and fractional vegetation cover may not be independent quantitites, ut least when the fermer is dejïned without regard to the presence of hare patches between plante, and that the customary variation of LAI with NDVI can be erplained as resulting from a variation in fractional vegetation cover. The following points are made: i) Fractional vegetation cover and LA1 are not entirely independent yuantities, depending on how LA1 is defined. Gare must be taken in using LA1 and fractional vegetation cover independently in a model because the forrner may partially take account of the latter; ii) A scaled NDVI taken between the linzits of minimum (bare ,soil) and maximum fractional vegetation cover ia insenstive to atmosphetic correction for both clear und hazy conditions, at least f3r viewing angles less than aborct 20 degrees from nadir; iii) A ,simple relution between scaled NDVI and fractional vegetation cover, previously described in the literature, is ficrther c.on&-med by the .simulations; iv) The sensitice dependence of LA1 (~1 ND17 when the fonwr is below a value of about 24 may bc viewed as being dut to the variation in the bar{: .soil component. Ol%evier Sciencc lx., 1997 ER - TY - JOUR ID - carter1994 AU - Carter, Gregory A. TI - Ratios of leaf reflectances in narrow wavebands as indicators of plant stress DO - 10.1080/01431169408954109 PR - Taylor & Francis T2 - International Journal of Remote Sensing PY - 1994 SN - 0143-1161 VL - 15 IS - 3 SP - 697-703 AB - Abstract Ratios of leaf reflectances that were measured within narrow wavebands (2nm) were evaluated as indicators of plant stress. Wavebands used in ratio computation were based on earlier studies that determined the wavelength regions in which reflectance was most affected by 8 stress agents among 6 plant species. Several ratios, such as reflectance at 695 nm divided by reflectance at 670 nm (R695/R670), were affected by some but not all stress agents. However, R695/R420, R605/R760, R695/R760 and R710/R760 were significantly greater (p≤0·05) in stressed compared with non-stressed leaves for all stress agents. The ratios that most strongly indicated plant stress were reflectance at 695 nm divided by reflectance at 420 nm or 760 nm. ER - TY - JOUR ID - carter1996 AU - Carter, Gregory A. AU - Cibula, William G. AU - Miller, Richard L. TI - Narrow-band Reflectance Imagery Compared with ThermalImagery for Early Detection of Plant Stress UR - http://www.sciencedirect.com/science/article/pii/S0176161796800708 DO - 10.1016/s0176-1617(96)80070-8 T2 - Journal of Plant Physiology PY - 1996 SN - 0176-1617 VL - 148 IS - 5 SP - 515-522 AB - Summary A field experiment compared plant stress detection by narrow-band reflectance and ratio images withthermal infrared images. Stress was induced in a mixed stand of 5 year old loblolly pine (Pinus taeda L.) and slash pine {Pinus elliottii Engelm.) by a soil application of diuron (DCMU) on 22 August followed by bromacil on 19 September, 1994. Herbicide-induced stress was first indicated on 24 and 26 September by significant (p⪯0.05) decreases in photosynthesis and the ratio of variable to maximum fluorescence (Fv/Fm), respectively. Stress was first detected remotely on 5 October by 694 ± 3 nm reflectance imagery and its ratio with reflectance at 760 ± 5 nm (p⪯0.05). This reflectance increase was detected at least 16 days prior to the first visible signs of damage, as quantified by the CIE color coordinate u', that occurred between 21 and 26 October. Reflectance images at 670 + 5 nm, 700 ± 5 nm and 760 ± 5 nm first detected stress on 21 October, 12 October and 20 December, respectively. Canopy temperature as indicated by imagery in the 8 to 12 μm band never differed significantly between herbicide-treated and control plots. This resulted from the close coupling of leaf temperatures with air temperature, and the tendency of wind and environmental moisture to equalize temperatures among treatments. The high sensitivity to stress of reflectance imagery at 694 ± 3 nm supports similar conclusions of earlier work, and indicates that imagery in the 690 to 700 nm band is far superior to thermal imagery for the early and pre-visual detection of stress in pine. KW - Pinus taeda, Pinus elliottii, plant stress, diuron, bromacil, chlorosis, canopy reflectance, canopy temperature, narrow-band imagery ER - TY - JOUR ID - ceccato2001 AU - Ceccato, Pietro AU - Flasse, Stéphane AU - Tarantola, Stefano AU - Jacquemoud, Stéphane AU - Grégoire, Jean-Marie TI - Detecting vegetation leaf water content using reflectance in the optical domain UR - http://www.sciencedirect.com/science/article/pii/S0034425701001912 DO - 10.1016/s0034-4257(01)00191-2 T2 - Remote Sensing of Environment PY - 2001 SN - 0034-4257 VL - 77 IS - 1 SP - 22-33 AB - This paper outlines the first part of a series of research studies to investigate the potential and approaches for using optical remote sensing to assess vegetation water content. It first analyzes why most methods used as approximations of vegetation water content (such as vegetation stress indices, estimation of degree of curing and chlorophyll content) are not suitable for retrieving water content at leaf level. It then documents the physical basis supporting the use of remote sensing to directly detect vegetation water content in terms of Equivalent Water Thickness (EWT) at leaf level. Using laboratory measurements, the radiative transfer model PROSPECT and a sensitivity analysis, it shows that shortwave infrared (SWIR) is sensitive to EWT but cannot be used alone to retrieve EWT because two other leaf parameters (internal structure and dry matter) also influence leaf reflectance in the SWIR. A combination of SWIR and NIR (only influenced by these two parameters) is necessary to retrieve EWT at leaf level. These results set the basis towards establishing operational techniques for the retrieval of EWT at top-of-canopy and top-of-atmospheric levels. KW - Leaf water content KW - Fuel moisture content KW - Optical domain KW - Shortwave infrared ER - TY - JOUR ID - ceccato2002 AU - Ceccato, Pietro AU - Gobron, Nadine AU - Flasse, Stéphane AU - Pinty, Bernard AU - Tarantola, Stefano TI - Designing a spectral index to estimate vegetation water content from remote sensing data: Part 1: Theoretical approach UR - http://www.sciencedirect.com/science/article/pii/S0034425702000378 DO - 10.1016/s0034-4257(02)00037-8 T2 - Remote Sensing of Environment PY - 2002 SN - 0034-4257 VL - 82 IS - 2–3 SP - 188-197 AB - This paper describes the methodology used to create a spectral index to retrieve vegetation water content from remotely sensed data in the solar spectrum domain. A global sensitivity analysis (GSA) using radiative transfer models is used to understand and quantify vegetation water content effects on the signal measured at three levels: leaf, canopy, and atmosphere. An index is then created that optimises retrieval of vegetation water content (in terms of water quantity per unit area at canopy level) and minimises perturbing effects of geophysical and atmospheric effects. The new index, optimised for the new SPOT-VEGETATION sensor, is presented as an example. Limitations and robustness of the index are also discussed. ER - TY - GEN ID - chappelle1992 AU - Chappelle, E.W. AU - Kim, M.S. AU - McMurtrey, J.E. TI - Ratio analysis of reflectance spectra (RARS): an algorithm for the remote estimation of the concentrations of chlorophyll a, chlorophyll b, and carotenoids in soybean leaves T2 - Remote Sensing of Environment PY - 1992 VL - 39 SP - 239–247 ER - TY - JOUR ID - chen1996 AU - Chen, J.M. TI - Evaluation of vegetation indices and a modified simple ratio for boreal applications T2 - Canadian Journal of Remote Sensing PY - 1996 VL - 22 IS - 3 SP - 229-242 AB - A Modified Simple Ratio (MSR) Is proposed for retrieving biophysical parameters of boreal forests using remote sensing data. This vegetation index is formulated based on an evaluation of several two-band vegetation indices, including the Normalized Difference Vegetation Index (NDVI), Simple Ratio (SR), Soil Adjusted Vegetation Indices (SAVI, SAVI1, SAVI2), Weighted Difference Vegetation Index (WDVI), Global Environment Monitoring Index (GEMI), Non-Linear Index (NLI), and Renormalized Difference Vegetation Index (RDVI). MSR is an improved version of RDVI for the purpose of linearizing their relationships with biophysical parameters. All indices were obtained from Landsat-5 TM band 3 (visible) and band 4 (near infrared) images after atmospheric corrections (except for GEMI) and were correlated with ground-based measurements made in 20 Jack Pine (Pinus banksiana) and Black Spruce (Picea mariana) stands during the BOREAS field experiment in 1994. The measurements include Leaf Area Index (LAI) and the Fraction of Photosynthetically Active Radiation (FPAR) absorbed by the forest canopies. Among these vegetation indices, SR, MSR, and NDVI were found to be best correlated with LAI and FPAR in both spring and summer. All other indices performed poorly. Both NDVI and MSR can be expressed as a function of SR. Measurement errors in remote sensing data often occur due to changes in solar zenith angle, subpixel contamination of clouds, or dissimilar surface features and the variation in the local topography and other environmental factors. These errors generally cause simultaneous increases or decreases in the red and near infrared reflectances, and their effects can be greatly reduced by taking the ratio. All other indices involving mathematical operations other than ratioing could retain the errors or even amplify them. The major problem in using the vegetation indices obtained from red and near infrared bands is the small sensitivity to the overstorey vegetation conditions. Although many of the vegetation indices such as SAVI, SAVI1, and SAVI2 are developed to minimize the effect of the background on retrieving the vegetation information, they also reduce their sensitivity to the changes in the overstorey conditions. KW - Boreal forests KW - FPAR KW - LAI KW - Vegetation index ER - TY - JOUR ID - cibula1992 AU - Cibula, W. G. AU - Zetka, E. F. AU - Rickman, D. L. TI - Response of thematic mapper bands to plant water stress UR - http://dx.doi.org/10.1080/01431169208904236 DO - 10.1080/01431169208904236 PR - Taylor & Francis T2 - International Journal of Remote Sensing PY - 1992 DA - 1992-07-01 SN - 0143-1161 VL - 13 IS - 10 SP - 1869-1880 AB - Abstract Changes in leaf reflectance as water content decreases have been hypothesized to occur in the 1 55-1.75 and 2.08-2.35 ?m wavelength regions. To evaluate this hypothesis, studies were conducted on ryegrass (Lolium muitiflorum Lam.) and oats (Avena saliva L.), which were grown in a controlled, outdoor situation. Both fully-watered control beds and water-stressed beds were periodically examined with a spectroradiometer calibrated against a reflectance reference of polytetrafluoroethylene. The observed changes correspond to those predicted by stochastic leaf models employed by other investigators (leaf reflection increases in the l.55-l.75?m region as leaf water content decreases). Although the percentage changes in TM bands 1-3 are nearly as great as those found in TM bands 5 and 7, the absolute values of reflectance change are much lower. We believe that these patterns are probably characteristic of a broad range of vegetation types. In terms of phenomena detection, these patterns should be considered in any practical remote sensing sensor scenario. ER - TY - CPAPER ID - clarke2001 AU - Clarke, T. R. AU - Moran, M. S. AU - Barnes, E. M. AU - Pinter, P. J., Jr. AU - Qi, J. TI - Planar domain indices: a method for measuring a quality of a single component in two-component pixels DO - 10.1109/igarss.2001.976818 T2 - Geoscience and Remote Sensing Symposium, 2001. IGARSS '01. IEEE 2001 International PY - 2001 VL - 3 SP - 1279-1281 AB - A method is presented that reduces the difficulty of measuring a particular quality of one component in a multi-component element. The planar domain index design requires two measurements: that of a signal sensitive to the desired quality of the target component and another signal sensitive to the component's weight or relative proportion to the whole. The quality signal and component weight signal form the two dimensions of a plane, and the maximum and minimum possible values for each signal define the boundaries of a domain within this plane. The position of a coordinate pair within the domain can then be correlated to the quality being measured, independent of the component's proportion to the whole. Examples given involve mixed vegetation and soil targets, with vegetation indices used to measure the component weight. Quality signals of the example applications include canopy minus air temperature as a measure of evapotranspiration, a normalized difference of near infrared and far red wavelengths as a measure of chlorophyll content, and differential synthetic aperture radar (SAR) for measuring near-surface soil moisture KW - agriculture, geophysical signal processing, geophysical techniques, image processing, terrain mapping, vegetation mapping, canopy, geophysical measurement technique, land surface, planar domain index, planar domain indices, quality, remote sensing, single ER - TY - GEN ID - clevers1989 AU - Clevers, J. G. P. W. TI - Application of a weighted infrared-red vegetation index for estimating leaf Area Index by Correcting for Soil Moisture UR - http://www.sciencedirect.com/science/article/pii/003442578990076X DO - 10.1016/0034-4257(89)90076-x T2 - Remote Sensing of Environment PY - 1989 SN - 0034-4257 VL - 29 IS - 1 SP - 25-37 AB - The simplified reflectance model described earlier (Clevers, 1988b) for estimating leaf area index (LAI) is further simplified. In this model the nearinfrared reflectance was corrected for soil background (in particular differences in soil moisture content) and subsequently used for estimating LAI by applying the inverse of a special case of the Mitscherlich function. In the specific situation that the ratio of the reflectances of bare soil in the red and near-infrared is constant for a given soil background, the corrected near-infrared reflectance is now ascertained as a weighted difference of total measured near-infrared and red reflectances (socalled WDVI = weighted difference vegetation index). The validity of this approach is confirmed by simulations with the SAIL model. The above concept was tested at the experimental farm of the Agricultural University Wageningen, by using reflectance factors measured in field trials by means of multispectral aerial photography. The soil type at the experimental farm yielded constant ratios between green, red, and near-infrared reflectances independent of soil moisture content (that is, as a function of time). The difference between measured near-infrared and red reflectances provided a satisfactory approximation of the corrected near-infrared reflectance. The estimation of LAI by this corrected near-infrared reflectance for real field data yielded good results in this study, resulting in the ascertainment of treatment effects with larger precision than by means of the LAI measured in the field by conventional field sampling methods. ER - TY - JOUR ID - clevers1994 AU - Clevers, J. G. P. W. AU - Büker, C. AU - van Leeuwen, H. J. C. AU - Bouman, B. A. M. TI - A framework for monitoring crop growth by combining directional and spectral remote sensing information UR - http://www.sciencedirect.com/science/article/pii/0034425794900426 DO - 10.1016/0034-4257(94)90042-6 T2 - Remote Sensing of Environment PY - 1994 SN - 0034-4257 VL - 50 IS - 2 SP - 161-170 AB - For monitoring agricultural crop production, growth of crops is modeled, for example, by using simulation models. Estimates of crop growth often are inaccurate for practical field conditions. Therefore, model simulations must be improved by incorporating information on the actual growth and development of field crops, for example, by using remote sensing data. Such data can be used to initialize, calibrate, or update crop growth models, and it can yield parameter estimates to be used as direct input into growth models: 1) leaf area index (LAI), 2) leaf angle distribution (LAD), and 3) leaf colour (optical properties in the PAR region). LAI and LAD determine the amount of light interception. Leaf (or crop) color influences the fraction of absorbed photosynthetically active radiation (APAR) and the maximum (potential) rate of photosynthesis of the leaves. A framework is described for integrating optical remote sensing data from various sources in order to estimate the mentioned parameters. In this article, the above concepts for crop growth estimation are elucidated and illustrated using groundbased and airborne data obtained during the MAC Europe 1991 campaign. Quantitative information concerning both LAI and LAD was obtained by measurements at two viewing angles (using data from the CAESAR scanner in dual-look mode). The red edge index was used for estimating the leaf optical properties (using AVIRIS data). Finally, a crop growth model (SUCROS) was calibrated on time series of optical reflectance measurements to improve the estimation of crop yield. ER - TY - JOUR ID - clevers2002 AU - Clevers, J. G. P. W. AU - De Jong, S. M. AU - Epema, G. F. AU - Van Der Meer, F. D. AU - Bakker, W. H. AU - Skidmore, A. K. AU - Scholte, K. H. TI - Derivation of the red edge index using the MERIS standard band setting UR - http://dx.doi.org/10.1080/01431160110104647 DO - 10.1080/01431160110104647 T2 - International Journal of Remote Sensing PY - 2002 DA - 2002/01/01 SN - 0143-1161 VL - 23 IS - 16 SP - 3169-3184 AB - Within ESA's Earth Observation programme, the Medium Resolution Imaging Spectrometer (MERIS) is one of the payload components of the European polar platform ENVISAT-1. MERIS will be operated with a standard band setting of 15 bands. The objective of this paper was to study whether the vegetation red edge index can be derived from the MERIS standard band setting. This red edge provides useful information on the physiological status of the vegetation. Two different data sets are explored for simulating the red edge using MERIS spectral bands. Results show that the maximum first derivative and a three-point Lagrangian technique are not appropriate measures for the red edge index. A 'linear method', estimating the inflexion point as the reflectance midpoint between the NIR plateau and the red minimum, is a more robust method. Results also show that the MERIS bands at 665, 705, 753.75 and 775 nm can be used for applying the linear method for red edge index estimation. However, since the band at 753.75 nm is located very close to the oxygen absorption feature of the atmosphere, an atmospheric correction must be applied previous to calculating the position of the red edge using the MERIS bands. ER - TY - JOUR ID - clevers2004 AU - Clevers, J. G. P. W. AU - Kooistra, L. AU - Salas, E. A. L. TI - Study of heavy metal contamination in river floodplains using the red-edge position in spectroscopic data UR - http://dx.doi.org/10.1080/01431160310001654473 DO - 10.1080/01431160310001654473 T2 - International Journal of Remote Sensing PY - 2004 DA - 2004/10/01 SN - 0143-1161 VL - 25 IS - 19 SP - 3883-3895 AB - One of the major environmental problems resulting from the regular flooding of rivers in Europe is the heavy metal contamination of soils. Various studies have shown that soil contamination may influence plant physiology and, through changes in leaf pigment concentrations, influence reflectance spectra. The main objective of this case study was to study whether the red-edge position (REP) of vegetation spectra may provide information on soil contamination by heavy metals in river floodplains. The use of the maximum first derivative, smoothing methods (like polynomial fitting and the inverted Gaussian function) and interpolation methods based on just a few spectral bands were evaluated for a test site in the floodplain of the river Waal in the Netherlands. On selected transects, heavy metal concentrations of soil samples and reflectance spectra of the growing vegetation using a field spectroradiometer were measured. A significant negative correlation between the REP and heavy metal concentration was found using the maximum first derivative method (R 2=0.64). The first derivative spectra in this study showed the presence of more than one peak within the red-edge region, as found by other authors. This phenomenon requires further detailed research using very fine spectral measurements. ER - TY - JOUR ID - cloutis1996 AU - Cloutis, E. A. AU - Connery, D. R. AU - Major, D. J. AU - Dover, F. J. TI - Airborne multi-spectral monitoring of agricultural crop status: effect of time of year, crop type and crop condition parameter UR - http://www.tandfonline.com/doi/abs/10.1080/01431169608949094 DO - 10.1080/01431169608949094 T2 - International Journal of Remote Sensing PY - 1996 DA - 1996/09/01 SN - 0143-1161 VL - 17 IS - 13 SP - 2579-2601 ER - TY - JOUR ID - cole1984 AU - Cole, Monica M. AU - Smith, Roger F. TI - Vegetation as Indicator of Environmental Pollution UR - http://www.jstor.org/stable/621782 T2 - Transactions of the Institute of British Geographers PY - 1984 SN - 00202754 VL - 9 IS - 4 SP - 477-493 AB - The environment can be polluted by industrial emissions and effluents and by dumped waste materials from mines. Most pollutants constitute health hazards and some like mercury and lead can cause disease and death. Toxic conditions can also occur in the natural environment notably where mineral elements, particularly heavy metals emanating from orebodies, enter the soils. Here metal concentration, although much lower than over mine dumps, frequently results in changes in the vegetation whereby the characteristic species give way to metal-tolerant species. Some of these indicator plants restrict their uptake of heavy metals whereas others accumulate them. The indicator plants reveal the presence of mineralization in sub-surface bedrock, including economic orebodies and may also outline areas contaminated by man's activities. They constitute the most suitable species for the reclamation of polluted areas. Examples of communities of indicator plants occupying naturally toxic ground over recently discovered copper, lead-zinc and nickel deposits in Africa, Australia and the UK are given and the presence of the same species over contaminated ground near smelters in Australia and in a meadow contaminated by run-off from old mines in Europe are cited. KW - Vegetation, Minerals, Indicator plants, Metal-tolerance, Mining, Pollution, Environment, Australia, Africa, Lrnited Kingdom ER - TY - JOUR ID - crist1984 AU - Crist, Eric P. AU - Cicone, Richard C. TI - A Physically-Based Transformation of Thematic Mapper Data---The TM Tasseled Cap DO - 10.1109/tgrs.1984.350619 T2 - Geoscience and Remote Sensing, IEEE Transactions on PY - 1984 SN - 0196-2892 VL - GE-22 IS - 3 SP - 256-263 AB - In an extension of previous simulation studies, a transformation of actual TM data in the six reflective bands is described which achieves three objectives: a fundamental view of TM data structures is presented, the vast majority of data variability is concentrated in a few (three) features, and the defined features can be directly associated with physical scene characteristics. The underlying TM data structure, based on three TM scenes as well as simulated data, is described, as are the general spectral characteristics of agricultural crops and other scene classes in the transformed data space. ER - TY - JOUR ID - curran1989 AU - Curran, Paul J. TI - Remote sensing of foliar chemistry UR - http://www.sciencedirect.com/science/article/pii/0034425789900692 DO - 10.1016/0034-4257(89)90069-2 T2 - Remote Sensing of Environment PY - 1989 SN - 0034-4257 VL - 30 IS - 3 SP - 271-278 AB - Remotely sensed data are being used to estimate foliar chemical content as a result of our need for the information and our increasing ability to understand and measure foliar spectra. This paper reviews how stepwise multiple regression and deconvolution have been used to extract chemical information from foliar spectra, and concludes that both methods are useful, but neither is ideal. It is recommended that the focus of research be modeling in the long term and experimentation in the short term. Long-term research should increase our understanding of the interaction between radiation and foliar chemistry so that the focus of research can move from leaf model to canopy model to field experiment. Short-term research should aim to design experiments in which remotely sensed data are used to generate unambiguous and accurate estimates of foliar chemical content. ER - TY - JOUR ID - curran1995 AU - Curran, Paul J. AU - Windham, W. Robert AU - Gholz, Henry L. TI - Exploring the relationship between reflectance red edge and chlorophyll concentration in slash pine leaves UR - http://treephys.oxfordjournals.org/content/15/3/203.abstract DO - 10.1093/treephys/15.3.203 T2 - Tree Physiology PY - 1995 DA - March 1, 1995 VL - 15 IS - 3 SP - 203-206 AB - Chlorophyll concentration is related positively to the point of maximum slope in the reflectance spectra of leaves and this point is termed the red edge. The reflectance spectra of slash pine (Pinus elliottii Engelm.) needles were measured in the field and the chlorophyll concentrations of the same needles were measured in the laboratory. The measurement errors for red edge and chlorophyll concentration were determined to be 2.2 nm (3% of mean) and 0.35 mg g-1 (19% of mean), respectively. The red edge–chlorophyll concentration relationship was strong (r2 = 0.82, n = 152). A red edge–chlorophyll concentration relationship for n = 100 was used with red edge measurements to estimate chlorophyll concentration with an rms error of 0.31 mg g-1 (17% of mean, n = 52). The entire red edge–chlorophyll concentration relationship for n = 152 was also used with red edge measurements to estimate the chlorophyll concentration of samples from an earlier experiment with an rms error of 0.47 mg g-1 (30% of mean, n = 38). We conclude that measures of red edge can be used to estimate the chlorophyll concentration of detached needles in the field with an accuracy similar to that obtained by conventional laboratory measurements. ER - TY - JOUR ID - dang2011 AU - Dang, Y. P. AU - Pringle, M. J. AU - Schmidt, M. AU - Dalal, R. C. AU - Apan, A. TI - Identifying the spatial variability of soil constraints using multi-year remote sensing UR - ://WOS:000293989100008 DO - 10.1016/j.fcr.2011.05.021 T2 - Field Crops Research PY - 2011 DA - Sep SN - 0378-4290 VL - 123 IS - 3 SP - 248-258 N1 - ISI Document Delivery No.: 808OU Times Cited: 1 Cited Reference Count: 42 Dang, Y. P. Pringle, M. J. Schmidt, M. Dalal, R. C. Apan, A. Grains Research & Development Corporation We wish to thank Peter and Jim Russell for providing their yield data and access to their farm. We thank the Grains Research & Development Corporation for partial funding of this study. Thanks are due to Dr. Jeremy Whish for doing the APSIM simulations and to Drs. Brett Robinson and Robert Denham for comments on draft versions. Elsevier science bv Amsterdam AB - In north-eastern Australia, soil attributes such as salinity, sodicity, acidity, and phytotoxic concentrations of chloride constrain the growth of crops. It is difficult to delineate constrained areas using conventional sampling methods. Alternatively, where crops fail, over multiple years, to pass a certain yield threshold, we might infer the presence of a soil constraint. For a wheat-growing farm over 10-year period we used remote sensing to obtain a large volume of surrogate yield data, by calibrating an archive of Normalised Difference Vegetation Index (NDVI) to an archive of (limited) ground-based observations. The model used was a generalised additive model that related wheat yield as a non-linear function of NDVI and a linear function of post-anthesis rainfall. Field locations where predicted yield consistently failed to reach the 75th percentile in a given year, over a number of years, we regarded as limited by at least one unknown soil constraint. Soil samples averaged for the constrained locations showed, compared with the unconstrained locations, relatively high concentrations of subsoil chloride, and, in the topsoil, relatively high exchangeable sodium percentage, and unused nitrate nitrogen. On-farm experiments suggested that, for constrained areas, preclusion of monoammonium phosphate (MAP) fertiliser application, coupled to gypsum amelioration, could potentially benefit the farm by A$32/ha/year (MAP) and A$207/ha/3 years (gypsum). Crown Copyright (c) 2011 Published by Elsevier B.V. All rights reserved. KW - Soil constraints KW - Crop yield KW - Precision agriculture KW - NDVI KW - Whole-farm KW - economics KW - crop yield KW - wheat yield KW - subsoil constraints KW - grain production KW - australia KW - vegetation KW - satellite KW - ndvi KW - management KW - salinity ER - TY - JOUR ID - dash2004 AU - Dash, J. AU - Curran, P. J. TI - The MERIS terrestrial chlorophyll index UR - http://dx.doi.org/10.1080/0143116042000274015 DO - 10.1080/0143116042000274015 PR - Taylor & Francis T2 - International Journal of Remote Sensing PY - 2004 DA - 2004/12/01 SN - 0143-1161 VL - 25 IS - 23 SP - 5403-5413 AB - The long wavelength edge of the major chlorophyll absorption feature in the spectrum of a vegetation canopy moves to longer wavelengths with an increase in chlorophyll content. The position of this red-edge has been used successfully to estimate, by remote sensing, the chlorophyll content of vegetation canopies. Techniques used to estimate this red-edge position (REP) have been designed for use on small volumes of continuous spectral data rather than the large volumes of discontinuous spectral data recorded by contemporary satellite spectrometers. Also, each technique produces a different value of REP from the same spectral data and REP values are relatively insensitive to chlorophyll content at high values of chlorophyll content. This paper reports on the design and indirect evaluation of a surrogate REP index for use with spectral data recorded at the standard band settings of the Medium Resolution Imaging Spectrometer (MERIS). This index, termed the MERIS terrestrial chlorophyll index (MTCI), was evaluated using model spectra, field spectra and MERIS data. It was easy to calculate (and so can be automated), was correlated strongly with REP but unlike REP was sensitive to high values of chlorophyll content. As a result this index became an official MERIS level-2 product of the European Space Agency in March 2004. Further direct evaluation of the MTCI is proposed, using both greenhouse and field data. ER - TY - JOUR ID - datt1998 AU - Datt, Bisun TI - Remote Sensing of Chlorophyll a, Chlorophyll b, Chlorophyll a+b, and Total Carotenoid Content in Eucalyptus Leaves UR - http://www.sciencedirect.com/science/article/pii/S0034425798000467 DO - 10.1016/s0034-4257(98)00046-7 T2 - Remote Sensing of Environment PY - 1998 SN - 0034-4257 VL - 66 IS - 2 SP - 111-121 AB - Algorithms based on reflectance band ratios have been developed for the remote estimation of chlorophyll a, chlorophyll b, chlorophyll a+b, and total carotenoid content of Eucalyptus leaves. Reflectance spectra over the 400–2500 nm range with a spectral resolution of 2 nm and the content of chlorophylls a, b, a+b, and total carotenoids were determined for leaves from several Eucalyptus species covering a wide range of chlorophyll a content (0.0121–0.0435 mg/cm2). Maximum sensitivity of reflectance to variation in pigment content was found in the green wavelength region at 550 nm and at 708 nm in the far-red wavelengths. The reflectance in the main pigment absorption regions in the blue (400–500 nm) and red (660–690 nm) wavelengths proved to be insensitive to variation in pigment content. The ratio R672/(R550× R708) correlated best with chlorophyll a, chlorophyll a+b, and total carotenoid contents. The ratio R672/R550 correlated best with chlorophyll b content. Reflectance ratios involving near infrared bands such as R750/R550 and R750/R700 did not correlate well with pigment content. This was due to the differential scattering effects of the wide range of young and mature leaf samples. A method was developed for adjusting all spectra to the same level of scatter. The near-infrared-based reflectance ratios from the scatter adjusted spectra showed high sensitivity to pigment content. The ratio R860/(R550×R708) from the scatter adjusted spectra correlated best with chlorophyll a, chlorophyll a+b, and total carotenoid contents, while R860/R550 correlated best with chlorophyll b content. The newly developed algorithms were tested on a validation data set and allowed accurate estimates of leaf pigment content. The pigment contents estimated by the ratios from untransformed spectra, R672/(R550×R708) and R672/R550, were found to be not significantly different from the estimates obtained using the scatter-adjusted reflectance ratios, R860/(R550×R708) and R860/R550. ER - TY - JOUR ID - datt1999 AU - Datt, Bisun TI - Remote Sensing of Water Content in Eucalyptus Leaves DO - http://dx.doi.org/10.1071/BT98042 T2 - Australian Journal of Botany PY - 1999 VL - 47 IS - 6 SP - 909-923 AB - The spectral reflectance of leaves from several Eucalyptus species was measured over the 400–2500 nm wavelengths with a laboratory spectroradiometer. The relationship of reflectance with the gravimetric water content and equivalent water thickness (EWT) of the leaves was analysed. The results showed that EWT was strongly correlated with reflectance in several wavelength regions. No significant correlations could be obtained between reflectance and gravimetric water content. It was also possible to confirm theoretically that reflectance changes of leaves could be directly linked to changes in EWT but not to changes in gravimetric water content. Several existing reflectance indices were evaluated for estimation of leaf water content and some new indices were developed and tested. Two semi-empirical indices developed in this study, (R850 - R2218)/(R850 - R1928) and (R850 - R1788)/(R850 - R1928), were found to show significantly stronger correlations with EWT than all other indices tested. It was also shown that these new indices were least sensitive to the effects of radiation scatter. The indices (R850 - R2218)/(R850 - R1928) and (R850 - R1788)/(R850 - R1928) are therefore proposed as two new indices for the remote estimation of vegetation water content. ER - TY - JOUR ID - daughtry2000 AU - Daughtry, C. S. T. AU - Walthall, C. L. AU - Kim, M. S. AU - de Colstoun, E. Brown AU - McMurtrey Iii, J. E. TI - Estimating Corn Leaf Chlorophyll Concentration from Leaf and Canopy Reflectance UR - http://www.sciencedirect.com/science/article/pii/S0034425700001139 DO - 10.1016/s0034-4257(00)00113-9 T2 - Remote Sensing of Environment PY - 2000 SN - 0034-4257 VL - 74 IS - 2 SP - 229-239 AB - Farmers must balance the competing goals of supplying adequate N for their crops while minimizing N losses to the environment. To characterize the spatial variability of N over large fields, traditional methods (soil testing, plant tissue analysis, and chlorophyll meters) require many point samples. Because of the close link between leaf chlorophyll and leaf N concentration, remote sensing techniques have the potential to evaluate the N variability over large fields quickly. Our objectives were to (1) select wavelengths sensitive to leaf chlorophyll concentration, (2) simulate canopy reflectance using a radiative transfer model, and (3) propose a strategy for detecting leaf chlorophyll status of plants using remotely sensed data. A wide range of leaf chlorophyll levels was established in field-grown corn (Zea mays L.) with the application of 8 N levels: 0%, 12.5%, 25%, 50%, 75%, 100%, 125%, and 150% of the recommended rate. Reflectance and transmittance spectra of fully expanded upper leaves were acquired over the 400-nm to 1,000-nm wavelength range shortly after anthesis with a spectroradiometer and integrating sphere. Broad-band differences in leaf spectra were observed near 550 nm, 715 nm, and >750 nm. Crop canopy reflectance was simulated using the SAIL (Scattering by Arbitrarily Inclined Leaves) canopy reflectance model for a wide range of background reflectances, leaf area indices (LAI), and leaf chlorophyll concentrations. Variations in background reflectance and LAI confounded the detection of the relatively subtle differences in canopy reflectance due to changes in leaf chlorophyll concentration. Spectral vegetation indices that combined near-infrared reflectance and red reflectance (e.g., OSAVI and NIR/Red) minimized contributions of background reflectance, while spectral vegetation indices that combined reflectances of near-infrared and other visible bands (MCARI and NIR/Green) were responsive to both leaf chlorophyll concentrations and background reflectance. Pairs of these spectral vegetation indices plotted together produced isolines of leaf chlorophyll concentrations. The slopes of these isolines were linearly related to leaf chlorophyll concentration. A limited test with measured canopy reflectance and leaf chlorophyll data confirmed these results. The characterization of leaf chlorophyll concentrations at the field scale without the confounding problem of background reflectance and LAI variability holds promise as a valuable aid for decision making in managing N applications. ER - TY - CONF ID - daughtry2001 AU - Daughtry, C. AU - Hunt, E. R. AU - Walthall, C. L. AU - Gish, T. J. AU - Liang, Shunlin AU - Kramer, E.J. TI - Assessing the Spatial Distribution of Plant Litter T2 - Proceedings of the Tenth JPL Airborne Earth Science Workshop PY - 2001 SP - 105-114 AB - Quantifying crop residue cover on the soil surface is important for improving estimates of surface energy balance, net primary productivity, nutrient cycling, and carbon sequestration. Quantifying crop residue cover is also an important factor in controlling soil erosion and evaluating the effectiveness of conservation tillage practices. By reducing the movement of eroded soil into streams and rivers, the movement of nutrients and pesticides is reduced. The overall result is less soil erosion and improved water quality. Current methods for quantifying crop residue cover are tedious and somewhat subjective. The standard technique for measuring crop residue cover used by the USDA Natural Resources Conservation Service (NRCS) is visual estimation along a line-transect. Reviews of crop residue measurement techniques document recent modifications and illustrate the unresolved problems of current techniques. Rapid, accurate, and objective methods to quantify residue cover are needed. The objectives of this research were to: (1) determine the spectral reflectance of green plants, plant litters, and soils as a function of water content; (2) assess the limits of discrimination that can be expected; and (3) evaluate hyperspectral imaging data for providing information on the spatial distribution of plant litter. This research provides the scientific foundation required for sensor development and field testing. ER - TY - JOUR ID - dorigo2007 AU - Dorigo, W. A. AU - Zurita-Milla, R. AU - de Wit, A. J. W. AU - Brazile, J. AU - Singh, R. AU - Schaepman, M. E. TI - A review on reflective remote sensing and data assimilation techniques for enhanced agroecosystem modeling UR - ://WOS:000246320700008 DO - 10.1016/j.jag.2006.05.003 T2 - International Journal of Applied Earth Observation and Geoinformation PY - 2007 DA - May SN - 0303-2434 VL - 9 IS - 2 SP - 165-193 N1 - ISI Document Delivery No.: 165QP Times Cited: 39 Cited Reference Count: 181 Dorigo, W. A. Zurita-Milla, R. de Wit, A. J. W. Brazile, J. Singh, R. Schaepman, M. E. Conference on Advances in Airborne Electromagnetics and Remote Sensing of Agro-Ecosystems 2004 Wageningen, NETHERLANDS Elsevier science bv Amsterdam AB - During the last 50 years, the management of agroecosystems has been undergoing major changes to meet the growing demand for food, timber, fibre and fuel. As a result of this intensified use, the ecological status of many agroecosystems has been severely deteriorated. Modeling the behavior of agroecosystems is, therefore, of great help since it allows the definition of management strategies that maximize (crop) production while minimizing the environmental impacts. Remote sensing can support such modeling by offering information on the spatial and temporal variation of important canopy state variables which would be very difficult to obtain otherwise. In this paper, we present an overview of different methods that can be used to derive biophysical and biochemical canopy state variables from optical remote sensing data in the VNIR-SWIR regions. The overview is based on an extensive literature review where both statistical-empirical and physically based methods are discussed. Subsequently, the prevailing techniques of assimilating remote sensing data into agroecosystem models are outlined. The increasing complexity of data assimilation methods and of models describing agroecosystem functioning has significantly increased computational demands. For this reason, we include a short section on the potential of parallel processing to deal with the complex and computationally intensive algorithms described in the preceding sections. The studied literature reveals that many valuable techniques have been developed both for the retrieval of canopy state variables from reflective remote sensing data as for assimilating the retrieved variables in agroecosystem models. However, for agroecosystem modeling and remote sensing data assimilation to be commonly employed on a global operational basis, emphasis will have to be put on bridging the mismatch between data availability and accuracy on one hand, and model and user requirements on the other. This could be achieved by integrating imagery with different spatial, temporal, spectral, and angular resolutions, and the fusion of optical data with data of different origin, such as LIDAR and radar/microwave. (c) 2006 Elsevier B.V. All rights reserved. KW - data assimilation KW - agroecosystem modeling KW - vegetation indices KW - canopy KW - reflectance modeling KW - biophysical variables KW - biochemical variables KW - parallel processing KW - radiative-transfer models KW - leaf-area index KW - hyperspectral vegetation KW - indexes KW - hydrologic data assimilation KW - multiple linear-regression KW - canopy chlorophyll density KW - ensemble kalman filter KW - bidirectional KW - reflectance KW - soil-moisture KW - crop models ER - TY - CONF ID - dorigo2007-2 AU - Dorigo, Wouter AU - Gerighausen, Heike TI - Automatic retrieval of crop characteristics: an example for hyperspectral AHS data from the AgriSAR campaign T2 - Proc. on AGRISAR and EAGLE Campaigns Final Workshop CY - Noordwijk, The Netherlands PY - 2007 DA - 2007-10-15 - 2007-10-16 KW - hyperspectral, AHS, imaging spectroscopy, radiative transfer model inversion, CRASh, PROSPECT, SAILh, LAI, chlorophyll, winter wheat, winter barley, winter rape, maize, sugar beet ER - TY - JOUR ID - duveiller2011 AU - Duveiller, Grégory AU - Weiss, Marie AU - Baret, Frédéric AU - Defourny, Pierre TI - Retrieving wheat Green Area Index during the growing season from optical time series measurements based on neural network radiative transfer inversion UR - http://www.sciencedirect.com/science/article/pii/S0034425710003354 DO - 10.1016/j.rse.2010.11.016 T2 - Remote Sensing of Environment PY - 2011 SN - 0034-4257 VL - 115 IS - 3 SP - 887-896 KW - Winter wheat KW - Leaf Area Index KW - Green Area Index KW - Radiative transfer inversion KW - Neural networks KW - Saturation KW - SPOT/HRV KW - SPOT/HRVIR KW - Time series ER - TY - CONF ID - ehammer2010 AU - Ehammer, Andrea AU - Fritsch, Sebastian AU - Conrad, Christopher AU - Lamers, John AU - Dech, Stefan TI - Statistical derivation of fPAR and LAI for irrigated cotton and rice in arid Uzbekistan by combining multi-temporal RapidEye data and ground measurements UR - http://link.aip.org/link/PSISDG/v7824/i1/p782409/s1&Agg=doi PY - 2010 VL - 7824 SP - 782409-782409-10-782409-782409-1 ER - TY - JOUR ID - eitel2007 AU - Eitel, J. U. H. AU - Long, D. S. AU - Gessler, P. E. AU - Smith, A. M. S. TI - Using insitu measurements to evaluate the new RapidEye™ satellite series for prediction of wheat nitrogen status UR - http://dx.doi.org/10.1080/01431160701422213 DO - 10.1080/01431160701422213 T2 - International Journal of Remote Sensing PY - 2007 DA - 2007/09/20 SN - 0143-1161 VL - 28 IS - 18 SP - 4183-4190 AB - This study assessed whether vegetation indices derived from broadband RapidEye? data containing the red edge region (690?730 nm) equal those computed from narrow band data in predicting nitrogen (N) status of spring wheat (Triticum aestivum L.). Various single and combined indices were computed from in?situ spectroradiometer data and simulated RapidEye? data. A new, combined index derived from the Modified Chlorophyll Absorption Ratio Index (MCARI) and the second Modified Triangular Vegetation Index (MTVI2) in ratio obtained the best regression relationships with chlorophyll meter values (Minolta Soil Plant Analysis Development (SPAD) 502 chlorophyll meter) and flag leaf N. For SPAD, r 2 values ranged from 0.45 to 0.69 (p<0.01) for narrow bands and from 0.35 and 0.77 (p<0.01) for broad bands. For leaf N, r 2 values ranged from 0.41 to 0.68 (p<0.01) for narrow bands and 0.37 to 0.56 (p<0.01) for broad bands. These results are sufficiently promising to suggest that MCARI/MTVI2 employing broadband RapidEye? data is useful for predicting wheat N status. ER - TY - JOUR ID - el-shikha2008 AU - El-Shikha, D. M. AU - Barnes, E. M. AU - Clarke, T. R. AU - Hunsaker, D. J. AU - Haberland, J. A. AU - Pinter, P. J. AU - Waller, P. M. AU - Thompson, T. L. TI - Remote sensing of cotton nitrogen status using the Canopy Chlorophyll Content Index (CCCI) UR - ://WOS:000255421800007 T2 - Transactions of the Asabe PY - 2008 DA - Jan-Feb SN - 0001-2351 VL - 51 IS - 1 SP - 73-82 N1 - ISI Document Delivery No.: 294QY Times Cited: 6 Cited Reference Count: 37 El-Shikha, D. M. Barnes, E. M. Clarke, T. R. Hunsaker, D. J. Haberland, J. A. Pinter, P. J., Jr. Waller, P. M. Thompson, T. L. Amer soc agricultural & biological engineers St joseph AB - Various remote sensing indices have been used to infer crop nitrogen (N) status for field-scale nutrient management. However, such indices may indicate erroneous N status if there is a decrease in crop canopy density influenced by other factors, such as water stress. The Canopy Chlorophyll Content Index (CCCI) is a two-dimensional remote sensing index that has been proposed for inferring cotton N status. The CCCI uses reflectances in the near-infrared (NIR) and red spectral regions to account for seasonal changes in canopy density, while reflectances in the NIR and far-red regions are used to detect relative changes in canopy chlorophyll, a surrogate for N content. The primary objective of this study was to evaluate the CCCI and several other remote sensing indices for detecting the N status for cotton during the growing season. A secondary objective was to evaluate the ability of the indices to appropriately detect N in the presence of variable water status. Remote sensing data were collected during the 1998 (day of year [DOY] 114 to 310) and 1999 (DOY 106 to 316) cotton seasons in Arizona, in which treatments of optimal and low levels of N and water were imposed. In the 1998 season, water treatments were not imposed until late in the season (DOY 261), well after full cover Following an early season N application in 1998 for the optimal (DOY 154) but not the low N treatment, the CCCI detected significant differences in crop N status between the N treatments starting on DOY 173, when canopy cover was about 30%. A common vegetation index, the ratio of NIR to red (RVI), also detected significant separation between N treatments, but RVI detection occurred 16 days after the CCCI response. After an equal amount of N was applied to both optimal and low N treatments on DOY 190 in 1998, the CCCI indicated comparable N status for the N treatments on DOY 198, a trend not detected by RVI. In the 1999 season, both N and water treatments were imposed early and frequently during the season. The N status was poorly described by both the CCCI and RVI under partial canopy conditions when water status differed among treatments. However, once full canopy was obtained in 1999, the CCCI provided reliable N status information regardless of water status. At full cotton cover, the CCCI was significantly correlated with measured parameters of N status, including petiole NO3-N (r = 0.74), SPAD chlorophyll (r = 0.65), and total leaf N contents (r = 0.86). For well-watered cotton, the CCCI shows promise as a useful indicator of cotton N status after the canopy reaches about 30% cover However, further study is needed to develop the CCCI as a robust N detection tool independent of water stress. KW - canopy reflectance KW - fertility detection KW - radiometers KW - spectral analysis KW - water stress KW - reflectance indexes KW - spectral radiance KW - winter-wheat KW - corn leaves KW - grain-yield KW - water KW - stress KW - plants KW - light KW - field ER - TY - CONF ID - escadafal1994 AU - Escadafal, R. AU - Belghith, A. AU - Ben Moussa, H. TI - Indices spectraux pour la dégradation des milieux naturels en Tunisie aride T2 - 6ème Symp. Int. Mesures Physiques et Signatures en Télédétection, ISPRS-CNES CY - Val d’lsère, France PY - 1994 DA - 0000-00-00 SP - 253–259 ER - TY - JOUR ID - escadafal1991 AU - Escadafal, R. AU - Huete, A. TI - Improvement in remote sensing of low vegetation cover in arid regions by correcting vegetation indices for soil "noise' T2 - Comptes Rendus - Academie des Sciences, Serie II PY - 1991 VL - 11 IS - 312 SP - 1385-1391 AB - The variations of near-infrared/red reflectance ratios of ten arid soil samples were correlated with a "redness index' computed from red and green spectral bands. These variations have been shown to limit the performances of vegetation indices (NDVI and soil adjusted VI) in discriminating low vegetation covers. The redness index is used to adjust for this "soil noise'. The "noise-corrected' SAVI was able to assess vegetation amounts with an error four times smaller than the uncorrected NDVI. These is an abridged English version. -from English summary KW - GEOBASE Subject Index: arid region KW - biomass KW - soil noise KW - vegetation index ER - TY - GEN ID - fensholt2003 AU - Fensholt, Rasmus AU - Sandholt, Inge TI - Derivation of a shortwave infrared water stress index from MODIS near- and shortwave infrared data in a semiarid environment UR - http://www.sciencedirect.com/science/article/pii/S0034425703001895 DO - 10.1016/j.rse.2003.07.002 T2 - Remote Sensing of Environment PY - 2003 SN - 0034-4257 VL - 87 IS - 1 SP - 111-121 AB - Two different configurations of a shortwave infrared water stress index (SIWSI) are derived from the MODIS near- and shortwave infrared data. A large absorption by leaf water occurs in the shortwave infrared wavelengths (SWIR) and the reflectance from plants thereby is negatively related to leaf water content. Two configurations of a water stress index, SIWSI(6,2) and SIWSI(5,2) are derived on a daily basis from the MODIS satellite data using the information from the near infrared (NIR) channel 2 (841–876 nm) and the shortwave infrared channel 5 (1230–1250 nm) or 6 (1628–1652 nm), respectively, which are wavelength bands at which leaf water content influence the radiometric response. The indices are compared to in situ top layer soil moisture measurements from the semiarid Senegal 2001 and 2002, serving as an indicator of canopy water content. The year 2001 rainfall in the region was slightly below average and the results show a strong correlation between SIWSI and soil moisture. The SIWSI(6,2) performs slightly better than the SIWSI(5,2) (r2=0.87 and 0.79). The fieldwork in 2002 did not verify the results found in 2001. However, year 2002 was an extremely dry year and the vegetation cover apparently was too sparse to provide information on the canopy water content. To test the robustness of the SIWSI findings in 2001, soil moisture has been modelled from daily rainfall data at 10 sites in the central and northern part of Senegal. The correlations between SIWSI and simulated soil moisture are generally high with a median r2=0.72 for both configurations of the SIWSI. It is therefore suggested that the combined information from the MODIS near- and shortwave infrared wavelengths is useful as an indicator of canopy water stress in the semiarid Sahelian environment. KW - Shortwave infrared water stress index (SIWSI) KW - MODIS satellite data KW - Rainfall KW - Soil moisture KW - Vegetation index KW - Sahel ER - TY - CONF ID - fischer2002 AU - Fischer, Christian TI - Use of GIS and Multitemporal Imaging Spectrometer data for Modelling and Mapping Environmental Changes in Mining Areas T2 - ISPRS Commission IV Symposium “Geospatial Theory, Processing and Applications” CY - Ottawa PY - 2002 DA - 8 – 12 July 2002 SN - 1682-1750 VL - 14 SP - 460-464 ER - TY - JOUR ID - friedl1994 AU - Friedl, M. A. AU - Schimel, D. S. AU - Michaelsen, J. AU - Davis, F. W. AU - Walker, H. TI - Estimating grassland biomass and leaf area index using ground and satellite data UR - http://dx.doi.org/10.1080/01431169408954174 DO - 10.1080/01431169408954174 T2 - International Journal of Remote Sensing PY - 1994 DA - 1994/05/10 SN - 0143-1161 VL - 15 IS - 7 SP - 1401-1420 AB - Abstract We compared estimates of regional biomass and LAI for a tallgrass prairie site derived from ground data versus estimates derived from satellite data. Linear regression models were estimated to predict LAI and biomass from Landsat-TM data for imagery acquired on three dates spanning the growing season of 1987 using co-registered TM data and ground measurements of LAl and biomass collected at 27 grassland sites. Mapped terrain variables including burning treatment, land-use, and topographic position were included as indicator variables in the models to acccount for variance in biomass and LAI not captured in the TM data. Our results show important differences in the relationships between Kauth-Thomas greenness (from TM), LAI, biomass and the various terrain variables. In general, site-wide estimates of biomass and LAI derived from ground versus satellite-based data were comparable. However, substantial differences were observed in June. In a number of cases, the regression models exhibited significantly higher explained variance due to the incorporation of terrain variables, suggesting that for areas encompassing heterogeneous landcover the inclusion of categorical terrain data in calibration procedures is a useful technique. ER - TY - JOUR ID - gamon1992 AU - Gamon, J. A. AU - Peñuelas, J. AU - Field, C. B. TI - A narrow-waveband spectral index that tracks diurnal changes in photosynthetic efficiency UR - http://www.sciencedirect.com/science/article/pii/003442579290059S DO - 10.1016/0034-4257(92)90059-s T2 - Remote Sensing of Environment PY - 1992 SN - 0034-4257 VL - 41 IS - 1 SP - 35-44 ER - TY - JOUR ID - gamon1997 AU - Gamon, J. A. AU - Serrano, L. AU - Surfus, J. S. TI - The photochemical reflectance index: an optical indicator of photosynthetic radiation use efficiency across species, functional types, and nutrient levels UR - http://dx.doi.org/10.1007/s004420050337 DO - 10.1007/s004420050337 T2 - Oecologia PY - 1997 SN - 0029-8549 VL - 112 IS - 4 SP - 492-501 AB - The photochemical reflectance index (PRI), derived from narrow-band reflectance at 531 and 570 nm, was explored as an indicator of photosynthetic radiation use efficiency for 20 species representing three functional types: annual, deciduous perennial, and evergreen perennial. Across species, top-canopy leaves in full sun at midday exhibited a strong correlation between PRI and ?F/Fm', a fluorescence-based index of photosystem II (PSII) photochemical efficiency. PRI was also significantly correlated with both net CO 2 uptake and radiation use efficiency measured by gas exchange. When species were examined by functional type, evergreens exhibited significantly reduced midday photosynthetic rates relative to annual and deciduous species. This midday reduction was associated with reduced radiation use efficiency, detectable as reduced net CO 2 uptake, PRI, and ?F/Fm' values, and increased levels of the photoprotective xanthophyll cycle pigment zeaxanthin. For each functional type, nutrient deficiency led to reductions in both PRI and ?F/Fm' relative to fertilized controls. Laboratory experiments exposing leaves to diurnal courses of radiation and simulated midday stomatal closure demonstrated that PRI changed rapidly with both irradiance and leaf physiological state. In these studies, PRI was closely correlated with both ?F/Fm' and radiation use efficiency determined from gas exchange at all but the lowest light levels. Examination of the difference spectra upon exposure to increasing light levels revealed that the 531 nm ? reflectance signal was composed of two spectral components. At low irradiance, this signal was dominated by a 545-nm component, which was not closely related to radiation use efficiency. At progressively higher light levels above 100 µmol m -2 s -1 , the 531-nm signal was increasingly dominated by a 526-nm component, which was correlated with light use efficiency and with the conversion of the xanthophyll pigment violaxanthin to antheraxanthin and zeaxanthin. Further consideration of the two components composing the 531-nm signal could lead to an index of photosynthetic function applicable over a wide range of illumination. The results of this study support the use of PRI as an interspecific index of photosynthetic radiation use efficiency for leaves and canopies in full sun, but not across wide ranges in illumination from deep shade to full sun. The discovery of a consistent relationship between PRI and photosynthetic radiation use efficiency for top-canopy leaves across species, functional types, and nutrient treatments suggests that relative photosynthetic rates could be derived with the “view from above” provided by remote reflectance measurements if issues of canopy and stand structure can be resolved. KW - Biomedizin & Life Sciences ER - TY - JOUR ID - gamon1999 AU - Gamon, J. A. AU - Surfus, J. S. TI - Assessing leaf pigment content and activity with a reflectometer UR - http://dx.doi.org/10.1046/j.1469-8137.1999.00424.x DO - 10.1046/j.1469-8137.1999.00424.x PR - Cambridge University Press T2 - New Phytologist PY - 1999 SN - 1469-8137 VL - 143 IS - 1 SP - 105–117 AB - This study explored reflectance indices sampled with a ‘leaf reflectometer’ as measures of pigment content for leaves of contrasting light history, developmental stage and functional type (herbaceous annual versus sclerophyllous evergreen). We employed three reflectance indices: a modified normalized difference vegetation index (NDVI), an index of chlorophyll content; the red/green reflectance ratio (RRED∶RGREEN), an index of anthocyanin content; and the change in photochemical reflectance index upon dark–light conversions (ΔPRI), an index of xanthophyll cycle pigment activity. In Helianthus annuus (sunflower), xanthophyll cycle pigment amounts were linearly related to growth light environment; leaves in full sun contained approximately twice the amount of xanthophyll cycle pigments as leaves in deep shade, and at midday a larger proportion of these pigments were in the photoprotective, de-epoxidized forms relative to shade leaves. Reflectance indices also revealed contrasting patterns of pigment development in leaves of contrasting structural types (annual versus evergreen). In H. annuus sun leaves, there was a remarkably rapid increase in amounts of both chlorophyll and xanthophyll cycle pigments along a leaf developmental sequence. This pattern contrasted with that of Quercus agrifolia (coast live oak, a sclerophyllous evergreen), which exhibited a gradual development of both chlorophyll and xanthophyll cycle pigments along with a pronounced peak of anthocyanin pigment content in newly expanding leaves. These temporal patterns of pigment development in Q. agrifolia leaves suggest that anthocyanins and xanthophyll cycle pigments serve complementary photoprotective roles during early leaf development. The results illustrate the use of reflectance indices for distinguishing divergent patterns of pigment activity in leaves of contrasting light history and functional type. KW - leaf development, leaf pigments, anthocyanins, chlorophyll, xanthophyll cycle, leaf reflectometer, reflectance indices, photoprotection ER - TY - CONF ID - gandia2004 AU - Gandia, S. AU - Fernández, G. AU - García, J. C. AU - & Moreno, J. TI - Retrieval of vegetation biophysical variables from CHRIS/PROBA data in the SPARC campaing T2 - Proceedings of the 2nd CHRISProba Workshop ESAESRIN Frascati Italy 2830 PY - 2004 AB - In the context of the SPARC campaign, a total of 10 different view angle images are available from CHRIS/PROBA data, all of them acquired in Mode 1 (62 spectral bands). These data make possible to test some of the algorithms developed to extract vegetation biophysical variables from high-spectral resolution data with multiangular capabilities, in the context of the SPECTRA mission. Validation of retrievals with the large dataset of ground measurements that is available in SPARC represents a unique opportunity to exploit the innovative CHRIS/PROBA data. Variability in ground measurements was evaluated by statistical techniques, according to the sampling used in the data collection. Two different approaches have been followed in the retrieval of vegetation biophysical variables. First, a large number of spectral indices have been tested with the available spectral information. The second method used is based on model inversion techniques. A combination of adapted versions of PROSPECT 1, and SAIL 2, models have been tested in forward mode, by using all available ground measurements to reproduce the top-of-canopy reflectance, and then compare these forward simulations with atmospherically corrected CHRIS data. ER - TY - JOUR ID - garrigues2008 AU - Garrigues, S. AU - Shabanov, N. V. AU - Swanson, K. AU - Morisette, J. T. AU - Baret, F. AU - Myneni, R. B. TI - Intercomparison and sensitivity analysis of Leaf Area Index retrievals from LAI-2000, AccuPAR, and digital hemispherical photography over croplands UR - http://www.sciencedirect.com/science/article/pii/S0168192308000683 DO - 10.1016/j.agrformet.2008.02.014 T2 - Agricultural and Forest Meteorology PY - 2008 SN - 0168-1923 VL - 148 IS - 8–9 SP - 1193-1209 KW - Effective Plant Area Index KW - Gap fraction KW - Optical techniques KW - LAI-2000 KW - AccuPAR KW - Digital Hemispherical Photograph KW - LAI validation ER - TY - JOUR ID - garson2003 AU - Garson, D. Caraux AU - Lacaze, B. TI - Monitoring Leaf Area Index of Mediterranean oak woodlands: Comparison of remotely-sensed estimates with simulations from an ecological process-based model UR - http://dx.doi.org/10.1080/0143116021000024267 DO - 10.1080/0143116021000024267 T2 - International Journal of Remote Sensing PY - 2003 DA - 2003/01/01 SN - 0143-1161 VL - 24 IS - 17 SP - 3441-3456 AB - Annual vegetation abundance mapping was carried out within the DeMon II European project over a period of 12 years (1984-1996). The project relied on advanced satellite-based methods for spatial and temporal monitoring of Mediterranean oak woodlands by means of a series of Landsat Thematic Mapper (TM) satellite data. A standardized approach developed previously focuses on the Languedoc site, Hautes Garrigues, a typical sensitive Mediterranean region, but now recovering after centuries of grazing and agricultural activities. After geometric and radiometric rectification of nine full Landsat TM scenes with a refined correction in a smaller area of 75 km 2 75 km, a GIS database was created containing satellite data, thematic maps of vegetation, geological maps, climatic data and field measurements. An empirical relation between radiometric ground truth measurements and satellite derived Normalized Difference Vegetation Index (NDVI) allows us to derive Leaf Area Index (LAI). An ecological process-based model (Forest BGC) has been adapted to simulate ecosystem processes in a satisfying way at a local scale. Consistent results were obtained from remote sensing data and from simulations at a local scale, suggesting the possible use of remote-sensing data to monitor vegetation abundance changes at a regional scale. Without considering human disturbances, it can be noted that not much variation of LAI induced by natural factors can be detected over the considered 12-year period. ER - TY - JOUR ID - gitelson2002 AU - Gitelson, A. A. AU - Kaufman, Y. J. AU - Stark, R. AU - Rundquist, D. TI - Novel algorithms for remote estimation of vegetation fraction UR - http://www.ingentaconnect.com/content/els/00344257/2002/00000080/00000001/art00289 http://dx.doi.org/10.1016/S0034-4257(01)00289-9 DO - 10.1016/s0034-4257(01)00289-9 T2 - Remote Sensing of Environment PY - 2002 VL - 80 IS - 1 SP - 76-87 AB -

Spectral properties of a wheat canopy with vegetation fraction (VF) from 0% to 100% in visible and near-infrared (NIR) ranges of the spectrum were studied in order to devise a technique for remote estimation of VF. When VF was <60%, from emergence till middle of the elongation stage, four distinct, and quite independent, spectral bands of reflectance existed in the visible range of the spectrum: 400 to 500 nm, 530 to 600 nm, near 670 nm, and around 700 nm. When VF was between 60% and 100%, reflectance in the NIR leveled off or even decreases with an increase of VF. The decreased reflectance in the NIR, occurring at or near the midseason, can be a limiting factor in the use of that spectral region for VF estimation. It was found that for VF>60%, the information content of reflectance spectra in visible range can be expressed by only two independent pairs of spectral bands: (1) the blue from 400 to 500 nm and the red near 670 nm; (2) the green around 550 nm and the red edge region near 700 nm. We propose using only the visible range of the spectrum to quantitatively estimate VF. The green (as well as a 700-nm band) and the red (near 670 nm) reflectances were used in developing new indices, which were linearly proportional to wheat VF ranging from 0% to 100%. The Atmospherically Resistant Vegetation Index (ARVI) concept was used to correct indices for atmospheric effects. Visible Atmospherically Resistant Index in the form VARI=(Rgreen-Rred)/(Rgreen+Rred-Rblue) was found to be minimally sensitive to atmospheric effects allowing estimation of VF with an error of <10% in a wide range of atmospheric optical thickness. Validation of the newly suggested technique was carried out using wheat independent data sets and reflectance data obtained for cornfields in Nebraska. Predicted green VF was compared with retrieved from digital images. Despite the fact that the reflectance contrast among the visible channels is much smaller than between the visible and NIR, the sensitivity of suggested indices to moderate to high values of VF is much higher than for the Normalized Difference Vegetation Index (NDVI), and the error in VF prediction did not exceed 10%. Suggested indices will complement the widely used NDVI, ARVI, Soil Adjusted Vegetation Index (SAVI) and others, which are based on the red and the NIR bands in VF estimation, and also Green Atmospherically Resistant Index (GARI), which is based on the green and the NIR bands.

ER - TY - JOUR ID - gitelson1997 AU - Gitelson, A. A. AU - Merzlyak, M. N. TI - Remote estimation of chlorophyll content in higher plant leaves UR - http://dx.doi.org/10.1080/014311697217558 DO - 10.1080/014311697217558 PR - Taylor & Francis T2 - International Journal of Remote Sensing PY - 1997 SN - 0143-1161 VL - 18 IS - 12 SP - 2691-2697 AB - Abstract Indices for the non-destructive estimation of chlorophyll content were formulated using various instruments to measure reflectance and absorption spectra in visible and near-infrared ranges, as well as chlorophyll contents from several non-related species from different climatic regions. The proposed new algorithms are simple ratios between percentage reflectance at spectral regions that are highly sensitive (540 to 630nm and around 700nm) and insensitive (nearinfrared) to variations in chlorophyll content: R NIR / R 700 and R NIR / R 550. The developed algorithms predicting leaf chemistry from the leaf optics were validated for nine plant species in the range of chlorophyll content from 0.27 to 62.9mug cm -2. An error of less than 4.2 mugcm -2 in chlorophyll prediction was achieved. The use of green and red (near 700nm) channels increases the sensitivity of NDVI to chlorophyll content by about five-fold. ER - TY - GEN ID - gitelson2004 AU - Gitelson, Anatoly A. TI - Wide Dynamic Range Vegetation Index for Remote Quantification of Biophysical Characteristics of Vegetation UR - http://www.sciencedirect.com/science/article/pii/S0176161704705726 DO - 10.1078/0176-1617-01176 T2 - Journal of Plant Physiology PY - 2004 SN - 0176-1617 VL - 161 IS - 2 SP - 165-173 AB - Summary The Normalized Difference Vegetation Index (NDVI) is widely used for monitoring, analyzing, and mapping temporal and spatial distributions of physiological and biophysical characteristics of vegetation. It is well documented that the NDVI approaches saturation asymptotically under conditions of moderate-to-high aboveground biomass. While reflectance in the red region (ρred) exhibits a nearly flat response once the leaf area index (LAI) exceeds 2, the near infrared (NIR) reflectance (ρNIR) continue to respond significantly to changes in moderate-to-high vegetation density (LAI from 2 to 6) in crops. However, this higher sensitivity of the ρNIR has little effect on NDVI values once the ρNIR exceeds 30 %. In this paper a simple modification of the NDVI was proposed. The Wide Dynamic Range Vegetation Index, WDRVI = (a * ρNIR-ρred)/(a * ρNIR+ρred), where the weighting coefficient a has a value of 0.1–0.2, increases correlation with vegetation fraction by linearizing the relationship for typical wheat, soybean, and maize canopies. The sensitivity of the WDRVI to moderate-to-high LAI (between 2 and 6) was at least three times greater than that of the NDVI. By enhancing the dynamic range while using the same bands as the NDVI, the WDRVI enables a more robust characterization of crop physiological and phenological characteristics. Although this index needs further evaluation, the linear relationship with vegetation fraction and much higher sensitivity to change in LAI will be especially valuable for precision agriculture and monitoring vegetation status under conditions of moderate-to-high density. It is anticipated that the new index will complement the NDVI and other vegetation indices that are based on the red and NIR spectral bands. KW - leaf area index KW - reflectance KW - remote estimation KW - vegetation fraction KW - vegetation index ER - TY - JOUR ID - gitelson1999 AU - Gitelson, Anatoly A. AU - Buschmann, Claus AU - Lichtenthaler, Hartmut K. TI - The Chlorophyll Fluorescence Ratio F735/F700 as an Accurate Measure of the Chlorophyll Content in Plants UR - http://www.sciencedirect.com/science/article/pii/S0034425799000231 DO - 10.1016/s0034-4257(99)00023-1 T2 - Remote Sensing of Environment PY - 1999 SN - 0034-4257 VL - 69 IS - 3 SP - 296-302 AB - A remote sensing technique is presented to estimate the chlorophyll content in higher plants. The ratio between chlorophyll fluorescence at 735 nm and in the range 700–710 nm, F735/F700 was found to be linearly proportional to the chlorophyll content (with determination coefficient, r2, more than 0.95), and, thus, this ratio can be used as a precise indicator of chlorophyll content in plant leaves. This new chlorophyll fluorescence ratio indicates chlorophyll levels with high precision- the error in chlorophyll prediction over a wide range of chlorophyll content (from 41 to 675 mg m−2) was less than 40 mg m−2. The technique was tested and validated in three plant species: beech (Fagus sylvatica L.), elm (Ulmus minor Miller), and wild vine (Parthenocissus tricuspidata L.). ER - TY - JOUR ID - gitelson1996 AU - Gitelson, Anatoly A. AU - Kaufman, Yoram J. AU - Merzlyak, Mark N. TI - Use of a green channel in remote sensing of global vegetation from EOS-MODIS DO - 10.1016/s0034-4257(96)00072-7 T2 - Remote Sensing of Environment PY - 1996 SN - 0034-4257 VL - 58 IS - 3 SP - 289-298 AB - Most animals use a “green” spectral range to remotely sense the presence and vitality of vegetation. While humans possess the same ability in their eyes, man-made space-borne sensors that sense evolution of global vegetation, have so far used a combination of the red and near infrared channels instead. In this article we challenge this approach, using measurements of reflectance spectra from 400 nm to 750 nm with spectral resolution of 2 nm, with simultaneous determination of pigment concentrations of mature and autumn senescing leaves. We show that, for a wide range of leaf greenness, the maximum sensitivity of reflectance coincides with the red absorption maximum of chlorophyll-a (Chl-a) at 670 nm. However, for yellow-green to green leaves (with Chl-a more than 3–5 μg/cm2), the reflectance near 670 nm is not sensitive to chlorophyll concentration because of saturation of the relationship of absorptions versus chlorophyll concentration. Maximum sensitivity of Chl-a concentration for a wide range of its variation (0.3–45 μg/cm2) was found, not surprisingly so, around the green band from 520 nm to 630 nm and also near 700 nm. We found that the inverse of the reflectance in the green band was proportional to Chl-a concentration with correlation r2 > 0.95. This band will be present on several future satellite sensors with a global view of vegetation (SeaWiFS to be launched in 1996, Polder on ADEOS-1 also in 1996, and MODIS on EOS in 1998 and 2000). New indexes that use the green channel and are resistant to atmospheric effects are developed. A green NDVI = (ϱnir − ϱgreen(ϱnir + ϱgreen) was tested for a range of Chl-a from 0.3 μg/cm2 to 45 μg/cm2, and found to have an error in the chlorophyll a derivation at leaf level of less than 3 μg/cm2. The new index has wider dynamic range than the NDVI and is, on average, at least five times more sensitive to Chl-a concentration. A green atmospherically resistant vegetation index (GARI), tailored on the concept of ARVI (Kaufman and Tanré, 1992), is developed and is expected to be as resistant to atmospheric effects as ARVI but more sensitive to a wide range of Chl-a concentrations. While NDVI and ARVI are sensitive to vegetation fraction and to rate of absorption of photosynthetic solar radiation, a green vegetation index like GARI should be added to sense the concentration of chlorophyll, to measure the rate of photosynthesis and to monitor plant stress. ER - TY - JOUR ID - gitelson1996-2 AU - Gitelson, Anatoly A. AU - Merzlyak, Mark N. AU - Lichtenthaler, Hartmut K. TI - Detection of Red Edge Position and Chlorophyll Content by Reflectance Measurements Near 700 nm UR - http://www.sciencedirect.com/science/article/pii/S0176161796802859 DO - 10.1016/s0176-1617(96)80285-9 T2 - Journal of Plant Physiology PY - 1996 SN - 0176-1617 VL - 148 IS - 3–4 SP - 501-508 AB - Summary Pigment contents was determined in and high spectral resolution reflectance measurements were acquired for spring, summer and autumn maple and horse chestnut leaves covering a wide range of chlorophyll content. Consistent and diagnostic differences in the red edge range (680-750 nm) of the reflectance spectrum were obtained for the various leaf samples of both species studied. This included the differences in the wavelength position of the red edge and in the reflectance values in the range of 690 to 710 nm. Both characteristics were found to be dependent on leaf chlorophyll concentration. The first derivative of reflectance spectra showed four peaks at 685-706, 710, 725 and 740 nm that were dependent in different degree on leaf age and pigment concentration in the leaves. The position and the magnitude of the first peak showed a high correlation with the leaf chlorophyll concentration. Reflectance at 700 nm was linearly dependent on the wavelength of the first peak. Variation of inflection point position with change in chlorophyll content was found small for yellow-green to dark green leaves (total chlorophyll in the range above 10 nmol/cm2). Reflectance near 700 nm was found to be a very sensitive indicator of the red edge position as well as of chlorophyll concentration. The ratio of reflectances at 750 nm to that near 700 nm (R750/R700) was directly proportional (correlation r2 > 0.95) to chlorophyll concentration. The ratio R750/R700 as a newly established index for non-invasive in-vivo chlorophyll determination was tested by independent data sets in the range of Chl contents from 0.6 to more than 60nmol/cm2 of maple and chestnut leaves with an estimation error of Chl of less than 3.7 nmol/cm2. KW - chlorophyll content KW - reflectance spectra of leaves KW - red edge position KW - vegetation indices ER - TY - CONF ID - gitelson2001 AU - Gitelson, Anatoly A. AU - Merzlyak, Mark N. AU - Zur, Y. AU - Stark, R. AU - Gritz, U. TI - Non-destructive and remote sensing techniques for estimation of vegetation status T2 - Third European Conference on Precision Agriculture CY - Montpellier, France PY - 2001 VL - 1 SP - 301-306 ER - TY - JOUR ID - gitelson2003 AU - Gitelson, Anatoly A. AU - Viña, Andrés AU - Arkebauer, Timothy J. AU - Rundquist, Donald C. AU - Keydan, Galina: Leavitt, Bryan TI - Remote estimation of leaf area index and green leaf biomass in maize canopies DO - 10.1029/2002gl016450 PR - AGU T2 - Geophys. Res. Lett. PY - 2003 SN - 0094-8276 VL - 30 IS - 5 SP - 1248 AB - Leaf area index (LAI) is an important variable for climate modeling, estimates of primary production, agricultural yield forecasting, and many other diverse studies. Remote sensing provides a considerable potential for estimating LAI at local to regional and global scales. Several spectral vegetation indices have been proposed, but their capacity to estimate LAI is highly reduced at moderate-to-high LAI. In this paper, we propose a technique to estimate LAI and green leaf biomass remotely using reflectances in two spectral channels either in the green around 550 nm, or at the red edge near 700 nm, and in the NIR (beyond 750 nm). The technique was tested in agricultural fields under a maize canopy, and proved suitable for accurate estimation of LAI ranging from 0 to more than 6. KW - Remote sensing, Instruments and techniques. General or miscellaneous ER - TY - JOUR ID - gitelson1994 AU - Gitelson, Anatoly AU - Merzlyak, Mark N. TI - Quantitative estimation of chlorophyll-a using reflectance spectra: Experiments with autumn chestnut and maple leaves DO - 10.1016/1011-1344(93)06963-4 T2 - Journal of Photochemistry and Photobiology B: Biology PY - 1994 SN - 1011-1344 VL - 22 IS - 3 SP - 247-252 AB - The signature analysis of reflectance spectra of autumn Aesculus hippocastanum L. and Acer platanoides L. leaves revealed spectral bands maximally (near 550 and 705 nm) and minimally (at more than 750 nm) sensitive to variation in chlorophyll content, which can serve as sensitive indicators of early stages of leaf senescence. Several functions of reflectance directly proportional to chlorophyll-a have been found. These make it possible to determine chlorophyll accurately with a background of high pigment concentration. KW - Chlorophyll-a, Leaf, Reflectance spectrum ER - TY - JOUR ID - glenn2010 AU - Glenn, E. P. AU - Nagler, P. L. AU - Huete, A. R. TI - Vegetation Index Methods for Estimating Evapotranspiration by Remote Sensing UR - ://WOS:000284318100001 DO - 10.1007/s10712-010-9102-2 T2 - Surveys in Geophysics PY - 2010 DA - Dec SN - 0169-3298 VL - 31 IS - 6 SP - 531-555 N1 - ISI Document Delivery No.: 681LY Times Cited: 7 Cited Reference Count: 112 Glenn, Edward P. Nagler, Pamela L. Huete, Alfredo R. Springer Dordrecht AB - Evapotranspiration (ET) is the largest term after precipitation in terrestrial water budgets. Accurate estimates of ET are needed for numerous agricultural and natural resource management tasks and to project changes in hydrological cycles due to potential climate change. We explore recent methods that combine vegetation indices (VI) from satellites with ground measurements of actual ET (ET(a)) and meteorological data to project ET(a) over a wide range of biome types and scales of measurement, from local to global estimates. The majority of these use time-series imagery from the Moderate Resolution Imaging Spectrometer on the Terra satellite to project ET over seasons and years. The review explores the theoretical basis for the methods, the types of ancillary data needed, and their accuracy and limitations. Coefficients of determination between modeled ET(a) and measured ET(a) are in the range of 0.45-0.95, and root mean square errors are in the range of 10-30% of mean ET(a) values across biomes, similar to methods that use thermal infrared bands to estimate ET(a) and within the range of accuracy of the ground measurements by which they are calibrated or validated. The advent of frequent-return satellites such as Terra and planed replacement platforms, and the increasing number of moisture and carbon flux tower sites over the globe, have made these methods feasible. Examples of operational algorithms for ET in agricultural and natural ecosystems are presented. The goal of the review is to enable potential end-users from different disciplines to adapt these methods to new applications that require spatially-distributed ET estimates. KW - NDVI KW - Enhanced Vegetation Index KW - Fluxnet KW - MODIS KW - Remote sensing KW - land-surface evaporation KW - basal crop coefficients KW - colorado river delta KW - modis satellite data KW - canopy reflectance KW - potential evapotranspiration KW - riparian evapotranspiration KW - meteorological data KW - eddy covariance KW - energy-balance ER - TY - JOUR ID - glenn2008 AU - Glenn, Edward AU - Huete, Alfredo AU - Nagler, Pamela AU - Nelson, Stephen TI - Review - Relationship Between Remotely-sensed Vegetation Indices, Canopy Attributes and Plant Physiological Processes: What Vegetation Indices Can and Cannot Tell Us About the Landscape UR - http://www.mdpi.com/1424-8220/8/4/2136/ DO - doi:10.3390/s8042136 T2 - Sensors PY - 2008 VL - 8 IS - 4 SP - 2136-2160 ER - TY - GEN ID - gobron2000 AU - Gobron, N. AU - Pinty, B. AU - Verstraete, M. M. AU - Widlowski, J. L. TI - Advanced vegetation indices optimized for up-coming sensors: Design, performance, and applications DO - 10.1109/36.885197 T2 - Geoscience and Remote Sensing, IEEE Transactions on PY - 2000 SN - 0196-2892 VL - 38 IS - 6 SP - 2489-2505 AB - This paper describes the implementation of a physical and mathematical approach to designing advanced vegetation indices optimized for future sensors operating in the solar domain such as the medium resolution imaging spectrometer (MERIS), the global imager (GLI), and the VEGETATION instrument, and proposes an initial evaluation of such indices. These optimized indices address sensor-specific issues such as dependencies with respect to the actual spectral response of the sensor as well as the natural sensitivity of remote sensing measurements to illumination and observing geometry, to atmospheric absorption and scattering effects, and to soil color or brightness changes. The derivation of vegetation index formulae optimized to estimate the same vegetation property fraction of absorbed photosynthetically active radiation (FAPAR) from data generated by different sensors allows the comparison of their relative performances compared with existing vegetation indices, both from a theoretical and experimental point of view and permits the creation of global products, as well as the constitution of long time series from multiple sensors. KW - geophysical techniques, remote sensing, vegetation mapping, FAPAR, GLI, IR, MERIS, SPOT, VEGETATION, advanced vegetation indices, formula, fraction of absorbed photosynthetically active radiation, geophysical measurement technique, global imager, infrared, mathematical approach, medium resolution imaging spectrometer, optical method, vegetation index, visible ER - TY - GEN ID - goel1994 AU - Goel, Narendra S. AU - Qin, Wenhan TI - Influences of canopy architecture on relationships between various vegetation indices and LAI and Fpar: A computer simulation UR - http://dx.doi.org/10.1080/02757259409532252 DO - 10.1080/02757259409532252 PR - Taylor & Francis T2 - Remote Sensing Reviews PY - 1994 DA - 1994/10/01 SN - 0275-7257 VL - 10 IS - 4 SP - 309-347 AB - Abstract Vegetation Indices (VIs) are often used to estimate important biophysical parameters, like LAI and Fpar, from vegetation canopy reflectance data. In this study, a three?dimensional model (Diana) is utilized to generate architecturally realistic tree and crop canopies in various development stages and to calculate bidirectional reflectance factors in the principal plane. We investigate the influence of various factors like soil brightness, optical properties of canopy elements, leaf angle distribution, spacing distance between plants and solar and view geometries on relationships between VI and Fpar, LAI and percentage ground cover (GC) in order to determine optimal VI and viewing conditions for the estimation of Fpar and LAI/GC. These simulation studies suggest that: (1) in most cases, Vis using off?nadir reflectances are more informative and useful than those based on nadir reflectances; (2) the optimal VI and sun/view geometries are usually different for inferring different parameters, depending on canopy architecture; (3) LAI can be practically estimated by VI only for homogeneous canopies while GC and Fpar can be inferred even for an inhomogeneous canopy; and (4) when optical properties of vegetation elements vary within a canopy, neither LAI/GC nor Fpar can be estimated by means of VI method with an acceptable accuracy. ER - TY - JOUR ID - goel2003 AU - Goel, P. K. AU - Prasher, S. O. AU - Landry, J. A. AU - Patel, R. M. AU - Viau, A. A. TI - Hyperspectral image classification to detect weed infestations and nitrogen status in corn UR - ://WOS:000182949700039 T2 - Transactions of the Asae PY - 2003 DA - Mar-Apr SN - 0001-2351 VL - 46 IS - 2 SP - 539-550 N1 - ISI Document Delivery No.: 679YN Times Cited: 9 Cited Reference Count: 47 Goel, PK Prasher, SO Landry, JA Patel, RM Viau, AA Amer soc agricultural engineers St joseph AB - The potential of hyperspectral aerial imagery for the detection of weed infestation and nitrogen fertilization level in a corn (Zea mays L.) crop was evaluated. A Compact Airborne Spectrographic Imager (CASI) was used to acquire hyperspectral data over a field experiment laid out at the Lods Agronomy Research Centre of Macdonald Campus, McGill University, Quebec, Canada. Corn was grown under four weed management strategies (no weed control, control of grasses, control of broadleaf weeds, and full weed control) factorally combined with nitrogen fertilization rates of 60, 120, and 250 N kg/ha. The aerial image was acquired at the tasseling stage, which was 66 days after planting. For the classification of remote sensing imagery, various widely used supervised classification algorithms (maximum likelihood, minimum distance, Mahalanobis distance, parallelepiped, and binary coding) and more sophisticated classification approaches (spectral angle mapper and linear spectral unmixing) were investigated. It was difficult to distinguish the combined effect of both weed and nitrogen treatments simultaneously. However, higher classification accuracies were obtained when only one factor, either weed or nitrogen treatment, was considered. With different classifiers, depending on the factors considered for the classification, accuracies ranged from 65.84% to 99.46%. No single classifier was found useful for all the conditions. KW - corn KW - hyperspectral KW - image classification KW - nitrogen KW - remote sensing KW - weeds KW - multispectral digital imagery KW - no-till corn KW - light reflectance KW - glycine-max KW - remote KW - yield KW - management KW - variability KW - growth KW - field ER - TY - JOUR ID - gonz_lez-sanpedro2008 AU - González-Sanpedro, MC AU - Le Toan, T AU - Moreno, J AU - Kergoat, L AU - Rubio, E TI - Seasonal variations of leaf area index of agricultural fields retrieved from Landsat data T2 - Remote Sensing of Environment PY - 2008 VL - 112 SP - 810-824 ER - TY - CONF ID - guyot1988 AU - Guyot, G. AU - Baret, F. AU - Major, D. J. TI - High spectral resolution: Determination of specral shifts between the red and the near infrared T2 - International Archives of Photogrammetry and Remote Sensing CY - XVIth ISPRS Congress, Technical Commission VII: Interpretation of Photographic and Remote Sensing Data , July 1-10, 1988, Kyoto, Japan PY - 1988 VL - 11 SP - 750−760 ER - TY - JOUR ID - haboudane2004 AU - Haboudane, Driss AU - Miller, John R. AU - Pattey, Elizabeth AU - Zarco-Tejada, Pablo J. AU - Strachan, Ian B. TI - Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture UR - http://www.sciencedirect.com/science/article/pii/S0034425704000264 DO - 10.1016/j.rse.2003.12.013 T2 - Remote Sensing of Environment PY - 2004 SN - 0034-4257 VL - 90 IS - 3 SP - 337-352 AB - A growing number of studies have focused on evaluating spectral indices in terms of their sensitivity to vegetation biophysical parameters, as well as to external factors affecting canopy reflectance. In this context, leaf and canopy radiative transfer models are valuable for modeling and understanding the behavior of such indices. In the present work, PROSPECT and SAILH models have been used to simulate a wide range of crop canopy reflectances in an attempt to study the sensitivity of a set of vegetation indices to green leaf area index (LAI), and to modify some of them in order to enhance their responsivity to LAI variations. The aim of the paper was to present a method for minimizing the effect of leaf chlorophyll content on the prediction of green LAI, and to develop new algorithms that adequately predict the LAI of crop canopies. Analyses based on both simulated and real hyperspectral data were carried out to compare performances of existing vegetation indices (Normalized Difference Vegetation Index [NDVI], Renormalized Difference Vegetation Index [RDVI], Modified Simple Ratio [MSR], Soil-Adjusted Vegetation Index [SAVI], Soil and Atmospherically Resistant Vegetation Index [SARVI], MSAVI, Triangular Vegetation Index [TVI], and Modified Chlorophyll Absorption Ratio Index [MCARI]) and to design new ones (MTVI1, MCARI1, MTVI2, and MCARI2) that are both less sensitive to chlorophyll content variations and linearly related to green LAI. Thorough analyses showed that the above existing vegetation indices were either sensitive to chlorophyll concentration changes or affected by saturation at high LAI levels. Conversely, two of the spectral indices developed as a part of this study, a modified triangular vegetation index (MTVI2) and a modified chlorophyll absorption ratio index (MCARI2), proved to be the best predictors of green LAI. Related predictive algorithms were tested on CASI (Compact Airborne Spectrographic Imager) hyperspectral images and, then, validated using ground truth measurements. The latter were collected simultaneously with image acquisition for different crop types (soybean, corn, and wheat), at different growth stages, and under various fertilization treatments. Prediction power analysis of proposed algorithms based on MCARI2 and MTVI2 resulted in agreements between modeled and ground measurement of non-destructive LAI, with coefficients of determination (r2) being 0.98 for soybean, 0.89 for corn, and 0.74 for wheat. The corresponding RMSE for LAI were estimated at 0.28, 0.46, and 0.85, respectively. KW - Hyperspectral KW - Spectral indices KW - Green LAI KW - Prediction algorithms KW - Chlorophyll content KW - Precision agriculture ER - TY - JOUR ID - haboudane2002 AU - Haboudane, Driss AU - Miller, John R. AU - Tremblay, Nicolas AU - Zarco-Tejada, Pablo J. AU - Dextraze, Louise TI - Integrated narrow-band vegetation indices for prediction of crop chlorophyll content for application to precision agriculture UR - http://www.sciencedirect.com/science/article/pii/S0034425702000184 DO - 10.1016/s0034-4257(02)00018-4 T2 - Remote Sensing of Environment PY - 2002 SN - 0034-4257 VL - 81 IS - 2–3 SP - 416-426 AB - Recent studies have demonstrated the usefulness of optical indices from hyperspectral remote sensing in the assessment of vegetation biophysical variables both in forestry and agriculture. Those indices are, however, the combined response to variations of several vegetation and environmental properties, such as Leaf Area Index (LAI), leaf chlorophyll content, canopy shadows, and background soil reflectance. Of particular significance to precision agriculture is chlorophyll content, an indicator of photosynthesis activity, which is related to the nitrogen concentration in green vegetation and serves as a measure of the crop response to nitrogen application. This paper presents a combined modeling and indices-based approach to predicting the crop chlorophyll content from remote sensing data while minimizing LAI (vegetation parameter) influence and underlying soil (background) effects. This combined method has been developed first using simulated data and followed by evaluation in terms of quantitative predictive capability using real hyperspectral airborne data. Simulations consisted of leaf and canopy reflectance modeling with PROSPECT and SAILH radiative transfer models. In this modeling study, we developed an index that integrates advantages of indices minimizing soil background effects and indices that are sensitive to chlorophyll concentration. Simulated data have shown that the proposed index Transformed Chlorophyll Absorption in Reflectance Index/Optimized Soil-Adjusted Vegetation Index (TCARI/OSAVI) is both very sensitive to chlorophyll content variations and very resistant to the variations of LAI and solar zenith angle. It was therefore possible to generate a predictive equation to estimate leaf chlorophyll content from the combined optical index derived from above-canopy reflectance. This relationship was evaluated by application to hyperspectral CASI imagery collected over corn crops in three experimental farms from Ontario and Quebec, Canada. The results presented here are from the L'Acadie, Quebec, Agriculture and Agri-Food Canada research site. Images of predicted leaf chlorophyll content were generated. Evaluation showed chlorophyll variability over crop plots with various levels of nitrogen, and revealed an excellent agreement with ground truth, with a correlation of r2=.81 between estimated and field measured chlorophyll content data. ER - TY - JOUR ID - hancock2007 AU - Hancock, D. W. AU - Dougherty, C. T. TI - Relationships between blue- and red-based vegetation indices and leaf area and yield of alfalfa UR - ://WOS:000251409000038 DO - 10.2135/cropsci2007.01.0031 T2 - Crop Science PY - 2007 DA - Nov-Dec SN - 0011-183X VL - 47 IS - 6 SP - 2547-2556 N1 - ISI Document Delivery No.: 237XF Times Cited: 1 Cited Reference Count: 30 Hancock, Dennis W. Dougherty, Charles T. Crop science soc amer Madison AB - The need for site-specific yield assessments of alfalfa (Medicago sativa L.) has spurred interest in developing methods to remotely sense biomass at harvest, Relationships between reflectance-based vegetation indices (Vis) and yield and yield-components of alfalfa have not been fully characterized. The objectives of this study were to evaluate the relationships between blue- and red-reflectance based Vis and canopy variables such as leaf area index (LAI), mass shoot(-1), shoot length, and alfalfa yield. Canopy reflectance was obtained with two reflectance spectrometers 1 d before each of five harvests in 2005 within rainfed and subsurface drip-irrigated alfalfa. Blue- and red-based normalized difference vegetation indices (NDVIs) and wide dynamic range vegetation indices (WDRVIs) at three levels of a near-infrared (NIR) reflectance-scalar ('alpha' = 0.1, 0.05, and 0.01) were calculated and regressed on alfalfa canopy variables. A quadratic-plateau model was used to determine when VIs no longer detected yield increments. Both blue- and red-based NDVIs and WDRVIs exhibited significant (P < 0.0001) saturative responses to LAI, yield components, and dry matter (DM) yield. Decreasing a widened the estimable yield range (0-1.82 vs. 0-2.76 Mg ha(-1) and 0-2.60 vs. 0-3.74 Mg ha-1, respectively) of both blue- and red-based WDRVIs. Significant (P < 0.0001) yield regression models within the effective range of the VIs (://WOS:000293038700032 DO - 10.1016/j.ecolmodel.2010.11.011 T2 - Ecological Modelling PY - 2011 DA - Jul SN - 0304-3800 VL - 222 IS - 14 SP - 2530-2541 N1 - ISI Document Delivery No.: 796GB Times Cited: 1 Cited Reference Count: 59 Hu, Shi Mo, Xingguo 973 Basic Research Project[2010CB428404]; China MOST[0911]; CAS[KZCX2-YW-Q06-1] This study was jointly supported by 973 Basic Research Project (2010CB428404), International Cooperation Project (0911) of China MOST, and the Innovation project of CAS (KZCX2-YW-Q06-1). Many thanks to the two anonymous reviews and the Editor whose pertinent comments have greatly improved the quality of this paper. Elsevier science bv Amsterdam Si AB - A process-based crop growth model (Vegetation Interface Processes (VIP) model) is used to estimate crop yield with remote sensing over the North China Plain. Spatial pattern of the key parameter-maximum catalytic capacity of Rubisco (V(cmax)) for assimilation is retrieved from Normalized Difference of Vegetation Index (NDVI) from Terra-MODIS and statistical yield records. The regional simulation shows that the agreements between the simulated winter wheat yields and census data at county-level are quite well with R(2) being 0.41-0.50 during 2001-2005. Spatial variability of photosynthetic capacity and yield in irrigated regions depend greatly on nitrogen input. Due to the heavy soil salinity, the photosynthetic capacity and yield in coastal region is less than 50 mu mol C m(-2) s(-1) and 3000 kg ha(-1), respectively, which are much lower than that in non-salinized region, 84.5 mu mol C m(-2) s(-1) and 5700 kg ha(-1). The predicted yield for irrigated wheat ranges from 4000 to 7800 kg ha(-1), which is significantly larger than that of rainfed, 1500-3000 kg ha(-1). According to the path coefficient analysis, nitrogen significantly affects yield, by which water exerts noticeably indirect influences on yield. The effect of water on yield is regulated, to a certain extent, by crop photosynthetic capacity and nitrogen application. It is believed that photosynthetic parameters retrieved from remote sensing are reliable for regional production prediction with a process-based model. (C) 2010 Elsevier B.V. All rights reserved. KW - Remote sensing data KW - V(cmax) KW - VIP model KW - water-use efficiency KW - north china plain KW - winter-wheat KW - durum-wheat KW - gas-exchange KW - elevated co2 KW - grain-yield KW - corn yield KW - ndvi data KW - nitrogen ER - TY - GEN ID - huete1988 AU - Huete, A. R. TI - A soil-adjusted vegetation index (SAVI) UR - http://www.sciencedirect.com/science/article/pii/003442578890106X DO - 10.1016/0034-4257(88)90106-x T2 - Remote Sensing of Environment PY - 1988 SN - 0034-4257 VL - 25 IS - 3 SP - 295-309 AB - A transformation technique is presented to minimize soil brightness influences from spectral vegetation indices involving red and near-infrared (NIR) wavelengths. Graphically, the transformation involves a shifting of the origin of reflectance spectra plotted in NIR-red wavelength space to account for first-order soil-vegetation interactions and differential red and NIR flux extinction through vegetated canopies. For cotton (Gossypium hirsutum L. var DPI-70) and range grass (Eragrosticslehmanniana Nees) canopies, underlain with different soil backgrounds, the transformation nearly eliminated soil-induced variations in vegetation indices. A physical basis for the soil-adjusted vegetation index (SAVI) is subsequently presented. The SAVI was found to be an important step toward the establishment of simple °lobal” that can describe dynamic soil-vegetation systems from remotely sensed data ER - TY - GEN ID - huete1992 AU - Huete, A. R. AU - Hua, G. AU - Qi, J. AU - Chehbouni, A. AU - van Leeuwen, W. J. D. TI - Normalization of multidirectional red and NIR reflectances with the SAVI UR - http://www.sciencedirect.com/science/article/pii/003442579290074T DO - 10.1016/0034-4257(92)90074-t T2 - Remote Sensing of Environment PY - 1992 SN - 0034-4257 VL - 41 IS - 2–3 SP - 143-154 AB - Directional reflectance measurements were made over a semidesert gramma (Bouteloua spp.) grassland at various times of the growing season. Azimuthal strings of view angle measurements from + 40° to − 40° were made for various solar zenith angles and soil moisture conditions. The sensitivity of the normalized difference vegetation index (NDVI) and the soil-adjusted vegetation index (SAVI) to these bidirectional measurements was assessed for purposes of improving remote temporal monitoring of vegetation activity. The NDVI response from the grassland canopy was strongly anisotropic about nadir view angles while the SAVI response was symmetric about nadir. This occurred for all sun angles, soil moisture condition, and grass densities. This enabled variations in SAVI-view angle response to be minimized with a cosine function. It is expected that this study will aid in improving the characterization of vegetation temporal activity from Landsat TM, SPOT, AVHRR, and the Earth Observing System MODIS sensor. ER - TY - JOUR ID - huete1988-2 AU - Huete, A. R. AU - Jackson, R. D. TI - Soil and atmosphere influences on the spectra of partial canopies UR - http://www.sciencedirect.com/science/article/pii/0034425788900430 DO - 10.1016/0034-4257(88)90043-0 T2 - Remote Sensing of Environment PY - 1988 SN - 0034-4257 VL - 25 IS - 1 SP - 89-105 AB - An atmospheric radiant transfer model was used to compare ground-measured radiances over partially vegetated canopies with their simulated responses at the top of a clear (100 km meteorological range) and a turbid (10 km) atmosphere. Radiance measurements in the first four bands of the Thematic Mapper were taken over incomplete cotton (Gossypium hirsutum L.) and Lehmann lovegrass (Eragrostis lehmanniana Nees) canopies with different soil backgrounds separately inserted underneath. Atmospheric influences on the spectra of partial canopies were found to be significantly dependent on the “brightness” of the underlying soil. The change in canopy red and near-infrared radiance between the ground and the top of the atmosphere was such that an increase, decrease, or no change could be observed, depending on the magnitude of the canopy substrate contribution. Both increasing soil “brightness” and atmospheric turbidity lowered the ratio (RVI) and normalized difference vegetation index values (NDVI). Consequently, atmospheric-induced RVI and NDVI degradation were greatest over canopies with darker soils and were not detectable over canopies with light-colored soils. In contrast, soil and atmospheric effects on the perpendicular vegetation index were independent with atmosphere degradation being similar across all soil backgrounds. Soil influences on vegetation indices from partial canopies were found to be of similar magnitude to those attributed to the atmosphere for the range of soil and atmosphere conditions examined here. ER - TY - JOUR ID - huete1997 AU - Huete, A. R. AU - Liu, H. Q. AU - Batchily, K. AU - van Leeuwen, W. TI - A comparison of vegetation indices over a global set of TM images for EOS-MODIS UR - http://www.sciencedirect.com/science/article/pii/S0034425796001125 DO - 10.1016/s0034-4257(96)00112-5 T2 - Remote Sensing of Environment PY - 1997 SN - 0034-4257 VL - 59 IS - 3 SP - 440-451 AB - A set of Landsat Thematic Mapper images representing a wide range of vegetation conditions from the NASA Landsat Pathfinder, global land cover test site (GLCTS) initiative were processed to simulate the Moderate Resolution Imaging Spectroradiometer (MODIS), global vegetation index imagery at 250 m pixel size resolution. The sites included boreal forest, temperate coniferous forest, temperate deciduous forest, tropical rainforest, grassland, savanna, and desert biomes. Differences and similarities in sensitivity to vegetation conditions were compared among various spectral vegetation indices (VIs). All VIs showed a qualitative relationship to variations in vegetation. However, there were significant differences among the VIs over desert, grassland, and forested biomes. The normalized difference vegetation index (NDVI) was sensitive to and responded primarily to the highly absorbing red reflectance band, while other indices such (is the soil and atmosphere resistant vegetation index (SARVI) were more responsive to variations in the near-infrared (NIR) band. As a result, we found the NDVI to mimic red reflectances and saturate over the forested sites while the SARVI, by contrast, did not saturate and followed variations in NIR refleetances. In the arid and semiarid biomes, the NDVI was much more sensitive to canopy background variations than the SARVI. Maximum differences among vegetation index behavior occurred over the evergreen needleleaf forest sites relative to the deciduous broadleaf forests and drier, grassland, and shrub sites. These differences appear to be useful in complementing the NDVI for improved monitoring of vegetation, with the NDVI sensitive to fraction of absorbed photosynthetic active radiation and the SARVI more sensitive to structural canopy parameters such as leaf area index and leaf morphology. ER - TY - JOUR ID - huete2002 AU - Huete, A. AU - Didan, K. AU - Miura, T. AU - Rodriguez, E. P. AU - Gao, X. AU - Ferreira, L. G. TI - Overview of the radiometric and biophysical performance of the MODIS vegetation indices DO - 10.1016/s0034-4257(02)00096-2 T2 - Remote Sensing of Environment PY - 2002 SN - 0034-4257 VL - 83 IS - 1–2 SP - 195-213 AB - We evaluated the initial 12 months of vegetation index product availability from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Earth Observing System-Terra platform. Two MODIS vegetation indices (VI), the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI), are produced at 1-km and 500-m resolutions and 16-day compositing periods. This paper presents an initial analysis of the MODIS NDVI and EVI performance from both radiometric and biophysical perspectives. We utilize a combination of site-intensive and regionally extensive approaches to demonstrate the performance and validity of the two indices. Our results showed a good correspondence between airborne-measured, top-of-canopy reflectances and VI values with those from the MODIS sensor at four intensively measured test sites representing semi-arid grass/shrub, savanna, and tropical forest biomes. Simultaneously derived field biophysical measures also demonstrated the scientific utility of the MODIS VI. Multitemporal profiles of the MODIS VIs over numerous biome types in North and South America well represented their seasonal phenologies. Comparisons of the MODIS-NDVI with the NOAA-14, 1-km AVHRR-NDVI temporal profiles showed that the MODIS-based index performed with higher fidelity. The dynamic range of the MODIS VIs are presented and their sensitivities in discriminating vegetation differences are evaluated in sparse and dense vegetation areas. We found the NDVI to asymptotically saturate in high biomass regions such as in the Amazon while the EVI remained sensitive to canopy variations. ER - TY - GEN ID - huete1994 AU - Huete, A.R. AU - Justice, C. AU - Liu, H. TI - Development of Vegetation and Soil Indices for MODIS- EOS T2 - Remote Sensing of Environment PY - 1994 VL - 49 SP - 224-234 ER - TY - JOUR ID - hunt_jr1989 AU - Hunt Jr, E. Raymond AU - Rock, Barrett N. TI - Detection of changes in leaf water content using Near- and Middle-Infrared reflectances UR - http://www.sciencedirect.com/science/article/pii/0034425789900461 DO - 10.1016/0034-4257(89)90046-1 T2 - Remote Sensing of Environment PY - 1989 SN - 0034-4257 VL - 30 IS - 1 SP - 43-54 AB - Detection of plant water stress by remote sensing has been proposed using indices of Near-Infrared (NIR, 0.7–1.3 µm) and Middle-Infrared (MIR, 1.3–2.5 µm) wavelengths. The first objective of this study was to test the ability of the Leaf Water Content Index (LWCI) to determine leaf Relative Water content (RWC) of different species with different leaf morphologies. The second objective was to determine how the Moisture Stress Index (MSI; MIR / NIR) varies with RWC and the Equivalent Water Thickness (EWT). Reflectance factors at 0.82 µm and 1.6 µm were measured on leaves of Quercus agrifolia (sclerophyllous leaves), Liquidambar styraciflua (hardwood deciduous tree leaves), Picea rubens and Picea pungens (conifer needles), and Glycine max (herbaceous dicot leaves) as they dried on a laboratory bench. RWC and EWT were measured concurrently with the reflectance measurements. The results showed that LWCI was equal to RWC for the species tested. However, the results of a sensitivity analysis indicated the reflectances at 1.6 µm for two different RWC must be known for accurate prediction of unknown RWC; thus the LWCI is impractical for field applications. MSI was linearly correlated to RWCwith each species having a different regression equation and to log10 EWT with data of all species falling on the same regression line. Because EWT is correlated with leaf area index, MSI should also be correlated with leaf area index. Assuming that the linear regression equation of MSI to EWT can be applied to canopies, then the minimum significant change of RWC that can be detected is 52%. For most plants, the natural variation in RWC from water stress is only about 20%, so that we conclude that indices derived from NIR and MIR reflectances cannot be used to remotely-sense water stress. ER - TY - GEN ID - hunt_jr1987 AU - Hunt Jr, Raymond E. AU - Rock, Barrett N. AU - Nobel, Park S. TI - Measurement of leaf relative water content by infrared reflectance UR - http://www.sciencedirect.com/science/article/pii/0034425787900940 DO - 10.1016/0034-4257(87)90094-0 T2 - Remote Sensing of Environment PY - 1987 SN - 0034-4257 VL - 22 IS - 3 SP - 429-435 AB - From basic considerations and Beer's law, a leaf water content index incorporating reflectances of wavelengths from 0.76 to 0.90 μm and from 1.55 to 1.75 μm (Landsat Thematic Mapper Bands TM4 and TM5, respectively) was developed that relates leaf reflectance to leaf relative water content. For the leaf succulent, Agave deserti, the leaf water content index was not significantly different from the relative water content for either individual leaves or an entire plant. Also, the relative water contents of intact plants of Encelia farinosa and Hilaria rigida in the field were estimated by the leaf water content index; variations in the proportion of living to dead leaf area could cause large errors in the estimate of relative water content. Thus, the leaf water content index may be able to estimate average relative water content of canopies when TM4 and TM5 are measured at a known relative water content and fraction of dead leaf material. ER - TY - GEN ID - hunt_jr_2011 AU - Hunt Jr., E. Raymond AU - Daughtry, C. S. T. AU - Eitel, Jan U. H. AU - Long, D. S. TI - Remote Sensing Leaf Chlorophyll Content Using a Visible Band Index T2 - Agronomy Journal PY - 2011 VL - 103 SP - 1090-1099 AB - Leaf chlorophyll content is an important variable for agricultural remote sensing because of its close relationship to leaf nitrogen content. We propose the triangular greenness index (TGI), which calculates the area of a triangle with three vertices: ('r, Rr), ('g, Rg), and ('b, Rb), where ' is the wavelength (nm) and R is the reflectance for bands in red (r), green (g), and blue (b) wavelengths. TGI was correlated with chlorophyll content using a variety of leaf and plot reflectance data. Generally, indices using the chlorophyll red-edge (710-730 nm) had higher correlations with chlorophyll content compared to TGI. However, with broad bands, correlations between TGI and chlorophyll content were equal or higher than other indices for corn and wheat. Simulations using the Scattering by Arbitrarily Inclined Leaves canopy model indicate an interaction among TGI, leaf area index (LAI) and soil type at low crop LAI, whereas at high crop LAI, TGI was only affected by leaf chlorophyll content. TGI will enable the use of low-cost sensors, including digital cameras, for nitrogen management by remote sensing. ER - TY - JOUR ID - h_ttich2009 AU - Hüttich, Christian AU - Gessner, Ursula AU - Herold, Martin AU - Strohbach, Ben AU - Schmidt, Michael AU - Keil, Manfred AU - Dech, Stefan TI - On the Suitability of MODIS Time Series Metrics to Map Vegetation Types in Dry Savanna Ecosystems: A Case Study in the Kalahari of NE Namibia UR - http://www.mdpi.com/2072-4292/1/4/620/ T2 - Remote Sensing PY - 2009 SN - 2072-4292 VL - 1 IS - 4 SP - 620-643 ER - TY - JOUR ID - jackson1991 AU - Jackson, Ray D. AU - Huete, Alfredo R. TI - Interpreting vegetation indices T2 - Preventive Veterinary Medicine PY - 1991 VL - 11 IS - 3-4 SP - 185-200 ER - TY - CONF ID - jacobsen1995 AU - Jacobsen, Anne AU - Broge, Niels H. AU - Hansen, Birger U. TI - Monitoring wheat fields and grasslands using spectral reflectance data T2 - International Symposium on Spectral Sensing Research (ISSSR) CY - Melbourne, Australia PY - 1995 DA - Nov. 26 to Dec. 1, 1995 ER - TY - JOUR ID - jago1999 AU - Jago, Rosemary A. AU - Cutler, Mark E. J. AU - Curran, Paul J. TI - Estimating Canopy Chlorophyll Concentration from Field and Airborne Spectra UR - http://www.sciencedirect.com/science/article/pii/S0034425798001138 DO - 10.1016/s0034-4257(98)00113-8 T2 - Remote Sensing of Environment PY - 1999 SN - 0034-4257 VL - 68 IS - 3 SP - 217-224 AB - This article investigates the effects of both soil contamination and nitrogen application on the red edge–chlorophyll concentration relationship for a vegetation canopy. Field based canopy reflectance and chlorophyll concentration data were collected at a grassland field site affected by soil contamination and a winter wheat field site affected by different levels of nitrogen fertilisation. The correlation between red edge position (REP) and canopy chlorophyll concentration was r=0.84 and 0.80 for the grassland and winter wheat field sites, respectively. Airborne imaging spectrometry was used to generate REP images (units, nm) of the grassland and winter wheat field sites. Strong correlations were observed between REP and canopy chlorophyll concentration at both field sites. Predictive regression equations were developed to map canopy chlorophyll concentration across the field sites. The rms error of estimated chlorophyll concentration was 0.42 mg g-1 (±12.69% of mean) and 2.09 mg g-1(±16.4% of mean) at the grassland and winter wheat field sites respectively. Results demonstrated the use of remotely sensed estimates of the REP from both field and airborne spectrometers for estimating chlorophyll concentration and indicated the potential of this technique for inferring both land contamination and grain yield. ER - TY - GEN ID - karnieli2001 AU - Karnieli, A. AU - Kaufman, Y. J. AU - Remer, L. AU - Wald, A. TI - AFRI - aerosol free vegetation index UR - http://www.ingentaconnect.com/content/els/00344257/2001/00000077/00000001/art00190 http://dx.doi.org/10.1016/S0034-4257(01)00190-0 DO - 10.1016/s0034-4257(01)00190-0 T2 - Remote Sensing of Environment PY - 2001 VL - 77 IS - 1 SP - 10-21 AB -

Aircraft measurements using a field spectrometer over variety of ground surfaces in Israel reveals that under clear sky conditions, the shortwave infrared (SWIR) spectral bands around 1.6 and 2.1 mum are highly correlated with the visible - blue, green, and red - spectral bands. Empirical linear relationships, such as rho0.469=0.25rho2.1; rho0.555=0.33rho2.1; rho0.645=0.5rho2.1; and rho0.645=0.66rho1.6, were found to be statistically significant and consistent with previous findings. Based on the above relationships, a modified vegetation index (VI) is proposed and named Aerosol Free Vegetation Index (AFRI). Two versions of this VI are formulated as: AFRI1.6=(rhoNIR-0.66rho1.6)/(rhoNIR+0.66rho1.6) and AFRI2.1=(rhoNIR-0.5rho2.1)/(rhoNIR+0.5rho2.1). It is shown that under clear sky conditions, the AFRIs (and especially AFRI2.1) closely resemble the Normalized Difference Vegetation Index (NDVI) and their values are almost identical. The advantage of the derived AFRIs, based on the ability of the SWIR bands, is to penetrate the atmospheric column even when aerosols such as smoke or sulfates exist. Consequently, these indices have a major application in assessing vegetation in the presence of smoke, anthropogenic pollution, or volcanic plumes. This was demonstrated by applying the AFRI for a biomass burned forest in Brazil. Limited success of these indices is expected in case of dust due to presence of larger particles that are of similar size to the wavelength and therefore not transparent at 2.1 mum. The AFRIs can be implemented to data from any sensor that has the SWIR bands. Currently, the most commonly used of such instruments are the Landsat - Thematic Mapper (TM) and Advanced Thematic Mapper Plus (ETM+), Moderate Resolution Imaging Spectrometer (MODIS), Advanced Spaceborne Thermal Emission And Reflection (ASTER), and Japanese Earth Resources Satellite - Optical System (JERS-OPS). Although the AFRI2.1 was demonstrated to perform better than the AFRI1.6, the latter still can be used for the same application in conjunction with instruments that have onboard only the 1.6-mum band, such as Systeme Probatoire d'Observation del la Terre (SPOT4) - VEGETATION, Indian Remote Sensing (IRS-1C/D), and Resource-21.

ER - TY - ABST ID - kaufman1992 AU - Kaufman, Y. J.;Tanre, D. TI - Atmospherically resistant vegetation index (ARVI) for EOS-MODIS DO - 10.1109/36.134076 T2 - Geoscience and Remote Sensing, IEEE Transactions on PY - 1992 SN - 0196-2892 VL - 30 IS - 2 SP - 261-270 KW - ecology KW - remote sensing KW - 0.47 micron KW - 0.66 micron KW - 0.865 micron KW - EOS-HIRIS KW - EOS-MODIS KW - Earth Observing System KW - atmospherically resistant vegetation index KW - blue channel KW - dynamic range KW - near-IR channel KW - normalized difference vegetation index KW - radiance KW - radi ER - TY - JOUR ID - kauth1976 AU - Kauth, R. J. and Thomas, G. S. TI - The tasselled cap - a graphic description of the spectraltemporal development of agricultural crops as seen by Landsat PR - Purdue University, West Lafayette, Indiana T2 - Procs. Symposium on Machine Processing of Remotely Sensed Data PY - 1976 SP - 41-51 ER - TY - CPAPER ID - key2002 AU - Key, C.H. AU - N. Benson AU - D. Ohlen AU - S. Howard AU - R. McKinley AU - Zhu Z. TI - The normalized burn ratio and relationships to burn severity: ecology, remote sensing and implementation PR - J.D. Greer, ed. Rapid Delivery of Remote Sensing Products T2 - Proceedings of the Ninth Forest Service Remote Sensing Applications Conference. American Society for Photogrammetry and Remote Sensing, Bethesda, MD CY - San Diego, CA PY - 2002 DA - 8-12 April, 2002 ER - TY - CONF ID - kim1994 AU - Kim, Moon S. AU - Doughtry, C.S.T. AU - Chappelle, E. W. AU - Mcmurtrey, J. E. AU - Walthall, C. L. TI - The use high spectral resolution bands for estimating absorbed photo synthetically active radiation (APAR) T2 - ISPRS’94 Val d’Isere, France, 17-21 January 1994 PY - 1994 SP - 299-306 AB - Most remote sensing estimations of vegetation variables such as Leaf Area Index (LAI), Absorbed Photosynthetically Active Radiation (APAR), and phytomass are made using broad band sensors with a bandwidth of approximately 100 nm. However, high resolution spectrometers are available and have not been fully exploited for the purpose of improving estimates of vegetation variables. A study directed to investigate the use of high spectral resolution spectroscopy for remote sensing estimates of APAR in vegetation canopies in the presence of nonphotosynthetic background materials such as soil and leaf litter is presented. A high spectral resolution method defined as the Chlorophyll Absorption Ratio Index (CARI) was developed for minimizing the effects of nonphotosynthetic materials in the remote estimates of APAR. CARI utilizes three bands at 550, 670, and 700 nm with bandwidth of 10 nm. Simulated canopy reflectance of a range of LAI were generated with the SAIL model using measurements of 42 different soil types as canopy background. CARI obtained from the simulated canopy reflectance was compared with the broad band vegetation indices (Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), and Simple Ratio (SR)). CARI reduced the effect of nonphotosynthetic background materials in the assessment of vegetation canopy APAR more effectively than broad band vegetation indices. ER - TY - JOUR ID - le_maire2004 AU - le Maire, G. AU - Francois, C. AU - Dufrene, E. TI - Towards universal broad leaf chlorophyll indices using PROSPECT simulated database and hyperspectral reflectance measurements DO - 10.1016/j.rse.2003.09.004 T2 - Remote Sensing of Environment PY - 2004 SN - 0034-4257 VL - 89 IS - 1 SP - 1-28 AB - Fifty-three leaves were randomly sampled on different deciduous tree species, representing a wide range of chlorophyll contents, tree ages, and leaf structural features. Their reflectance was measured between 400 and 800 nm with a 1-nm,step, and their chlorophyll content determined by extraction. A larger simulated database (11,583 spectra) was built using the PROSPECT model, in order to test, calibrate, and obtain universal indices, i.e., indices applicable to a wide range of species and leaf structure. To our knowledge, almost all leaf chlorophyll indices published in the literature since 1973 have been tested on both databases. Fourteen canonical types of indices (published ones and new ones) were identified, and their wavelengths calibrated on the simulated database as well as on the experimental database to determine the best wavelengths and, hence, the best performances in chlorophyll estimation for each index types. These indices go from simple reflectance ratios to more sophisticated indices Using reflectance first derivatives (using the Savitzky and Golay method). We also tested other nondestructive methods to obtain total chlorophyll concentration: SPAD (Minolta Camera, Osaka, Japan) and neural networks. The validity of the actual PROSPECT model is challenged by our results: Important discordances are found when the indices are calculated with PROSPECT compared to experimental data, especially for some indices and wavelengths. The discordance is even greater when the indices are determined with PROSPECT and applied on the experimental database. A new calibration of PROSPECT is therefore necessary for any study aiming at using simulated spectra to determine or to calibrate indices. The "peak jump" and the multiple-peak feature observed on the first derivative of the reflectances (e.g., in the Red-Edge Inflection Point [REIP] index) has been investigated. It was shown that chlorophyll absorption alone can explain this feature. The peak jump disqualifies' the REIP to be a valuable chlorophyll index. A simple modified difference ratio gave the best results among all published indices (cross-validated RMSE = 2.1 mug/cm(2) on the experimental database). After calibration on the experimental database, modified Simple Ratio (mSR) and modified Normalized Difference (mND) indices gave the best 2 performances (RMSECV = 1.8 mug/cm(2) on the experimental database). The new Double Difference (DD) index, although not the best on the 2), 2 experimental database (RMSECV 2.9 mug/cm(2)), has the best results on the larger simulated database (RMSE = 3.7 mug/cm(2)) and is expected to give good results on larger experimental databases. The best reflectance-based indices give better performances than the current commercial nondestructive device SPAD (RMSECV = 4.5 mug/cm(2)). In This leaf-level study, the best indices are very near from each other, so that complex methods are useless: REIP-like, neural networks, and derivative-based indices are not necessary and give worst results than simpler properly chosen indices. These conclusions will certainly be different for. a canopy-level study, where the derivative-based indices may perform significantly better than the other ones. (C) 2003 Elsevier Inc. All rights reserved. KW - universal broad leaf chlorophyll indices. PROSPECT. hyperspectral. reflectance measurements. neural-network classification. radiative-transfer models. remote-sensing. data. red-edge. vegetation indexes. spectral reflectance. optical-properties. bidirectio ER - TY - GEN ID - le_maire2008 AU - le Maire, Guerric AU - François, Christophe AU - Soudani, Kamel AU - Berveiller, Daniel AU - Pontailler, Jean-Yves AU - Bréda, Nathalie AU - Genet, Hélène AU - Davi, Hendrik AU - Dufrêne, Eric TI - Calibration and validation of hyperspectral indices for the estimation of broadleaved forest leaf chlorophyll content, leaf mass per area, leaf area index and leaf canopy biomass UR - http://www.sciencedirect.com/science/article/pii/S003442570800196X DO - 10.1016/j.rse.2008.06.005 T2 - Remote Sensing of Environment PY - 2008 SN - 0034-4257 VL - 112 IS - 10 SP - 3846-3864 AB - This article aims at finding efficient hyperspectral indices for the estimation of forest sun leaf chlorophyll content (CHL, µg cmleaf− 2), sun leaf mass per area (LMA, gdry matter mleaf− 2), canopy leaf area index (LAI, m2leaf msoil− 2) and leaf canopy biomass (Bleaf, gdry matter msoil− 2). These parameters are useful inputs for forest ecosystem simulations at landscape scale. The method is based on the determination of the best vegetation indices (index form and wavelengths) using the radiative transfer model PROSAIL (formed by the newly-calibrated leaf reflectance model PROSPECT coupled with the multi-layer version of the canopy radiative transfer model SAIL). The results are tested on experimental measurements at both leaf and canopy scales. At the leaf scale, it is possible to estimate CHL with high precision using a two wavelength vegetation index after a simulation based calibration. At the leaf scale, the LMA is more difficult to estimate with indices. At the canopy scale, efficient indices were determined on a generic simulated database to estimate CHL, LMA, LAI and Bleaf in a general way. These indices were then applied to two Hyperion images (50 plots) on the Fontainebleau and Fougères forests and portable spectroradiometer measurements. They showed good results with an RMSE of 8.2 µg cm− 2 for CHL, 9.1 g m− 2 for LMA, 1.7 m2 m− 2 for LAI and 50.6 g m− 2 for Bleaf. However, at the canopy scale, even if the wavelengths of the calibrated indices were accurately determined with the simulated database, the regressions between the indices and the biophysical characteristics still had to be calibrated on measurements. At the canopy scale, the best indices were: for leaf chlorophyll content: NDchl = (ρ925 − ρ710)/(ρ925 + ρ710), for leaf mass per area: NDLMA = (ρ2260 − ρ1490)/(ρ2260 + ρ1490), for leaf area index: DLAI = ρ1725 − ρ970, and for canopy leaf biomass: NDBleaf = (ρ2160 − ρ1540)/(ρ2160 + ρ1540). KW - Chlorophyll KW - LMA KW - SLA KW - Leaf biomass KW - EO1 Hyperion KW - ASD Fieldspec KW - LAI KW - PROSPECT KW - SAIL KW - PROSAIL ER - TY - JOUR ID - lee2010 AU - Lee, W. S. AU - Alchanatis, V. AU - Yang, C. AU - Hirafuji, M. AU - Moshou, D. AU - Li, C. TI - Sensing technologies for precision specialty crop production UR - ://WOS:000283271800001 DO - 10.1016/j.compag.2010.08.005 T2 - Computers and electronics in agriculture PY - 2010 DA - Oct SN - 0168-1699 VL - 74 IS - 1 SP - 2-33 N1 - ISI Document Delivery No.: 668LQ Times Cited: 11 Cited Reference Count: 367 Lee, W. S. Alchanatis, V. Yang, C. Hirafuji, M. Moshou, D. Li, C. Elsevier sci ltd Oxford AB - With the advances in electronic and information technologies, various sensing systems have been developed for specialty crop production around the world. Accurate information concerning the spatial variability within fields is very important for precision farming of specialty crops. However, this variability is affected by a variety of factors, including crop yield, soil properties and nutrients, crop nutrients, crop canopy volume and biomass, water content, and pest conditions (disease, weeds, and insects). These factors can be measured using diverse types of sensors and instruments such as field-based electronic sensors, spectroradiometers, machine vision, airborne multispectral and hyperspectral remote sensing, satellite imagery, thermal imaging, RFID, and machine olfaction system, among others. Sensing techniques for crop biomass detection, weed detection, soil properties and nutrients are most advanced and can provide the data required for site specific management. On the other hand, sensing techniques for diseases detection and characterization, as well as crop water status, are based on more complex interaction between plant and sensor, making them more difficult to implement in the field scale and more complex to interpret. This paper presents a review of these sensing technologies and discusses how they are used for precision agriculture and crop management, especially for specialty crops. Some of the challenges and considerations on the use of these sensors and technologies for specialty crop production are also discussed. (C) 2010 Elsevier B.V. All rights reserved. KW - Specialty crop KW - Precision agriculture KW - Sensing KW - Review KW - on-the-go KW - infrared reflectance spectroscopy KW - soil-moisture content KW - airborne hyperspectral imagery KW - grain-sorghum yield KW - leaf-area index KW - quickbird satellite imagery KW - difference vegetation index KW - tree canopy KW - characteristics KW - compaction profile sensor ER - TY - ABST ID - leprieur1996 AU - Leprieur, C. AU - Kerr, Y. H. AU - Pichon, J. M. TI - Critical assessment of vegetation indices from AVHRR in a semi-arid environment UR - http://www.tandfonline.com/doi/abs/10.1080/01431169608949092 DO - 10.1080/01431169608949092 PR - Taylor & Francis T2 - International Journal of Remote Sensing PY - 1996 DA - 1996/09/01 SN - 0143-1161 VL - 17 IS - 13 SP - 2549-2563 AB - Abstract The most frequently used vegetation index (VI), the Normalized Difference Vegetation Index (NDVI) and its variants introduced recently to correct for atmospheric and soil optical response such as Global Environment Monitoring Index (GEMI) and Modified Soil-Adjusted Vegetation Index (MSAVI) are evaluated over a Sahelian region. The usefulness and limitations of the various vegetation indices are discussed, with special attention to cloud contamination and green vegetation detection from space. The HAPEX Sahel database is used as a test case to compare these indices in arid and semi-arid environments. Selected sites are characterized by sparse vegetation cover and day-to-day variability in atmospheric composition. Simulated indices values behaviour at the surface level shows that these VIs were all sensitive to the presence of green vegetation but were affected differently by changes in soil colour and brightness. We showed that GEMI is less sensitive to atmospheric variations than both NDVI and MSAVI since it exhibits a high atmospheric transmissivity over its entire range for various atmospheric aerosol loadings and water vapour contents. These results were first tested on a vegetation gradient, and secondly evaluated on a transect which encompasses various soils formations. On the vegetation gradient, it was found that GEMI computed from measurements at the top of the atmosphere is invariable from one day to the next. On the bare soils transect, MSAVI calculated at the surface level, has shown a great insensitivity to soil optical responses modifications, while GEMI exhibits from space noticeable variability in this bright soil context. Finally, it was illustrated that GEMI exhibits interesting properties for cloud detection because of the strong decrease of its value on cloudy pixels. ER - TY - ABST ID - lichtenthaler1996 AU - Lichtenthaler, Hartmut K. TI - Vegetation Stress: an Introduction to the Stress Concept in Plants UR - http://www.sciencedirect.com/science/article/pii/S0176161796802872 DO - 10.1016/s0176-1617(96)80287-2 T2 - Journal of Plant Physiology PY - 1996 SN - 0176-1617 VL - 148 IS - 1–2 SP - 4-14 AB - Summary This is a presentation of the essentials of the present stress concept in plants, which has been well developed in the past 60 years. Any unfavorable condition or substance that affects or blocks a plants metabolism, growth or development, is to be regarded as stress. Plant and vegetation stress can be induced by various natural and anthropogenic stress factors. One has to differentiate between short-term and long-term stress effects as well as between low stress events, which can be partially compensated for by acclimation, adaptation and repair mechanisms, and strong stress or chronic stress events causing considerable damage that may eventually lead to cell and plant death. The different stress syndrome responses of plants are summarized in a scheme. The major abiotic, biotic and anthropogenic stressors are listed. Some stress tolerance mechanisms are mentioned. Stress conditions and stress-induced damage in plants can be detected using the classical ecophysiological methods. In recent years various non-invasive methods sensing different parameters of the chlorophyll fluorescence have been developed to biomonitor stress constraints in plants and damage to their photosynthetic apparatus. These fluorescence methods can be applied repeatedly to the same leaf and plant, e.g. before and after stress events or during recovery. A new dimension in early stress detection in plants has been achieved by the novel high resolution fluorescence imaging analysis of plants, which not only senses the chlorophyll fluorescence, but also the bluegreen fluorescence emanating from epidermis cell walls which can change under stress induced strain. This powerful new technique opens new possibilities for stress detection in plants. KW - Bluegreen fluorescence KW - chlorophyll fluorescence KW - damage KW - resistance KW - long-term stress KW - strain KW - stress-factors ER - TY - JOUR ID - lymburner2000 AU - Lymburner, L. AU - Beggs, PJ. AU - Jacobson, CR. TI - Estimation of canopy-average surface-specific leaf area using Landsat TM data T2 - Photogrammetric Engineering and Remote Sensing PY - 2000 SN - 0099-1112 VL - 66 IS - 2 SP - 183-191 AB - Specific leaf area (SLA) is an important ecological variable because of its links with plant ecophysiology and leaf biochemistry. Variations in SLA are associated with variations in leaf optical properties, and these changes in leaf optical properties have been found to result in changes in canopy reflectance. This paper utilizes these changes to explore the potential of estimating SLA using Landsat TM data. Fourteen sites with varying vegetation were sampled on the Lambert Peninsula in Ku-ring-gai Chase National Park to the north of Sydney, Australia. A sampling strategy that facilitated the calculation of canopy-average surface SLA (SLA(CS)) was developed. The relationship between SLA(CS), reflectance in Landsat TM bands, and a number of vegetation indices, were explored using univariate regression. The observed relationships between SLA(CS) and canopy reflectance are also discussed in terms of trends observed in a pre-existing leaf optical properties dataset (LOPEX 93). Field data indicate that there is a strong correlation between SLA(CS) and red, near-infrared, and the second midinfrared bands of Landsat TM data. A strong correlation between SLA(CS) and the following vegetation indices: Soil and Atmosphere Resistant Vegetation Index (SARVI2), Normalized Difference Vegetation Index (NDVI), and Ratio Vegetation Index (RVI), suggests that these vegetation indices could be used to estimate SLA(CS) using Landsat TM data. ER - TY - GEN ID - maccioni2001 AU - Maccioni, Andrea AU - Agati, Giovanni AU - Mazzinghi, Piero TI - New vegetation indices for remote measurement of chlorophylls based on leaf directional reflectance spectra UR - http://www.sciencedirect.com/science/article/pii/S1011134401001452 DO - 10.1016/s1011-1344(01)00145-2 T2 - Journal of Photochemistry and Photobiology B: Biology PY - 2001 SN - 1011-1344 VL - 61 IS - 1-2 SP - 52-61 AB - Directional reflectance (R) spectra from 380 to 780 nm for nadir illuminated leaves of four different plants (croton, Codiaeum variegatum; spotted eleagnus, Eleagnus pungens Maculata; Japanese pittosporum, Pittosporum tobira and Benjamin fig, Ficus benjamina Starlight) were acquired at a viewing angle of 30° from the nadir direction. Chlorophyll-a and -b content of leaves covered a range of 1–60 and 0.5–21 μg/cm2, respectively. In contrast with previous results from hemispherical reflectance measurements, directional reflectance data does not correlate well with chlorophyll concentration. This is mainly due to the external reflectance (RE) at the leaf epidermis, caused by the mismatch of the refractive index at the air–epidermis and epidermis–inner layer boundary. The external reflectance can be identified with the blue flat reflectance between 380 and 480 nm. The inner reflectance (RI), obtained by subtracting the external reflectance from the measured spectra, was found to be linearly related to the logarithm of the chlorophyll content. Good fitting of the log (Chl) versus RI(λ) curves were obtained for RI in the green band (around 550 nm) and close to the inflection point in the red edge (around 700 nm). The coefficient of determination, r2, of curve fitting improved (up to 0.97) when the normalised inner reflectance NRI(λ)=RI(λ)/RI(λ0), with λ0≥750 nm, was used instead of the absolute reflectance. The best indices for Chl, Chl-a and Chl-b determination were RI542/RI750, RI706/RI750 and RI556/RI750, respectively. However, since the content of Chl-a relative to Chl-b was almost constant for the plants investigated, the two last indices must be further validated on leaves with a high variability in the Chl-a:Chl-b ratio. The error in the determination of chlorophyll content was found to be of the order of 10%. This value was lower than those obtained by applying the vegetation indices previously suggested. Therefore, the normalised inner reflectance in the green and in the red edge represents a more suitable index for the chlorophyll determination than those up to now used. KW - Chlorophyll, Leaf directional reflectance, Leaf reflectance spectra, Remote sensing of chlorophyll ER - TY - JOUR ID - main2011 AU - Main, Russell AU - Cho, Moses Azong AU - Mathieu, Renaud AU - O’Kennedy, Martha M. AU - Ramoelo, Abel AU - Koch, Susan TI - An investigation into robust spectral indices for leaf chlorophyll estimation UR - http://www.sciencedirect.com/science/article/pii/S092427161100089X DO - 10.1016/j.isprsjprs.2011.08.001 T2 - ISPRS Journal of Photogrammetry and Remote Sensing PY - 2011 SN - 0924-2716 VL - 66 IS - 6 SP - 751-761 AB - Quantifying photosynthetic activity at the regional scale can provide important information to resource managers, planners and global ecosystem modelling efforts. With increasing availability of both hyperspectral and narrow band multispectral remote sensing data, new users are faced with a plethora of options when choosing an optical index to relate to their chosen or canopy parameter. The literature base regarding optical indices (particularly chlorophyll indices) is wide ranging and extensive, however it is without much consensus regarding robust indices. The wider spectral community could benefit from studies that apply a variety of published indices to differing sets of species data. The consistency and robustness of 73 published chlorophyll spectral indices have been assessed, using leaf level hyperspectral data collected from three crop species and a variety of savanna tree species. Linear regression between total leaf chlorophyll content and bootstrapping were used to determine the leafpredictive capabilities of the various indices. The indices were then ranked based on the prediction error (the average root mean square error (RMSE)) derived from the bootstrapping process involving 1000 iterative resampling with replacement. The results show two red-edge derivative based indices (red-edge position via linear extrapolation index and the modified red-edge inflection point index) as the most consistent and robust, and that the majority of the top performing indices (in spite of species variability) were simple ratio or normalised difference indices that are based on off-chlorophyll absorption centre wavebands (690–730 nm). KW - Leaf level reflectance KW - Leaf chlorophyll KW - Red-edge KW - Vegetation indices KW - Photosynthetic activity ER - TY - JOUR ID - major1990 AU - Major, D. J. AU - Baret, F. AU - Guyot, G. TI - A ratio vegetation index adjusted for soil brightness UR - http://dx.doi.org/10.1080/01431169008955053 DO - 10.1080/01431169008955053 PR - Taylor & Francis T2 - International Journal of Remote Sensing PY - 1990 DA - 1990-05-01 SN - 0143-1161 VL - 11 IS - 5 SP - 727-740 AB - Abstract Improved parameters for a soil-adjusted vegetation index (SAVI) are derived using SAIL model output for simulated wheat canopy reflectance. The SAVI is much less sensitive than the ratio vegetation index to changes in background caused by soil colour or surface soil moisture content. The parameters are developed to minimize variability due to soil brightness over the practical range of solar elevations, lear angle distributions (LAD) and leaf area indices (LAI). The parameters are added to the near-infrared (NIR) and red reflectances before calculating the NIR/red ratio. Three new versions of the SAVI are developed based on the theoretical consideration of the effects of wet and dry soils. All three are superior to the NIR/red ratio, the perpendicular vegetation index and a soil-adjusted vegetation index. Our simplest version requires the addition of a parameter to the red reflectance. The second and third versions require an iterative procedure to find the best parameters that are then added to the red or the NIR and red reflectances. In general, SAVI adjustment parameters required to remove soil-brightness effects decrease as factors that obscure the soil-surface increase. Low solar elevation and high LAI result in increasingly negative values for the parameters. The NIR/red ratio is the vegetation index least influenced by soil brightness at LAI greater than three. Our iterated versions have lowest overall errors but are occasionally subject to higher errors at the combination of low zenith angles and erectophile canopies. The SAVI based on the bare soil reflectance performs best on field data. ER - TY - JOUR ID - malthus1993 AU - Malthus, Tim J. AU - Andrieu, Bruno AU - Danson, F. Mark AU - Jaggard, Keith W. AU - Steven, Michael D. TI - Candidate high spectral resolution infrared indices for crop cover UR - http://www.sciencedirect.com/science/article/pii/003442579390095F DO - 10.1016/0034-4257(93)90095-f T2 - Remote Sensing of Environment PY - 1993 SN - 0034-4257 VL - 46 IS - 2 SP - 204-212 ER - TY - GEN ID - mcmurtrey1994 AU - McMurtrey, J.E. III AU - Chappelle, E.W. AU - Kim, M.S. AU - Meisinger, J.J. AU - Corp, L.A. TI - Distinguishing nitrogen fertilization levels in field corn (Zea mays L.) with actively induced fluorescence and passive reflectance measurements T2 - Remote Sensing of Environment PY - 1994 VL - 47 SP - 36–44 ER - TY - CONF ID - merton1998 AU - Merton, R. N. TI - Monitoringcommunityhysteresis using spectralshiftanalysis and the red-edgevegetationstressindex T2 - Seventh Annual JPL Airborne Earth Science Workshop CY - Pasadena, California PY - 1998 DA - 12–16 January, 1998 SP - 12-16 ER - TY - JOUR ID - merzlyak2003 AU - Merzlyak, M. N. AU - Gitelson, A. A. AU - Chivkunova, O. B. AU - Solovchenko, A. E. AU - Pogosyan, S. I. TI - Application of Reflectance Spectroscopy for Analysis of Higher Plant Pigments T2 - Russian Journal of Plant Physiology PY - 2003 VL - 50 IS - 5 SP - 704-710 AB - Nondestructive techniques developed by the authors for assessment of chlorophylls, carotenoids, and anthocyanins in higher plant leaves and fruits are presented. The spectral features of leaf reflectance in the visible and near infrared regions are briefly considered. For pigment analysis only reflectance values at several specific wavelengths are required. The chlorophyll (Chl) content over a wide range of its changes can be assessed during leaf ontogeny using reflectance near 700 nm and, in the absence of anthocyanins, at 550 nm. The approaches used for elimination of Chl interference in the analysis of carotenoids (reflectance at 520 nm) and anthocyanins (at 550 nm) are described. The suitability of reflectance spectroscopy for estimates of carotenoid/chlorophyll ratios during leaf senescence and fruit ripening is demonstrated. The algorithms developed for pigment analysis are presented, and the conditions of their applicability are considered. Further perspectives for the application of reflectance spectroscopy including remote sensing for estimation of plant pigment content and physiological states are discussed. KW - chlorophyll KW - carotenoids KW - anthocyanins KW - reflectance spectroscopy KW - leaves KW - fruits ER - TY - JOUR ID - merzlyak1999 AU - Merzlyak, Mark N. AU - Gitelson, Anatoly A. AU - Chivkunova, Olga B. AU - Rakitin, Victor Y. U. TI - Non-destructive optical detection of pigment changes during leaf senescence and fruit ripening UR - http://dx.doi.org/10.1034/j.1399-3054.1999.106119.x DO - 10.1034/j.1399-3054.1999.106119.x T2 - Physiologia Plantarum PY - 1999 SN - 1399-3054 VL - 106 IS - 1 SP - 135-141 AB - Reflectance spectra in the visible and near infra-red range of the spectrum, acquired for maple (Acer platanoides L.), chestnut (Aesculus hippocastanum L.), potato (Solanum tuberosum L.), coleus (Coleus blumei Benth.), leaves and lemon (Citrus limon L.) and apple (Malus domestica Borkh.) fruits were studied. An increase of reflectance between 550 and 740 nm accompanied senescence-induced degradation of chlorophyll (Chl), whereas in the range 400–500 nm it remained low, due to retention of carotenoids (Car). It was found that both leaf senescence and fruit ripening affect the difference between reflectance (R) near 670 and 500 nm (R678-R500), depending on pigment composition. The plant senescing reflectance index in the form (R678-R500)/R750 was found to be sensitive to the Car/Chl ratio, and was used as a quantitative measure of leaf senescence and fruit ripening. The changes in the index were followed during leaf senescence, and natural and ethylene-induced fruit ripening. This novel index can be used for estimating the onset, the stage, relative rates and kinetics of senescence/ripening processes. ER - TY - JOUR ID - metternicht2003 AU - Metternicht, G. TI - Vegetation indices derived from high-resolution airborne videography for precision crop management T2 - International Journal of Remote Sensing PY - 2003 SN - 0143-1161 VL - 24 IS - 14 SP - 2855-2877 ER - TY - JOUR ID - miura2008 AU - Miura, T. AU - Yoshioka, H. AU - Fujiwara, K. AU - Yamamoto, H., TI - Inter-Comparison of ASTER and MODIS Surface Reflectance and Vegetation Index Products for Synergistic Applications to Natural Resource Monitoring T2 - Sensors PY - 2008 VL - 8 SP - 2480–2499 ER - TY - JOUR ID - moran1997 AU - Moran, M. S. AU - Inoue, Y. AU - Barnes, E. M. TI - Opportunities and limitations for image-based remote sensing in precision crop management UR - http://www.sciencedirect.com/science/article/pii/S003442579700045X DO - 10.1016/s0034-4257(97)00045-x T2 - Remote Sensing of Environment PY - 1997 SN - 0034-4257 VL - 61 IS - 3 SP - 319-346 AB - This review addresses the potential of image-based remote sensing to provide spatially and temporally distributed information for precision crop management (PCM). PCM is an agricultural management system designed to target crop and soil inputs according to within, field requirements to optimize profitability and protect the environment. Progress in. PCM has been hampered by a lack of timely, distributed information on crop and soil conditions. Based on a review of the information requirements of PCM, eight areas were identified in which image-based remote sensing technology could provide information that is currently lacking or inadequate. Recommendations were made for applications with potential for near-term implementation with available remote sensing technology and instrumentation. We found that both aircraft- and satellite-based re-trote sensing could provide valuable information for PCM applications. Images from aircraft-based sensors have a unique role for monitoring seasonally variable crop/soil conditions and for time specific and time-critical crop management; current satellitebased sensors have limited, but important, applications; and upcoming commercial Earth observation satellites may provide the resolution, timeliness, and high quality required for many PCM operations. The current limitations for image-based remote sensing applications are mainly due to sensor attributes, such as restricted spectral range, coarse spatial resolution, slow turnaround time, and inadequate repeat coverage. According to experts in PCM, the potential market for remote sensing products in PCM is good. Future work should be focused on assimilating remotely sensed infonna- tion into existing decision support systems (DSS), and conducting economic and technical analysis of remote sensing applications with season-long pilot projects. ER - TY - JOUR ID - moulin1998 AU - Moulin, S. AU - Bondeau, A. AU - Delecolle, R. TI - Combining agricultural crop models and satellite observations: from field to regional scales UR - ://WOS:000073315500002 DO - 10.1080/014311698215586 T2 - International Journal of Remote Sensing PY - 1998 DA - Apr SN - 0143-1161 VL - 19 IS - 6 SP - 1021-1036 N1 - ISI Document Delivery No.: ZK386 Times Cited: 118 Cited Reference Count: 72 Moulin, S Bondeau, A Delecolle, R Taylor & francis ltd London AB - This review article gives an overview of how satellite observations are used to feed or tune crop models and improve their capability to predict crop yields in a region. Relations between crop characteristics which correspond to models state variables and satellite observations are briefly analysed, together with the various types of crop models commonly used. Various strategies for introducing short wavelength radiometric information into specific crop models are described, from direct update of model state variables to optimization of model parameter values, and some of them are exemplified. Methods to unmix crop-specific information from mixed pixels in coarse resolution-high frequency imagery are analysed. The conditions of use of the various methods and types of information are discussed. KW - photosynthetically active radiation KW - leaf-area index KW - winter-wheat KW - use KW - efficiency KW - spectral reflectance KW - vegetation canopies KW - temporal KW - variations KW - simulation-models KW - yield estimation KW - sail model ER - TY - JOUR ID - nagler2000 AU - Nagler, P. L AU - Daughtry, C. S. T. AU - Goward, S. N. TI - Plant Litter and Soil Reflectance DO - 10.1016/s0034-4257(99)00082-6 T2 - Remote Sensing of Environment PY - 2000 SN - 0034-4257 VL - 71 IS - 2 SP - 207-215 AB - The presence of plant litter on the soil surface influences the flow of nutrients, carbon, water, and energy in terrestrial ecosystems. Quantifying plant litter cover is important for interpreting vegetated landscapes and for evaluating the effectiveness of conservation tillage practices. Current methods of measuring litter cover are subjective, requiring considerable visual judgment. Reliable and objective methods are needed. The spectral reflectance (0.4–2.5 μm) of wet and dry soils (six types) and plant litters (2 crops, 14 forest, and 2 grasses) of different ages were measured. Discrimination of plant litters from the soils was ambiguous in the visible and near-infrared (0.4–1.1μm) wavelength region. An absorption feature associated with cellulose and lignin was observed at 2.1 μm in the spectra of dry plant litter, which was not present in the spectra of soils. A new spectral variable, cellulose absorption index (CAI), was defined using the relative depth of the reflectance spectra at 2.1 μm. CAI of dry litter was significantly greater than CAI of soils. CAI generally decreased with age of the litter. Water absorption dominated the spectral properties of both soils and plant litter and significantly reduced the CAI of the plant litters. Nevertheless, the CAI of wet litter was significantly greater then CAI of wet soil. This study provides a new methodology to discriminate plant litter from soils by differences in spectral reflectance produced by their physical and chemical attributes. This remote sensing method should improve quantification of plant litter cover and thus improve estimates of phytomass production, surface energy balance, and the effectiveness of soil conservation practices. Plant litter reflectance is a verifiable component in vegetative landscapes and should be labeled and modeled separately from soils in landscape studies. ER - TY - JOUR ID - nagler2005 AU - Nagler, Pamela L. AU - Scott, Russell L. AU - Westenburg, Craig AU - Cleverly, James R. AU - Glenn, Edward P. AU - Huete, Alfredo R. TI - Evapotranspiration on western U.S. rivers estimated using the Enhanced Vegetation Index from MODIS and data from eddy covariance and Bowen ratio flux towers UR - http://www.sciencedirect.com/science/article/pii/S0034425705001616 DO - 10.1016/j.rse.2005.05.011 T2 - Remote Sensing of Environment PY - 2005 SN - 0034-4257 VL - 97 IS - 3 SP - 337-351 AB - We combined remote sensing and in-situ measurements to estimate evapotranspiration (ET) from riparian vegetation over large reaches of western U.S. rivers and ET by individual plant types. ET measured from nine flux towers (eddy covariance and Bowen ratio) established in plant communities dominated by five major plant types on the Middle Rio Grande, Upper San Pedro River, and Lower Colorado River was strongly correlated with Enhanced Vegetation Index (EVI) values from the Moderate Resolution Imaging Spectrometer (MODIS) sensor on the NASA Terra satellite. The inclusion of maximum daily air temperatures (Ta) measured at the tower sites further improved this relationship. Sixteen-day composite values of EVI and Ta were combined to predict ET across species and tower sites (r2 = 0.74); the regression equation was used to scale ET for 2000–2004 over large river reaches with Ta from meteorological stations. Measured and estimated ET values for these river segments were moderate when compared to historical, and often indirect, estimates and ranged from 851–874 mm yr- 1. ET of individual plant communities ranged more widely. Cottonwood (Populus spp.) and willow (Salix spp.) stands generally had the highest annual ET rates (1100–1300 mm yr- 1), while mesquite (Prosopis velutina) (400–1100 mm yr- 1) and saltcedar (Tamarix ramosissima) (300–1300 mm yr- 1) were intermediate, and giant sacaton (Sporobolus wrightii) (500–800 mm yr- 1) and arrowweed (Pluchea sericea) (300–700 mm yr- 1) were the lowest. ET rates estimated from the flux towers and by remote sensing in this study were much lower than values estimated for riparian water budgets using crop coefficient methods for the Middle Rio Grande and Lower Colorado River. KW - Evapotranspiration KW - Riparian KW - Water balance KW - MODIS KW - Saltcedar KW - Remote sensing ER - TY - JOUR ID - nichol2000 AU - Nichol, Caroline J. AU - Huemmrich, Karl F. AU - Black, T. Andrew AU - Jarvis, Paul G. AU - Walthall, Charles L. AU - Grace, John AU - Hall, Forrest G. TI - Remote sensing of photosynthetic-light-use efficiency of boreal forest UR - http://www.sciencedirect.com/science/article/pii/S0168192399001677 DO - 10.1016/s0168-1923(99)00167-7 T2 - Agricultural and Forest Meteorology PY - 2000 SN - 0168-1923 VL - 101 IS - 2–3 SP - 131-142 AB - Using a helicopter-mounted portable spectroradiometer and continuous eddy covariance data we were able to evaluate the photochemical reflectance index (PRI) as an indicator of canopy photosynthetic light-use efficiency (LUE) in four boreal forest species during the Boreal Ecosystem Atmosphere experiment (BOREAS). PRI was calculated from narrow waveband reflectance data and correlated with LUE calculated from eddy covariance data. Significant linear correlations were found between PRI and LUE when the four species were grouped together and when divided into functional type: coniferous and deciduous. Data from the helicopter-mounted spectroradiometer were then averaged to represent data generated by the Airborne Visible Infrared Imaging Spectrometer (AVIRIS). We calculated PRI from these data and relationships with canopy LUE were investigated. The relationship between PRI and LUE was weakened for deciduous species but strengthened for the coniferous species. The robust nature of this relationship suggests that relative photosynthetic rates may be derived from remotely-sensed reflectance measurements. KW - Xanthophyll cycle KW - AVIRIS KW - Photochemical reflectance index KW - Eddy covariance ER - TY - JOUR ID - oppelt2004 AU - Oppelt, N. AU - Mauser, W. TI - Hyperspectral monitoring of physiological parameters of wheat during a vegetation period using AVIS data UR - http://www.ingentaconnect.com/content/tandf/tres/2004/00000025/00000001/art00011 http://dx.doi.org/10.1080/0143116031000115300 DO - 10.1080/0143116031000115300 T2 - International Journal of Remote Sensing PY - 2004 VL - 25 IS - 1 SP - 145-159 AB - Information on the quantity and spatial distribution of canopy physiological and biochemical components is of importance for the study of nutrient cycles, productivity, vegetation stress and, more recently, in driving ecosystem models. In this context, remote sensing can play a unique and essential role because of its ability to acquire synoptic information at different time and space scales. This paper presents parts of a two-year field and laboratory study with the new airborne hyperspectral sensor, the Airborne Visible near Infrared Imaging Spectrometer (AVIS), over a test site in the Bavarian Alpine foothills, Germany (48° 8prime N, 11° 17prime E). The 80-band AVIS was developed at the Department for Earth and Environmental Sciences of the Ludwig-Maximilians-University Munich and records the 550-1000 nm spectral range. Using this system, 18 hyperspectral datasets were collected between April and September of 1999 and 2000. Weekly measurements of several plant parameters (height, biomass, leaf chlorophyll content, leaf nitrogen content) were carried out during these time periods on three (1999) and six (2000) fields of winter wheat, whereby two different cultivars were investigated in 2000. After system correction and calibration, the hyperspectral data were atmospherically corrected and calibrated to reflectance. The resulting spectra were analysed for their chemical compounds. The statistical analysis was carried out using the Chlorophyll Absorption Integral (CAI) in comparison to established indices: Optimized Soil-Adjusted Vegetation Index (OSAVI) and hyperspectral Normalized Difference Vegetation Index (hNDVI). Both the chlorophyll and nitrogen content of the leaves showed good correlations with CAI on a field mean basis. These results as well as two-dimensional information on these parameters are presented to provide information about the spatial heterogeneity within a field. ER - TY - CONF ID - pearson1972 AU - Pearson, R. L. AU - Miller, L. D. TI - Remote mapping of standing crop biomass for estimation of the productivity of the short-grass Prairie, Pawnee National Grasslands, Colorado PR - Willow Run Laboratories, Environmental Research Institute of Michigan T2 - Proceedings of the Eighth International Symposium on Remote Sensing of Environment PY - 1972 SP - 1357-1381 AB - The U.S. IBP Grassland Biome Program sponsored by the National Science Foundation has undertaken an ecosystem analysis study of an entire shortgrass prairie biome using systems analysis techniques. One of the most important spatial parameters of the grassland biome which must be determined on an areal basis is the amount of vegetation present on the prairie at a particular place and time. Estimates of the amount of vegetation present have traditionally been made by hand clipping plots of known area with shears and weighing the dried vegetation from the plot trimmed to determine the mass of vegetative material per unit area, its biomass, and its calorie equivalent. A more efficient means of determining the amount of plant cover has been devised using remote spectral measurements of the vegetation. These measurements can be obtained from any altitude allowing small plot estimates from ground measurements or large area estimates from aerial or satellite measurements. ER - TY - JOUR ID - penuelas_j_1995 AU - Penuelas J., Baret F., Filella I. TI - Semi-empirical indices to assess carotenoids/chlorophyll a ratio from leaf spectral reflectance T2 - Photosynthetica PY - 1995 VL - 31 SP - 221 –230 ER - TY - JOUR ID - penuelas1993 AU - Penuelas, J. AU - Filella, I. AU - Biel, C. AU - Serrano, L. AU - Save, R. TI - The reflectance at the 950–970 nm region as an indicator of plant water status UR - http://dx.doi.org/10.1080/01431169308954010 DO - 10.1080/01431169308954010 PR - Taylor & Francis T2 - International Journal of Remote Sensing PY - 1993 SN - 0143-1161 VL - 14 IS - 10 SP - 1887-1905 AB - We present new remote sensing indices of plant water status: the ratio between the reflectance at 970 nm, one of the water absorption bands, and the reflectance at a reference wavelength, 900 nm (R970/R9000; the first derivative minimum in this near-infrared region (dNIRminimum ) and the wavelength where this minimum is found ( ?NIRminimum). In order to evaluate them, we carried out three experiments. Daily irrigated gerbera plants were allowed to dry until almost wilting and then daily irrigation was restarted; pepper and bean plants were grown for four months submitted to two different irrigation treatments; and bean detached leaves were submitted to progressive dehydration whereas pressure-volume curves were being carried out. In gerbera plants, the trough about 950?970 nm decreased as the drought was increasing. Therefore, the R970/R900 index and the dNIRminimum closely tracked the changes in relative water content (RWC), leaf water potential, stomatal conductance and the foliage-air temperature differences. The ?dNIRminimum tracked even better these changes in gerberas. However, these water status indices began to be significant when the water stress was already well developed, at RWC smaller than 85 per cent. The same happened to detached leaves of beans which did not present differences above ?1·55 MPa water potential. Beans and peppers growing at soil matric potentials larger than ?0·04 MPa presented higher R970/R900 values than those growing at soil matric potentials only larger than ?0·01 MPa. In all the cases, the maximum response of these indices was found in the varieties or the species that lost cell wall elasticity in response to drought stress. This could indicate an important structural component in these indices changes. Relative water content itself seemed to be, however, the most important factor as shown by the highest correlation coefficients with these spectral indices. These spectral signals were more evident at canopy level than at leaf level. They seem to be useful as water status indicators at ground level, especially when there are not important changes of LAI and when plants wholly cover the soil. ER - TY - JOUR ID - penuelas1997 AU - Penuelas, J. AU - Llusia, J. AU - Pinol, J. AU - Filella, I. TI - Photochemical reflectance index and leaf photosynthetic radiation-use-efficiency assessment in Mediterranean trees UR - http://dx.doi.org/10.1080/014311697217387 DO - 10.1080/014311697217387 T2 - International Journal of Remote Sensing PY - 1997 DA - 1997/09/01 SN - 0143-1161 VL - 18 IS - 13 SP - 2863-2868 AB - Abstract This Letter presents new data validating the use of the photochemical reflectance index PRI (R570-R531)/(R570 + R531) to assess photosynthetic- radiation-use-efficiency under mild water stress. Gas exchange, fluorescence and the PRI of leaves from the Mediterranean trees Quercus ilex and Phillyrea latifolia growing in the field were followed from spring to summer 1996 in central Catalonia (NE Spain). The same variables were measured in seedlings of these two species and Pistacia lentiscus submitted to progressive drying after witholding irrigation. Except for severely drought damaged plants, significant relations of the reflectance index PRI with fluorescence yield of the photosystem II (Delta F/F' m), non photochemical fluorescence quenching ( qN ) and photosynthetic radiation use efficiency (PRUE) were found, thus indicating a functional relation among these parameters. A simple portable radiometer measuring ground level reflectance at narrow bands centred at 531 and 570nm could instantaneously calculate the PRI index and give the PRUE estimation. ER - TY - JOUR ID - penuelas1997-2 AU - Penuelas, J. AU - Pinol, J. AU - Ogaya, R. AU - Filella, I. TI - Estimation of plant water concentration by the reflectance Water Index WI (R900/R970) UR - http://dx.doi.org/10.1080/014311697217396 DO - 10.1080/014311697217396 T2 - International Journal of Remote Sensing PY - 1997 DA - 1997/09/01 SN - 0143-1161 VL - 18 IS - 13 SP - 2869-2875 AB - Abstract Water Index WI (R900/R970) was used for the estimation of plant water concentration (PWC) by ground-based, reflectance measurements. Reflectance and PWC were measured for adult plants growing in the field throughout an annual cycle and in potted seedlings submitted to progressive desiccation. The species studied were characteristicly Mediterranean: Pinus halepensis, Quercus ilex, Quercus coccifera, Arbutus unedo, Cistus albidus, Cistus monspeliensis, Phillyrea angustifolia, Pistacia lentiscus and Brachypodium retusum . WI was significantly correlated with PWC when all the species were considered together, and with almost all the species considered individually, especially when a wider range of PWC was obtained by extreme dessication of experimental plants. The correlations increased when normalizing WI by NDVI. The wavelength of the trough corresponding to water absorption band tended to shift from 970-980 nm to lower wavelengths 930-950 nm with decreasing PWCs. Infrared measurement of plant temperature and T leaf - T air provided worse assessment of PWC. A simple radiometer measuring plant reflectance at 680, 900, and 970nm could speed up the measurement of PWC, and be useful in wildfire risk evaluation and drought assessment. ER - TY - JOUR ID - penuelas1995 AU - Penuelas, Josep AU - Filella, Iolanda AU - Gamon, John A. TI - Assessment of photosynthetic radiation-use efficiency with spectral reflectance UR - http://dx.doi.org/10.1111/j.1469-8137.1995.tb03064.x DO - 10.1111/j.1469-8137.1995.tb03064.x T2 - New Phytologist PY - 1995 SN - 1469-8137 VL - 131 IS - 3 SP - 291-296 AB - Reflectance changes at 531 nm, associated with the zeaxanthin-antheraxanthin-violaxanthin interconversion and the related thylakoid energization, are widespread among plant species. We evaluated an index based on 531 nm reflectance (‘PRI’, Photochemical Reflectance Index calculated as (R531- R570)/(R531+ R570)) as an indicator of efficiency of photosynthetic radiation use in seven species representing both C3 and CAM photosynthetic pathways. Leaves exposed to a dark-lighted ark transition in a steady-state laboratory gas exchange system exhibited nearly parallel changes in PRI and PS II quantum yield (?F/Fm'). Similar PRI and ?F/Fm' responses were seen in leaves exposed to diurnally changing sunlight levels outdoors. PRI was linearly related to ?F/Fm', and both ?F/Fm' and PRI were exponentially related to instantaneous efficiency of photosynthetic radiation-use in different species over a range of different field conditions. These results extend previous studies by indicating a functional relationship between PRI. ?F/Fm', and photosynthetic radiation-use efficiency. The narrow-band PRI index offers a simple, portable means of assessing PS II radiation-use efficiency, analogous to ?F/Fm', and with the potential for remote applications at scales larger than the leaf. KW - Photosynthetic radiation-use efficiency (PRUE) KW - reflectance and fluorescence KW - zeaxanthin KW - photochemical reflectance index (PRI) KW - quantum yield (?F/Fm') ER - TY - JOUR ID - pe_uelas1998 AU - Peñuelas, J. AU - Filella, I. TI - Visible and near-infrared reflectance techniques for diagnosing plant physiological status UR - http://dx.doi.org/10.1016/S1360-1385(98)01213-8 DO - 10.1016/S1360-1385(98)01213-8 T2 - Trends in Plant Science PY - 1998 SN - 13601385 VL - 3 IS - 4 SP - 151-156 ER - TY - JOUR ID - pe_uelas1994 AU - Peñuelas, J. AU - Gamon, J. A. AU - Fredeen, A. L. AU - Merino, J. AU - Field, C. B. TI - Reflectance indices associated with physiological changes in nitrogen- and water-limited sunflower leaves UR - http://www.sciencedirect.com/science/article/pii/0034425794901368 DO - 10.1016/0034-4257(94)90136-8 T2 - Remote Sensing of Environment PY - 1994 SN - 0034-4257 VL - 48 IS - 2 SP - 135-146 AB - We followed diurnal and seasonal changes in physiology and spectral reflectance of leaves throughout the canopies of sunflower plants grown in control, nitrogen (N)-limited, and water-stressed plots. Leaves from control sunflower plants had significantly higher levels of nitrogen, chlorophyll (chl), ribulose bis phosphate carboxylase / oxygenase (RuBPCase) activity and photosynthetic rates and lower starch content and leaf thickness than N-limited plants. Water-stressed plants had the highest N and chl contents (on an area basis). They also had the lowest water potential and photosynthetic rates, in spite of maintaining high RuBPCase activities. Leaves from stressed plants (especially N-limited) had significantly higher reflectances in the visible wavelengths and lower in the near IR than leaves from control plants. The only clear trend across canopy levels was the higher reflectance at all wavelengths but especially in the visible of the lower (oldest) leaves. NDVI-like parameters were useful in distinguishing stress and control leaves over the growing season. However, several narrow-band indices provided better physiological information than NDVI. The physiological reflectance index (PRI) (R550 - R530 / R550 + R530) followed diurnal changes in xanthophyll pigments and photosynthetic rates of control and N-limited leaves. The maximum of the first derivative of reflectance in the green (dG) was correlated with diurnal photosynthetic rate, and with seasonal chl and N changes. The normalized pigment chlorophyll ratio Index (NPCI) (R680 - R430 / R680 + R430) varied with total pigments / chl. The water band index (WBI) (R970 / R902) followed water status. The normalized ratio between the maxima of the first derivatives of reflectances at the red edge and green regions (EGFN) was correlated with chl and N content. Principal components analysis yielded several indicators of physiological status. The first principal component was higher in control leaves, the second was higher in N-limited leaves, and the third was higher in water-limited leaves. Discriminant analysis based on the combination of several narrow-band spectral indices clearly separated leaves into the three treatment groups. These results illustrate the promise of narrow-band spectroradiometry for assessing the physiological state of vegetation. ER - TY - JOUR ID - pe_uelas1993 AU - Peñuelas, Josep AU - Gamon, John A. AU - Griffin, Kevin L. AU - Field, Christopher B. TI - Assessing community type, plant biomass, pigment composition, and photosynthetic efficiency of aquatic vegetation from spectral reflectance UR - http://www.sciencedirect.com/science/article/pii/003442579390088F DO - 10.1016/0034-4257(93)90088-f T2 - Remote Sensing of Environment PY - 1993 SN - 0034-4257 VL - 46 IS - 2 SP - 110-118 AB - We studied the reflectance spectra of the aquatic vegetation of Searsville Lake in coastal central California using a high spectral resolution hand-held spectroradiometer. The three aquatic types—submerged, floating, and emergent—exhibited clear differences in their spectral reflectance and can be distinguished on the basis of discriminant analysis using reflectance parameters. This technique can be used in large-area mapping of aquatic plants. The normalized difference vegetation index (NDVI) and the simple ratio (SR) were well correlated with chlorophyll content, photosynthetic efficiency, and biomass in the emergent species. New, narrow-bandwidth indices and reflectance indices calculated from first and second derivative spectra were strongly correlated with the ratio of secondary and protective pigments to chlorophyll a and with epoxidation state of the xanthophyll cycle pigments, and therefore, with photosynthetic efficiency. These new indices may be useful in the remote sensing of plant physiological status. ER - TY - JOUR ID - pinder1999 AU - Pinder, J. E. AU - McLeod, K. W. TI - Indications of relative drought stress in longleaf pine from Thematic Mapper data T2 - Photogrammetric Engineering and Remote Sensing PY - 1999 VL - 65 SP - 495–501 ER - TY - JOUR ID - pinter2003 AU - Pinter, P. J. AU - Hatfield, J. L. AU - Schepers, J. S. AU - Barnes, E. M. AU - Moran, M. S. AU - Daughtry, C. S. T. AU - Upchurch, D. R. TI - Remote sensing for crop management UR - ://WOS:000221193400006 T2 - Photogrammetric Engineering and Remote Sensing PY - 2003 DA - Jun SN - 0099-1112 VL - 69 IS - 6 SP - 647-664 N1 - ISI Document Delivery No.: 817RA Times Cited: 88 Cited Reference Count: 256 Pinter, PJ Hatfield, JL Schepers, JS Barnes, EM Moran, MS Daughtry, CST Upchurch, DR Amer soc photogrammetry Bethesda AB - Scientists with the Agricultural Research Service (ARS) and various government agencies and private institutions have provided a great deal of fundamental information relating spectral reflectance and thermal emittance properties of soils and crops to their agronomic and biophysical characteristics. This knowledge has facilitated the development and use of various remote sensing methods for non-destructive monitoring of plant growth and development and for the detection of many environmental stresses which limit plant productivity. Coupled with rapid advances in computing and position-locating technologies, remote sensing from ground-, air-, and space-based platforms is now capable of providing detailed spatial and temporal information on plant response to their local environment that is needed for site specific agricultural management approaches. This manuscript, which emphasizes contributions by ARS researchers, reviews the biophysical basis of remote sensing; examines approaches that have been developed, refined, and tested for management of water, nutrients, and pests in agricultural crops; and assesses the role of remote sensing in yield prediction. It concludes with a discussion of challenges facing remote sensing in the future. KW - water-stress index KW - spectral-biophysical data KW - soil heat-flux KW - infrared KW - aerial photography KW - laser-induced fluorescence KW - constant leaf KW - temperature KW - adjusted vegetation index KW - surface-energy balance KW - clover-seed production KW - gossypium-hirsutum l ER - TY - JOUR ID - pinty1992 AU - Pinty, B. AU - Verstraete, M. M. TI - GEMI: a non-linear index to monitor global vegetation from satellites UR - http://dx.doi.org/10.1007/BF00031911 DO - 10.1007/bf00031911 T2 - Plant Ecology PY - 1992 SN - 1385-0237 VL - 101 IS - 1 SP - 15-20 AB - Knowledge about the state, spatial distribution and temporal evolution of the vegetation cover is of great scientific and economic value. Satellite platforms provide a most convenient tool to observe the biosphere globally and repetitively, but the quantitative interpretation of the observations may be difficult. Reflectance measurements in the visible and near-infrared regions have been analyzed with simple but powerful indices designed to enhance the contrast between the vegetation and other surface types, however, these indices are rather sensitive to atmospheric effects. The ‘correction’ of satellite data for atmospheric effects is possible but requires large data sets on the composition of the atmosphere. Instead, we propose a new vegetation index which has been designed specifically to reduce the relative effects of these undesirable atmospheric perturbations, while maintaining the information about the vegetation cover. KW - Biomedizin & Life Sciences ER - TY - JOUR ID - pu2003 AU - Pu, R. AU - Ge, S. AU - Kelly, N. M. AU - Gong, P. TI - Spectral absorption features as indicators of water status in coast live oak ( Quercus agrifolia ) leaves UR - http://dx.doi.org/10.1080/01431160210155965 DO - 10.1080/01431160210155965 T2 - International Journal of Remote Sensing PY - 2003 DA - 2003/01/01 SN - 0143-1161 VL - 24 IS - 9 SP - 1799-1810 AB - A total of 139 reflectance spectra (between 350 and 2500 nm) from coast live oak ( Quercus agrifolia ) leaves were measured in the laboratory with a spectrometer FieldSpec?Pro FR. Correlation analysis was conducted between absorption features, three-band ratio indices derived from the spectra and corresponding relative water content (RWC, %) of oak leaves. The experimental results indicate that there exist linear relationships between the RWC of oak leaves and absorption feature parameters: wavelength position (WAVE), absorption feature depth (DEP), width (WID) and the multiplication of DEP and WID (AREA) at the 975 nm, 1200 nm and 1750 nm positions and two three-band ratio indices: RATIO 975 and RATIO 1200, derived at 975 nm and 1200 nm. AREA has a higher and more stable correlation with RWC compared to other features. It is worthy of noting that the two three-band ratio indices, RATIO 975 and RATIO 1200, may have potential application in assessing water status in vegetation. ER - TY - JOUR ID - pu2008 AU - Pu, Ruiliang AU - Gong, Peng AU - Yu, Qian TI - Comparative Analysis of EO-1 ALI and Hyperion, and Landsat ETM+ Data for Mapping Forest Crown Closure and Leaf Area Index UR - http://www.mdpi.com/1424-8220/8/6/3744/ T2 - Sensors PY - 2008 SN - 1424-8220 VL - 8 IS - 6 SP - 3744-3766 ER - TY - JOUR ID - qi1994 AU - Qi, J. AU - Chehbouni, A. AU - Huete, A. R. AU - Kerr, Y. H. AU - Sorooshian, S. TI - A modified soil adjusted vegetation index UR - http://www.sciencedirect.com/science/article/pii/0034425794901341 DO - 10.1016/0034-4257(94)90134-1 T2 - Remote Sensing of Environment PY - 1994 SN - 0034-4257 VL - 48 IS - 2 SP - 119-126 AB - There is currently a great deal of interest in the quantitative characterization of temporal and spatial vegetation patterns with remotely sensed data for the study of earth system science and global change. Spectral models and indices are being developed to improve vegetation sensitivity by accounting for atmosphere and soil effects. The soil-adjusted vegetation index (SAVI) was developed to minimize soil influences on canopy spectra by incorporating a soil adjustment factor L into the denominator of the normalized difference vegetation index (NDVI) equation. For optimal adjustment of the soil effect, however, the L factor should vary inversely with the amount of vegetation present. A modified SAVI (MSAVI) that replaces the constant L in the SAVI equation with a variable L function is presented in this article. The L function may be derived by induction or by using the product of the NDVI and weighted difference vegetation index (WDVI). Results based on ground and aircraft-measured cotton canopies are presented. The MSAVI is shown to increase the dynamic range of the vegetation signal while further minimizing the soil background influences, resulting in greater vegetation sensitivity as defined by a “vegetation signal” to “soil noise” ratio. ER - TY - JOUR ID - richardson1992 AU - Richardson, A. J. AU - Everitt, J. H. TI - Using spectral vegetation indices to estimate rangeland productivity T2 - Geocartogr Int PY - 1992 VL - 1 SP - 63–69 ER - TY - JOUR ID - richardson1977 AU - Richardson, A.J. AU - Wiegand, C.L. TI - Distinguishing vegetation from soil background information T2 - Photogrammetric Engineering and Remote Sensing PY - 1977 VL - 43 IS - 2 SP - 1541-1552 ER - TY - JOUR ID - richardson2002 AU - Richardson, Andrew D. AU - Duigan, Shane P. AU - Berlyn, Graeme P. TI - An evaluation of noninvasive methods to estimate foliar chlorophyll content UR - http://dx.doi.org/10.1046/j.0028-646X.2001.00289.x DO - 10.1046/j.0028-646X.2001.00289.x PR - Blackwell Science Ltd T2 - New Phytologist PY - 2002 SN - 1469-8137 VL - 153 IS - 1 SP - 185-194 AB - Over the last decade, technological developments have made it possible to quickly and nondestructively assess, in situ, the chlorophyll (Chl) status of plants. We evaluated the performance of these optical methods, which are based on the absorbance or reflectance of certain wavelengths of light by intact leaves. * •As our benchmark, we used standard extraction techniques to measure Chla, Chlb, and total Chl content of paper birch (Betula papyrifera) leaves. These values were compared with the nominal Chl index values obtained with two hand-held Chl absorbance meters and several reflectance indices correlated with foliar Chl. * •The noninvasive optical methods all provided reliable estimates of relative leaf Chl. However, across the range of Chl contents studied (0.0004–0.0455 mg cm−2), some reflectance indices consistently out-performed the hand-held meters. Most importantly, the reflectance indices that performed best were not those most commonly used in the literature. * •We report equations to convert from index values to actual Chl content, but caution that differences in leaf structure may necessitate species-specific calibration equations. KW - absorbance KW - chlorophyll KW - Chla : Chlb leaf optical properties KW - pigment KW - red edge KW - reflectance KW - spectral index ER - TY - JOUR ID - richter2009 AU - Richter, K. AU - Atzberger, C. AU - Vuolo, F. AU - Weihs, P. AU - D’Urso, G. TI - Experimental assessment of the Sentinel-2 band setting for RTM-based LAI retrieval of sugar beet and maize UR - http://dx.doi.org/10.5589/m09-010 DO - 10.5589/m09-010 T2 - Canadian Journal of Remote Sensing PY - 2009 DA - 2009/06/01 VL - 35 IS - 3 SP - 230-247 ER - TY - JOUR ID - ricotta1999 AU - Ricotta, Carlo AU - Avena, Giancarlo AU - De Palma, Alessandra TI - Mapping and monitoring net primary productivity with AVHRR NDVI time-series: statistical equivalence of cumulative vegetation indices UR - http://www.sciencedirect.com/science/article/pii/S0924271699000283 DO - 10.1016/s0924-2716(99)00028-3 T2 - ISPRS Journal of Photogrammetry and Remote Sensing PY - 1999 SN - 0924-2716 VL - 54 IS - 5–6 SP - 325-331 AB - In the last two decades, numerous investigators have proposed cumulative vegetation indices (i.e., functions which encode the cumulative effect of NDVI maximum value composite time-series into a single variable) for net primary productivity (NPP) mapping and monitoring on a regional to continental basis. In this paper, we investigate the relationships among three of the most commonly used cumulative vegetation indices, expanding on the definition of equivalence of remotely sensed vegetation indices for decision making. We consider two cumulative vegetation indices as equivalent, if the value of one index is statistically predictable from the value of the other index. Using an annual time-series of broad-scale AVHRR NDVI monthly maximum value composites of the island of Corsica (France), we show that the pairwise linear association among the analysed cumulative vegetation indices shows coefficients of determination (R2) higher than 0.99. That is, knowing the value of one index is statistically equivalent to knowing the value of the other indices for application purposes. KW - Corsica KW - cumulative vegetation indices KW - Fourier transform KW - NDVI KW - net primary productivity ER - TY - JOUR ID - riedell1999 AU - Riedell, W.E. AU - Blackmer, T.M. TI - Leaf reflectance spectra of cereal aphid-damaged wheat T2 - Crop science PY - 1999 VL - 39 IS - 6 AB - The efficiency of field monitoring for insect pests would be improved with knowledge of reflected solar radiation from crop canopies during insect outbreaks. The objectives of this greenhouse study were to characterize leaf reflectance spectra of wheat (Triticum aestivum L.) damaged by Russian wheat aphids (Diuraphis noxia Mordvilko) and greenbugs (Schizaphis graminum Rondani) and to determine those leaf reflectance wavelengths that were most responsive to crop stress imposed by these aphid pests. When the ligule was visible on second oldest leaf, wheat plants were infested with four wingless adult Russian wheat aphids, four wingless adult greenbugs, or left uninfested (four replicate plants per treatment). Plants and aphid populations were allowed to grow under greenhouse conditions for 3 wk, after which leaf-reflected radiation (from the adaxial surface across the 350-1075 nm range), dry weight, area, and chlorophyll concentrations were measured. When compared with the control, greenbug feeding damage caused general necrosis in oldest (first) leaves and dramatically lowered the dry weight, leaf area, and chlorophyll concentration of the second, third, and fourth leaves. Russian wheat aphid feeding resulted in a reduction in leaf dry weight and area in the third and fourth leaves, and a reduction in total chlorophyll concentration in all leaves. Leaf reflectance in the 625- to 635-nm and the 680- to 695-nm ranges, as well as the normalized total pigment to chlorophyll a ratio index (NPCI), were significantly correlated with total chlorophyll concentrations in both greenbug- and Russian wheat aphid-damaged plants. Thus, both of these wavelength ranges, as well as this reflectance index, were good indicators of chlorophyll loss and leaf senescence caused by the aphid feeding damage. KW - Triticum aestivum KW - Diuraphis noxia KW - Schizaphis graminum KW - leaves KW - reflectance KW - defoliation KW - monitoring KW - methodology KW - leaf area KW - chlorophyll KW - senescence KW - spectral analysis KW - chemical constituents of plants ER - TY - JOUR ID - rondeaux1996 AU - Rondeaux, Geneviève AU - Steven, Michael AU - Baret, Frédéric TI - Optimization of soil-adjusted vegetation indices UR - http://www.sciencedirect.com/science/article/pii/0034425795001867 DO - 10.1016/0034-4257(95)00186-7 T2 - Remote Sensing of Environment PY - 1996 SN - 0034-4257 VL - 55 IS - 2 SP - 95-107 AB - The sensitivity of the normalized difference vegetation index (NDVI) to soil background and atmospheric effects has generated an increasing interest in the development of new indices, such as the soil-adjusted vegetation index (SAVI), transformed soil-adjusted vegetation index (TSAVI), atmospherically resistant vegetation index (AR VI), global environment monitoring index (GEMI), modified soil-adjusted vegetation index (MSAVI), which are less sensitive to these external influences. These indices are theoretically more reliable than NDVI, although they are not yet widely used with satellite data. This article focuses on testing and comparing the sensitivity of NDVI, SAVI, TSAVI, MSAVI and GEMI to soil background effects. Indices are simulated with the SAIL model for a large range of soil reflectances, including sand, clay, and dark peat, with additional variations induced by moisture and roughness. The general formulation of the SAVI family of indices with the form VI = (NIR - R) / (NIR + R + X) is also reexamined. The value of the parameter X is critical in the minimization of soil effects. A value of X = 0.16 is found as the optimized value. Index performances are compared by means of an analysis of variance. ER - TY - GEN ID - rouse1973 AU - Rouse, J.W., Jr. AU - Haas,R.H. AU - Schell, J.A. AU - Deering, D.W. TI - Monitoring the vernal advancement and retrogradation (green wave effect) of natural vegetation T2 - Prog. Rep. RSC 1978-1 CY - Remote Sensing Center, Texas A&M Univ., College Station PY - 1973 SP - 93p N1 - ER - TY - CONF ID - rouse1974 AU - Rouse, J.W. AU - Haas, R.H. AU - Schell, J.A. AU - Deering, D.W. TI - Monitoring vegetation systems in the Great Plains with ERTS T2 - Proceedings of the Third Earth Resources Technology Satellite- 1 Symposium CY - Greenbelt, NASA SP-351 PY - 1974 SP - 301–317 ER - TY - JOUR ID - royo2003 AU - Royo, C. AU - Aparicio, N. AU - Villegas, D. AU - Casadesus, J. AU - Monneveux, P. AU - Araus, J. L. TI - Usefulness of spectral reflectance indices as durum wheat yield predictors under contrasting Mediterranean conditions UR - http://dx.doi.org/10.1080/0143116031000150059 DO - 10.1080/0143116031000150059 T2 - International Journal of Remote Sensing PY - 2003 DA - 2003/01/01 SN - 0143-1161 VL - 24 IS - 22 SP - 4403-4419 ER - TY - JOUR ID - schlerf2005 AU - Schlerf, M. AU - Atzberger, C. AU - Hill, J. TI - Remote sensing of forest biophysical variables using HyMap imaging spectrometer data T2 - Remote Sensing of Environment PY - 2005 VL - 95 SP - 177−194 ER - TY - JOUR ID - schmidt2001 AU - Schmidt, H. AU - Karnieli, A. TI - Sensitivity of vegetation indices to substrate brightness in hyper-arid environment: The Makhtesh Ramon Crater (Israel) case study UR - http://dx.doi.org/10.1080/01431160110063779 DO - 10.1080/01431160110063779 T2 - International Journal of Remote Sensing PY - 2001 DA - 2001/01/01 SN - 0143-1161 VL - 22 IS - 17 SP - 3503-3520 AB - The influence of soil background on most vegetation indices (VIs) derived from remotely sensed imagery is a well known phenomenon, and has generated interest in the development of indices that would be less sensitive to this influence. Several such indices have been developed thus far. This paper focuses on testing and comparing the sensitivity of seven intensively used, Landsat Thematic Mapper (TM) derived, VIs (NDVI, SAVI, MSAVI, PVI, WDVI, SAVI 2 and TSAVI) to bare surface variation with almost no vegetation signal. The study was conducted on a terrain composed of a high variety of bare surface materials of which basalt and gypsum are two extremely dark and bright substrates respectively. It was found that SAVI and MSAVI respond to bare surface material very similarly. Such close similarity was also found between PVI and WDVI, and between SAVI 2 and TSAVI. NDVI tends to be overestimated on dark surfaces, while SAVI, PVI and TSAVI show more sensitivity to bright surfaces. Comparison between DeltaVI (the difference between pairs of VIs) and the brightness of the different surface materials showed a high correlation in each case, which underlines the fact that the response of different VIs to bare surface variation is mainly related to the surface brightness. ER - TY - JOUR ID - serrano2000 AU - Serrano, Lydia AU - Filella, Iolanda AU - Peñuelas, Josep TI - Remote Sensing of Biomass and Yield of Winter Wheat under Different Nitrogen Supplies UR - https://www.crops.org/publications/cs/abstracts/40/3/723 DO - 10.2135/cropsci2000.403723x T2 - Crop Science PY - 2000 DA - 2000/5 VL - 40 IS - 3 SP - 723-731 AB - Vegetation indices derived from reflectance data are related to canopy variables such as aboveground biomass, leaf area index (LAI), and the fraction of intercepted photosynthetically active radiation (fIPAR). However, under N stress the relationships between vegetation indices (VI) and these canopy variables might be confounded due to plant chlorosis. We studied the relationships between reflectance-based VI and canopy variables (aboveground biomass, LAI canopy chlorophyll A content [LAI × Chl A], and fIPAR) for a wheat (Triticum aestivum L.) crop growing under different N supplies. Nitrogen fertilization promoted significant increases in radiation interception (plant growth) and, to a lesser extent, in radiation use efficiency (RUE). The VI vs. LAI relationships varied significantly among treatments, rendering the VI-based equations unreliable to estimate LAI under contrasting N conditions. However, a single relationship emerged when LAI × Chl A was considered. Moreover, VI were robust indicators of fIPAR by green canopy components independently of N treatment and phenology. Aboveground biomass was poorly correlated with grain yield, whereas cumulative VI simple ratio (SR) was a good predictor of grain yield, probably because cumulative SR closely tracked the duration and intensity of the canopy photosynthetic capacity. ER - TY - JOUR ID - serrano2002 AU - Serrano, Lydia AU - Peñuelas, Josep AU - Ustin, Susan L. TI - Remote sensing of nitrogen and lignin in Mediterranean vegetation from AVIRIS data: Decomposing biochemical from structural signals UR - http://www.sciencedirect.com/science/article/pii/S0034425702000111 DO - 10.1016/s0034-4257(02)00011-1 T2 - Remote Sensing of Environment PY - 2002 SN - 0034-4257 VL - 81 IS - 2–3 SP - 355-364 AB - Remote sensing estimates of vegetation nitrogen (N) and lignin concentration are central to assess ecosystem processes such as growth and decomposition. Although remote sensing techniques have been proven useful to assess N and lignin contents in continuous green canopies, more studies are needed to address their capabilities, particularly in low and sparsely vegetated ecosystems. We investigated the possibility of estimating canopy N and lignin concentrations in chaparral vegetation using Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) reflectance acquired over an area around Point Dume in the Santa Monica Mountains (Los Angeles, CA, USA). Two approaches were tested: multiple stepwise regression based on first difference reflectance (FDR) and reflectance (R) indices. Multiple stepwise regressions (of three or fewer wavelengths) accounted for a large variance in canopy biochemical concentration (r2∼0.9, P<0.01). Log transformed R indices [log (1/R)] formulated on the basis of previously known N and lignin absorption wavelengths also showed significant correlations (P<0.01) with canopy biochemical concentration (r2 ranging from 0.39 to 0.48). In addition, the contribution of structural and biochemical signals and background effects on the performance of these indices was evaluated. These indices accounted for a increased variance when adding information on canopy structural attributes (e.g., relative contribution of each species and biomass amount) to foliar biochemical concentration. The relative contributions of foliar biochemical concentration and canopy structure (biomass amount) on the spectral signal were further evaluated by analyzing the residuals from linear regressions: foliar N concentration accounted for 42% of the variance for a normalized difference index based on the 1510-nm N absorption feature, while the foliar lignin concentration accounted for 44% of the variance for a normalized difference index based on the 1754 nm lignin absorption feature. These percentages increased to 58% when stands with senescing vegetation were disregarded. We propose the two indices, Normalized Difference Nitrogen Index (NDNI=[log (1/R1510)−log (1/R1680)]/[log (1/R1510)+log (1/R1680)]) and Normalized Difference Lignin Index (NDLI=[log (1/R1754)−log (1/R1680)]/[log (1/R1754)+log (1/R1680)]) as indices to assess N and lignin in native shrub vegetation. ER - TY - JOUR ID - serrano2000-2 AU - Serrano, Lydia AU - Ustin, Susan L. AU - Roberts, Dar A. AU - Gamon, John A. AU - Peñuelas, Josep TI - Deriving Water Content of Chaparral Vegetation from AVIRIS Data UR - http://www.sciencedirect.com/science/article/pii/S0034425700001474 DO - 10.1016/s0034-4257(00)00147-4 T2 - Remote Sensing of Environment PY - 2000 SN - 0034-4257 VL - 74 IS - 3 SP - 570-581 AB - Spectral imaging data acquired with Advanced Visible Infrared Imaging Spectrometer over Point Dume (Los Angeles County, CA, USA) were used to assess the ability of hyperspectral reflectance data to estimate canopy Relative Water Content (RWC) at the landscape level. The study was performed on 23 vegetation stands comprised of three characteristic chaparral plant communities, with contrasting phenological stages and canopy cover. Several estimates of water content based on the near-infrared (NIR; reflectance indices and water thickness derived from reflectance and radiance data) and shortwave infrared (SWIR) water absorption bands were compared to measurements of vegetation structure and water content made on the ground. The Water Index (WI) and Normalized Difference Water Index (NDWI), reflectance indices formulated from the NIR water absorption bands, were the best indicators of canopy RWC estimated from combining leaf relative water content with measures of canopy structure. A stepwise multiple regression revealed that canopy structure explained 36% and 41% of the variation in WI and NDWI, respectively. The explained variance in WI and NDWI increased to 44% and 48% when leaf relative water content was included in the model. By contrast, the inclusion of leaf relative water content did not contribute significantly to the explained variance in indices formulated using SWIR water absorption bands and in those based on water thickness. The relationship between WI and the canopy RWC significantly improved when only data from plots with green vegetation cover >70% were considered (r2=0.88, p<0.001). All the indices studied had an important structural component (as indicated by the strong correlation with NDVI), yet only the indices WI and NDWI additionally responded to water content. These results indicate that the WI and NDWI are sensitive to variations in canopy relative water content at the landscape scale. ER - TY - JOUR ID - shibayama1999 AU - Shibayama, Michio AU - Salli, Arto AU - Häme, Tuomas AU - Iso-Iivari, Lasse AU - Heino, Saini AU - Alanen, Marjaana AU - Morinaga, Shinsuke AU - Inoue, Yoshio AU - Akiyama, Tsuyoshi TI - Detecting Phenophases of Subarctic Shrub Canopies by Using Automated Reflectance Measurements UR - http://www.sciencedirect.com/science/article/pii/S0034425798000820 DO - 10.1016/s0034-4257(98)00082-0 T2 - Remote Sensing of Environment PY - 1999 SN - 0034-4257 VL - 67 IS - 2 SP - 160-180 AB - Boreal and subarctic plant phenophases are advantageous indicators of climatic change on a global scale. Remote sensing is a promising technique for assessing such changes over extended areas. An automated field measuring system collected seasonal reflectances of natural shrubs in visible, near-, and mid-infrared wavelength ranges. A boom-mounted four-band spectroradiometer was installed on a 4-m-high tower to measure seasonal radiances in green (520–600 nm), red (630–690 nm), near-infrared (765–900 nm), and mid-infrared (1570–1730 nm) spectral bands from undisturbed subarctic shrub vegetation during the 1994 and 1995 growing seasons (mid-June to mid-September) in northernmost Finland (69°45'N, 27°00'E, 105 m above sea level). The radiometer was vertically looking down on four fixed ground plots and a weatherproof reference panel continuously during all the daylight hours. The reflectance factor calculations, using the reference panel and solarimeter readings, included corrections for the reference panel degradation and non-Lambertian characteristics. Daily averages of visible and near-infrared band reflectance factors offered smooth seasonal trends in spite of the variation in solar irradiance at the times of data collection. The turning point dates in the trends of seasonal near-infrared (765–900 nm) and red (630–690 nm) reflectance factors might indicate the end of growth and the beginning of autumn changes, respectively. The normalized difference vegetation index and ratio of green (520–600 nm) to red (630–690 nm) band reflectance factors, however, seemed to be more accurate in monitoring them. ER - TY - JOUR ID - sims2002 AU - Sims, Daniel A. AU - Gamon, John A. TI - Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages UR - http://www.sciencedirect.com/science/article/pii/S003442570200010X DO - 10.1016/s0034-4257(02)00010-x T2 - Remote Sensing of Environment PY - 2002 SN - 0034-4257 VL - 81 IS - 2–3 SP - 337-354 AB - Leaf pigment content can provide valuable insight into the physiological performance of leaves. Measurement of spectral reflectance provides a fast, nondestructive method for pigment estimation. A large number of spectral indices have been developed for estimation of leaf pigment content. However, in most cases these indices have been tested for only one or at most a few related species and thus it is not clear whether they can be applied across species with varying leaf structural characteristics. Our objective in this study was to develop spectral indices for prediction of leaf pigment content that are relatively insensitive to species and leaf structure variation and thus could be applied in larger scale remote-sensing studies without extensive calibration. We also quantified the degree of spectral interference between pigments when multiple pigments occur within the same leaf tissue. We found that previously published spectral indices provided relatively poor correlations with leaf chlorophyll content when applied across a wide range of species and plant functional types. Leaf surface reflectance appeared to be the most important factor in this variation. By developing a new spectral index that reduces the effect of differences in leaf surface reflectance, we were able to significantly improve the correlations with chlorophyll content. We also found that an index based on the first derivative of reflectance in the red edge region was insensitive to leaf structural variation. The presence of other pigments did not significantly affect estimation of chlorophyll from spectral reflectance. Previously published carotenoid and anthocyanin indices performed poorly across the whole data set. However, we found that the photochemical reflectance index (PRI, originally developed for estimation of xanthophyll cycle pigment changes) was related to carotenoid/chlorophyll ratios in green leaves. This result has important implications for the interpretation of PRI measured at both large and small scales. Our results demonstrate that spectral indices can be applied across species with widely varying leaf structure without the necessity for extensive calibration for each species. This opens up new possibilities for assessment of vegetation health in heterogeneous natural environments. ER - TY - GEN ID - smith1995 AU - Smith, RCG AU - Adams, J AU - Stephens, DJ AU - Hick, PT TI - Forecasting wheat yield in a Mediterranean-type environment from the NOAA satellite UR - http://www.publish.csiro.au/paper/AR9950113 DO - http://dx.doi.org/10.1071/AR9950113 T2 - Australian Journal of Agricultural Research PY - 1995 VL - 46 IS - 1 SP - 113-125 AB - This paper reports the relationship between the spatial variation in mean wheat yield/ha of 50 Local Government Areas in Western Australia and satellite measures of the Normalized Difference Vegetation Index (NDVI). Yield/ha was based on estimates of the area harvested and actual grain received by the Cooperative Bulk Handling Ltd. The study area covered 16.3 million ha, in which 2.9 million ha of wheat were sown and 4.66 million tonnes of grain harvested. This was 78% of the total Western Australian wheat crop. Spatial variations in NDVI in early July, at around stem elongation, accounted for 46% of the spatial variation in final yield. This increased to 56% of yield variance around the onset of anthesis at the end of August. It remained high until early November (48%) when crops were senescing or senescent. A combination of NDVI from late August and early November accounted for 70% of the yield variance. In comparison, total rainfall during the 1992 growing season from April to October, the main determinant of yield variations, accounted for 28% of the yield variation. The significant correlation of NDVI with final yield by the middle of the growing season 3 to 5 months before harvest indicates the feasibility of making useful yield forecasts from this time onwards. In addition, the NDVI could provide useful spatial information on the significance of the yield/canopy development/water use relationship which underlies this correlation. ER - TY - JOUR ID - strachan2002 AU - Strachan, Ian B. AU - Pattey, Elizabeth AU - Boisvert, Johanne B. TI - Impact of nitrogen and environmental conditions on corn as detected by hyperspectral reflectance DO - 10.1016/s0034-4257(01)00299-1 T2 - Remote Sensing of Environment PY - 2002 SN - 0034-4257 VL - 80 IS - 2 SP - 213-224 AB - Indices derived from hyperspectral reflectance spectra have the potential to be used as indicators of environmental stress in crops. This study uses canopy-scale, ground-based measurements of hyperspectral reflectance to demonstrate the temporal patterns in corn development under imposed fertility (N rate) and environmental (water availability) stresses. In 1998, two large areas in a 30-ha corn (Zea mays, L.) field near Ottawa, Canada (45°18′N, 75°44′W) were supplied with 99 and 17 kg N ha−1, while the balance of the field received the recommended rate of 155 kg N ha−1. Reflectance measurements were taken nine times using a portable spectroradiometer at georeferenced locations within these areas. Individual reflectance-based indices demonstrated the relative differences between application rates and identified both nitrogen and water stresses at various times in the growing season. No single index was able to describe the status of the corn crop throughout the season. Canonical discriminant analysis provided accurate classification of samples by N rate during early, mid, and late season conditions with overall success rates of 70%, 88%, and 93%, respectively. A shift in importance from green-based derivatives to red-based derivatives was noted from mid to late season and attributed to the natural reduction in green pigments as the crop entered senescence. Canopy-scale photochemical reflectance index (PRI) was shown to be correlated with canopy radiation use efficiency (RUE). Mid-season water stress affected the relationship. Multiple years of data are required to demonstrate robust relationships between hyperspectral indices and corn ecophysiological status because of the interaction between environmental and nutrient stresses. Identifying areas of fields sensitive to weather-induced stresses will allow better management of N application. Timing the collection of hyperspectral image data at early and late vegetative phase could enhance precision agriculture by allowing supplemental nutrient application, identifying stress patterns and aid in yield forecasting. KW - Hyperspectral reflectance KW - Precision agriculture KW - Stress detection KW - Corn field KW - Radiation use efficiency KW - Chlorophyll KW - Leaf area index KW - Crop water content ER - TY - JOUR ID - thenkabail2002 AU - Thenkabail, P. S. AU - Smith, R. B. AU - De Pauw, E. TI - Evaluation of narrowband and broadband vegetation indices for determining optimal hyperspectral wavebands for agricultural crop characterization T2 - Photogrammetric Engineering And Remote Sensing PY - 2002 VL - 68 IS - 6 SP - 607-621 ER - TY - JOUR ID - thenot2002 AU - Thenot, F. AU - Méthy, M. AU - Winkel, T. TI - The Photochemical Reflectance Index (PRI) as a water-stress index UR - http://dx.doi.org/10.1080/01431160210163100 DO - 10.1080/01431160210163100 T2 - International Journal of Remote Sensing PY - 2002 DA - 2002/01/01 SN - 0143-1161 VL - 23 IS - 23 SP - 5135-5139 AB - Measurements of leaf reflectance in two narrow wavelength bands centred around 531 and 570 nm were carried out during withering of two contrasting functional and structural plant types: Chenopodium quinoa (Willd.) and Arbutus unedo (L.). The Photochemical Reflectance Index (PRI)=( R 531 - R 570 )/ ( R 531 + R 570 ) was calculated. The results showed that PRI could be used as a reliable water-stress index. However, some limits to the use of PRI have to be emphasized, e.g. the wilting of leaves during dry periods. If such limits are under control, PRI could be a non-destructive and low cost method for assessing plant water status. ER - TY - JOUR ID - tucker1979 AU - Tucker, C. J. AU - Elgin Jr, J. H. AU - McMurtrey Iii, J. E. AU - Fan, C. J. TI - Monitoring corn and soybean crop development with hand-held radiometer spectral data UR - http://www.sciencedirect.com/science/article/pii/003442577990004X DO - 10.1016/0034-4257(79)90004-x T2 - Remote Sensing of Environment PY - 1979 SN - 0034-4257 VL - 8 IS - 3 SP - 237-248 AB - Red and photographic infrared data were collected with a hand-held radiometer under a variety of conditions at 4- to 12-day intervals throughout the growing season and were used to monitor corn and soybean growth and development. The normalized difference transformation was used to effectively compensate for the variation in irradiational conditions. With these data, plotted against time, green-leaf biomass dynamics were compared between the crops. By this approach, based entirely upon spectral inputs, the crop canopies were nondestructively monitored. Five spectral stages were defined and were related to crop development for corn and soybeans. ER - TY - JOUR ID - underwood2003 AU - Underwood, Emma AU - Ustin, Susan AU - DiPietro, Deanne TI - Mapping nonnative plants using hyperspectral imagery UR - http://www.sciencedirect.com/science/article/pii/S0034425703000968 DO - 10.1016/s0034-4257(03)00096-8 T2 - Remote Sensing of Environment PY - 2003 SN - 0034-4257 VL - 86 IS - 2 SP - 150-161 AB - Nonnative plant species are causing enormous ecological and environmental impacts from local to global scale. Remote sensing images have had mixed success in providing spatial information on land cover characteristics to land managers that increase effective management of invasions into native habitats. However, there has been limited evaluation of the use of hyperspectral data and processing techniques for mapping specific invasive species based on their spectral characteristics. This research evaluated three different methods of processing hyperspectral imagery: minimum noise fraction (MNF), continuum removal, and band ratio indices for mapping iceplant (Carpobrotus edulis) and jubata grass (Cortaderia jubata) in California's coastal habitat. Validation with field sampling data showed high mapping accuracies for all methods for identifying presence or absence of iceplant (97%), with the MNF procedure producing the highest accuracy (55%) when the classes were divided into four different densities of iceplant. KW - AVIRIS KW - Hyperspectral KW - Invasive plants KW - Nonnative plants KW - Iceplant KW - Carpobrotus edulis KW - Jubata grass KW - Cortaderia jubata KW - Mapping ER - TY - JOUR ID - vogelmann1993 AU - Vogelmann, J.E. AU - Rock, B.N. AU - Moss, D.M. TI - Red Edge Spectral Measurements from Sugar Maple Leaves UR - http://dx.doi.org/10.1080/01431169308953986 DO - 10.1080/01431169308953986 PR - Taylor & Francis T2 - International Journal of Remote Sensing PY - 1993 SN - 0143-1161 VL - 14 IS - 8 SP - 1563-1575 AB - Abstract Many sugar maple stands in the northeastern United States experienced extensive insect damage during the 1988 growing season. Chlorophyll data and high spectral resolution spectrometer laboratory reflectance data were acquired for multiple collections of single detached sugar maple leaves variously affected by the insect over the 1988 growing season. Reflectance data indicated consistent and diagnostic differences in the red edge portion (680-750 nm) of the spectrum among the various samples and populations of leaves. These included differences in the red edge inflection point (REIP), a ratio of reflectance at 740-720 nm (RE3/RE2), and a ratio of first derivative values at 715-705 nm (D715/D705), All three red edge parameters were highly correlated with variation in total chlorophyll content. Other spectral measures, including the Normalized Difference Vegetation Index (NDVI) and the Simple Vegetation Index Ratio (VI), also varied among populations and over the growing season, but did not correlate well with total chlorophyll content. Leaf stacking studies on light and dark backgrounds indicated REIP, RE3/RE2 and D715/D705 to be much less influenced by differences in green leaf biomass and background condition than either NDVI or VI. ER - TY - JOUR ID - wang2007 AU - Wang, Fu-min AU - Huang, Jing-feng AU - Tang, Yan-lin AU - Wang, Xiu-zhen TI - New Vegetation Index and Its Application in Estimating Leaf Area Index of Rice UR - http://www.sciencedirect.com/science/article/pii/S1672630807600274 DO - 10.1016/s1672-6308(07)60027-4 T2 - Rice Science PY - 2007 SN - 1672-6308 VL - 14 IS - 3 SP - 195-203 AB - Leaf area index (LAI) is an important characteristic of land surface vegetation system, and is also a key parameter for the models of global water balancing and carbon circulation. By using the reflectance values of Landsat-5 blue, green and red channels simulated from rice reflectance spectrum, the sensitivities of the bands to LAI were analyzed, and the response and capability to estimate LAI of various NDVIs (normalized difference vegetation indices), which were established by substituting the red band of general NDVI with all possible combinations of red, green and blue bands, were assessed. Finally, the conclusion was tested by rice data at different conditions. The sensitivities of red, green and blue bands to LAI were different under various conditions. When LAI was less than 3, red and blue bands were more sensitive to LAI. Though green band in the circumstances was less sensitive to LAI than red and blue bands, it was sensitive to LAI in a wider range. When the vegetation indices were constituted by all kinds of combinations of red, green and blue bands, the premise for making the sensitivity of these vegetation indices to LAI be meaningful was that the value of one of the combinations was greater than 0.024, i.e. visible reflectance (VIS)>0.024. Otherwise, the vegetation indices would be saturated, resulting in lower estimation accuracy of LAI. Comparison on the capabilities of the vegetation indices derived from all kinds of combinations of red, green and blue bands to LAI estimation showed that GNDVI (Green NDVI) and GBNDVI (Green-Blue NDVI) had the best relations with LAI. The capabilities of GNDVI and GBNDVI to LAI estimation were tested under different circumstances, and the same result was acquired. It suggested that GNDVI and GBNDVI performed better to predict LAI than the conventional NDVI. KW - vegetation index KW - rice KW - leaf area index KW - reflectance spectrum KW - remote sensing ER - TY - JOUR ID - wilson2002 AU - Wilson, Emily Hoffhine AU - Sader, Steven A. TI - Detection of forest harvest type using multiple dates of Landsat TM imagery UR - http://www.sciencedirect.com/science/article/pii/S0034425701003182 DO - 10.1016/s0034-4257(01)00318-2 T2 - Remote Sensing of Environment PY - 2002 SN - 0034-4257 VL - 80 IS - 3 SP - 385-396 AB - A simple and relatively accurate technique for classifying time-series Landsat Thematic Mapper (TM) imagery to detect levels of forest harvest is the topic of this research. The accuracy of multidate classification of the normalized difference vegetation index (NDVI) and the normalized difference moisture index (NDMI) were compared and the effect of the number of years (1–3, 3–4, 5–6 years) between image acquisition on forest change accuracy was evaluated. When Landsat image acquisitions were only 1–3 years apart, forest clearcuts were detected with producer's accuracy ranging from 79% to 96% using the RGB-NDMI classification method. Partial harvests were detected with lower producer's accuracy (55–80%) accuracy. The accuracy of both clearcut and partial harvests decreased as time between image acquisition increased. In all classification trials, the RGB-NDMI method produced significantly higher accuracies, compared to the RGB-NDVI. These results are interesting because the less common NDMI (using the reflected middle infrared band) outperformed the more popular NDVI. In northern Maine, industrial forest landowners have shifted from clearcutting to partial harvest systems in recent years. The RGB-NDMI change detection classification applied to Landsat TM imagery collected every 2–3 years appears to be a promising technique for monitoring forest harvesting and other disturbances that do not remove the entire overstory canopy. ER - TY - JOUR ID - wittich1995 AU - Wittich, K. P. AU - Hansing, O. TI - AREA-AVERAGED VEGETATIVE COVER FRACTION ESTIMATED FROM SATELLITE DATA UR - ://WOS:A1995RB98100008 DO - 10.1007/bf01245391 T2 - International Journal of Biometeorology PY - 1995 DA - May SN - 0020-7128 VL - 38 IS - 4 SP - 209-215 N1 - Times Cited: 52 AB - The relationship was analysed between the vegetation cover factor expressed as a percentage and the area-averaged normalized difference vegetation index (NDVI). On selected days the NDVI was calculated from channel 1 and 2 reflectance data of the National Oceanic and Atmospheric Administration (NOAA-11) satellite's advanced very high-resolution radiometer (AVHRR) for five test areas under agricultural and forestry use. No ground-based reflectance measurements could be made for validation of these data. Therefore the land surface NDVI, which varied with time, and percentage vegetation cover of the test areas were deduced from time-independent but site-specific statistical land use data updated by temporal phenological observations, and from surface-specific reflectance curves published in the literature. The result indicated that the area-averaged NDVI, as obtained from the NOAA-11 radiometer, was less than the value calculated from the land surface NDVI. After correction to reduce the offset of the data, the values would be a suitable indicator of the fraction of vegetation cover. ER - TY - JOUR ID - wu2008 AU - Wu, Chaoyang AU - Niu, Zheng AU - Tang, Quan AU - Huang, Wenjiang TI - Estimating chlorophyll content from hyperspectral vegetation indices: Modeling and validation UR - http://www.sciencedirect.com/science/article/pii/S0168192308000920 DO - 10.1016/j.agrformet.2008.03.005 T2 - Agricultural and Forest Meteorology PY - 2008 SN - 0168-1923 VL - 148 IS - 8–9 SP - 1230-1241 AB - Leaf chlorophyll content, a good indicator of photosynthesis activity, mutations, stress and nutritional state, is of special significance to precision agriculture. Recent studies have demonstrated the feasibility of retrieval of chlorophyll content from hyperspectral vegetation indices composed by the reflectance of specific bands. In this paper, a set of vegetation indices belonged to three classes (normalized difference vegetation index (NDVI), modified simple ratio (MSR) index and the modified chlorophyll absorption ratio index (MCARI, TCARI) and the integrated forms (MCARI/OSAVI and TCARI/OSAVI)) were tested using the PROSPECT and SAIL models to explore their potentials in chlorophyll content estimation. Different bands combinations were also used to derive the modified vegetation indices. In the sensitivity study, four new formed indices (MSR[705,750], MCARI[705,750], TCARI/OSAVI[705,750] and MCARI/OSAVI[705,750]) were proved to have better linearity with chlorophyll content and resistant to leaf area index (LAI) variations by taking into account the effect of quick saturation at 670 nm with relatively low chlorophyll content. Validation study was also conducted at canopy scale using the ground truth data in the growth duration of winter wheat (chlorophyll content and reflectance data). The results showed that the integrated indices TCARI/OSAVI[705,750] and MCARI/OSAVI[705,750] are most appropriate for chlorophyll estimation with high correlation coefficients R2 of 0.8808 and 0.9406, respectively, because more disturbances such as shadow, soil reflectance and nonphotosynthetic materials are taken into account. The high correlation between the vegetation indices obtained in the developmental stages of wheat and Hyperion data (R2 of 0.6798 and 0.7618 for TCARI/OSAVI[705,750] and MCARI/OSAVI[705,750], respectively) indicated that these two integrated index can be used in practice to estimate the chlorophylls of different types of corns. KW - Vegetation indices KW - Sensitivity KW - Chlorophyll content KW - LAI KW - Validation ER - TY - JOUR ID - wu2009 AU - Wu, Chaoyang AU - Niu, Zheng AU - Tang, Quan AU - Huang, Wenjiang AU - Rivard, Benoit AU - Feng, Jilu TI - Remote estimation of gross primary production in wheat using chlorophyll-related vegetation indices UR - http://www.sciencedirect.com/science/article/pii/S0168192308003560 DO - 10.1016/j.agrformet.2008.12.007 T2 - Agricultural and Forest Meteorology PY - 2009 SN - 0168-1923 VL - 149 IS - 6–7 SP - 1015-1021 AB - A number of recent studies have focused on estimating gross primary production (GPP) using vegetation indices (VIs). In this paper, GPP is retrieved as a product of incident light use efficiency (LUE), defined as GPP/PAR, and the photosynthetically active radiation (PAR). As a good correlation is found between canopy chlorophyll content and incident LUE for six types of wheat canopy (R2 = 0.87, n = 24), indices aimed for chlorophyll assessment can be used as an indicator of incident LUE and the product of chlorophyll indices and PAR will be a proxy of GPP. In a field experiment, we investigated four canopy chlorophyll content related indices (Red edge Normalized Difference Vegetation Index [Red Edge NDVI], modified Chlorophyll Absorption Ratio Index [MCARI710], Red Edge Chlorophyll Index [CIred edge] and the MERIS Terrestrial Chlorophyll Index [MTCI]) for GPP estimation during the growth cycle of wheat. These indices are validated for leaf and canopy chlorophyll estimation with ground truth data of canopy chlorophyll content. With ground truth data, a strong correlation is observed for canopy chlorophyll estimation with correlation coefficients R2 of 0.79, 0.84, 0.85 and 0.87 for Red Edge NDVI, MCARI710, CIred edge and MTCI, respectively (n = 24). As evidence of the existence of a relationship between canopy chlorophyll and GPP/PAR, these indices are shown to be a good proxy of GPP/PAR with R2 ranging from 0.70 for Red Edge NDVI and 0.75 for MTCI (n = 240). Remote estimation of GPP from canopy chlorophyll content Ã— PAR is proved to be relatively successful (R2 of 0.47, 0.53, 0.65 and 0.66 for Red edge NDVI, MCARI710, CIred edge and MTCI respectively, n = 240). These results open up a new possibility to estimate GPP and should inspire new models for remote sensing of GPP. KW - GPP KW - LUE KW - Vegetation indices KW - Canopy chlorophyll content KW - Sensitivity KW - Validation ER - TY - JOUR ID - wu2007 AU - Wu, Jindong AU - Wang, Dong AU - Bauer, Marvin E. TI - Assessing broadband vegetation indices and QuickBird data in estimating leaf area index of corn and potato canopies UR - http://www.sciencedirect.com/science/article/pii/S0378429007000160 DO - 10.1016/j.fcr.2007.01.003 T2 - Field Crops Research PY - 2007 SN - 0378-4290 VL - 102 IS - 1 SP - 33-42 AB - Leaf area index (LAI) is a key biophysical variable that can be used to derive agronomic information for field management and yield prediction. In the context of applying broadband and high spatial resolution satellite sensor data to agricultural applications at the field scale, an improved method was developed to evaluate commonly used broadband vegetation indices (VIs) for the estimation of LAI with VI–LAI relationships. The evaluation was based on direct measurement of corn and potato canopies and on QuickBird multispectral images acquired in three growing seasons. The selected VIs were correlated strongly with LAI but with different efficiencies for LAI estimation as a result of the differences in the stabilities, the sensitivities, and the dynamic ranges. Analysis of error propagation showed that LAI noise inherent in each VI–LAI function generally increased with increasing LAI and the efficiency of most VIs was low at high LAI levels. Among selected VIs, the modified soil-adjusted vegetation index (MSAVI) was the best LAI estimator with the largest dynamic range and the highest sensitivity and overall efficiency for both crops. QuickBird image-estimated LAI with MSAVI–LAI relationships agreed well with ground-measured LAI with the root-mean-square-error of 0.63 and 0.79 for corn and potato canopies, respectively. LAI estimated from the high spatial resolution pixel data exhibited spatial variability similar to the ground plot measurements. For field scale agricultural applications, MSAVI–LAI relationships are easy-to-apply and reasonably accurate for estimating LAI. KW - Leaf area index KW - QuickBird KW - Remote sensing KW - Sensitivity KW - Stability KW - Vegetation index ER - TY - JOUR ID - xie2007 AU - Xie, H. AU - Tian, Y. Q. AU - Granillo, J. A. AU - Keller, G. R. TI - Suitable remote sensing method and data for mapping and measuring active crop fields UR - ://WOS:000244093200023 DO - 10.1080/01431160600702673 T2 - International Journal of Remote Sensing PY - 2007 DA - Jan SN - 0143-1161 VL - 28 IS - 1-2 SP - 395-411 N1 - ISI Document Delivery No.: 134OR Times Cited: 9 Cited Reference Count: 22 Xie, H. Tian, Y. Q. Granillo, J. A. Keller, G. R. Taylor & francis ltd Abingdon AB - The objective of the study was to examine suitable remote sensing methods and data for mapping and measuring the acreages of active crop lands in order to improve irrigation management. We compared classification results from a supervised classification method and a method using normalized difference vegetation index (NDVI) with additional pre-classification processing. IKONOS and Landsat Enhanced Thematic Mapper Plus (ETM+) images were tested to see if high spatial resolution remote sensing data would have significant advantages in distinguishing between active and fallow lands. The classification achieved an overall accuracy of 93.63%. The results showed that the supervised classification did not have a clear advantage over the simple method using NDVI at the level of distinguishing between active crops and fallow lands. The result suggests that using ETM + instead of IKONOS high spatial resolution imageries is appropriate because of the high cost of IKONOS imageries and image heterogeneity of agricultural fields. It was shown that pre-processing with a mask to exclude the non-agricultural objects blended with agricultural fields is critical. KW - soil heat-flux KW - vegetation indexes KW - net-radiation KW - satellite KW - management KW - imagery ER - TY - JOUR ID - yang2004 AU - Yang, Chenghai AU - Everitt, James H. AU - Bradford, Joe M. TI - Airborne Hyperspectral Imagery and Yield Monitor Data for Mapping Cotton Yield Variability T2 - Precision Agriculture PY - 2004 VL - 5 SP - 445–461 AB - Increased availability of hyperspectral imagery necessitates the evaluation of its potential for precision agriculture applications. This study examined airborne hyperspectral imagery for mapping cotton (Gossypium hirsutum L.) yield variability as compared with yield monitor data. Hyperspectral images were acquired using an airborne imaging system from two cotton fields during the 2001 growing season, and yield data were collected from the fields using a cotton yield monitor. The raw hyperspectral images contained 128 bands between 457 and 922 nm. The raw images were geometrically corrected, georeferenced and resampled to 1 m resolution, and then converted to reflectance. Aggregation functions were then applied to each of the 128 bands to reduce the cell resolution to 4 m (close to the cotton picker’s cutting width) and 8 m. The yield data were also aggregated to the two grids. Correlation analysis showed that cotton yield was significantly related to the image data for all the bands except for a few bands in the transitional range from the red to the near-infrared region. Stepwise regression performed on the yield and hyperspectral data identified significant bands and band combinations for estimating yield variability for the two fields. Narrow band normalized difference vegetation indices derived from the significant bands provided better yield estimation than most of the individual bands. The stepwise regression models based on the significant narrow bands explained 61% and 69% of the variability in yield for the two fields, respectively. To demonstrate if narrow bands may be better for yield estimation than broad bands, the hyperspectral bands were aggregated into Landsat-7 ETM+ sensor’s bandwidths. The stepwise regression models based on the four broad bands explained only 42% and 58% of the yield variability for the two fields, respectively. These results indicate that hyperspectral imagery may be a useful data source for mapping crop yield variability. KW - cotton, hyperspectral imagery, remote sensing, yield monitor, yield mapping ER - TY - GEN ID - zarco-tejada_p_j_miller_j_r_1999 AU - Zarco-Tejada P.J. AU - Miller J.R. TI - Land Cover Mapping at BOREAS using red edge spectral parameters from CASI imagery T2 - J. Geophys. Res. Atmospheres. PY - 1999 VL - 104 ER - TY - JOUR ID - zarco-tejada_p_j_sepulcre-cant_2007 AU - Zarco-Tejada P.J. AU - Sepulcre-Cantó, G. TI - REMOTE SENSING OF VEGETATION BIOPHYSICAL PARAMETERS FOR DETECTING STRESS CONDITION AND LAND COVER CHANGES T2 - Estudios de la Zona No Saturada del Suelo PY - 2007 VL - 8 ER - TY - JOUR ID - zarco-tejada2001 AU - Zarco-Tejada, P. J. AU - Miller, J. R. AU - Noland, T. L. AU - Mohammed, G. H. AU - Sampson, P. H. TI - Scaling-up and model inversion methods with narrow-band optical indices for chlorophyll content estimation in closed forest canopies with hyperspectral data T2 - IEEE Transactions on Geoscience and Remote Sensing PY - 2001 VL - 39 SP - 1491−1507 ER - TY - JOUR ID - zarco-tejada2003 AU - Zarco-Tejada, P. J. AU - Rueda, C. A. AU - Ustin, S. L. TI - Water content estimation in vegetation with MODIS reflectance data and model inversion methods UR - http://www.sciencedirect.com/science/article/pii/S0034425702001979 DO - 10.1016/s0034-4257(02)00197-9 T2 - Remote Sensing of Environment PY - 2003 SN - 0034-4257 VL - 85 IS - 1 SP - 109-124 AB - Statistical and radiative-transfer physically based studies have previously demonstrated the relationship between leaf water content and leaf-level reflectance in the near-infrared spectral region. The successful scaling up of such methods to the canopy level requires modeling the effect of canopy structure and viewing geometry on reflectance bands and optical indices used for estimation of water content, such as normalized difference water index (NDWI), simple ratio water index (SRWI) and plant water index (PWI). This study conducts a radiative transfer simulation, linking leaf and canopy models, to study the effects of leaf structure, dry matter content, leaf area index (LAI), and the viewing geometry, on the estimation of leaf equivalent water thickness from canopy-level reflectance. The applicability of radiative transfer model inversion methods to MODIS is studied, investigating its spectral capability for water content estimation. A modeling study is conducted, simulating leaf and canopy MODIS-equivalent synthetic spectra with random input variables to test different inversion assumptions. A field sampling campaign to assess the investigated simulation methods was undertaken for analysis of leaf water content from leaf samples in 10 study sites of chaparral vegetation in California, USA, between March and September 2000. MODIS reflectance data were processed from the same period for equivalent water thickness estimation by model inversion linking the PROSPECT leaf model and SAILH canopy reflectance model. MODIS reflectance data, viewing geometry values, and LAI were used as inputs in the model inversion for estimation of leaf equivalent water thickness, dry matter, and leaf structure. Results showed good correlation between the time series of MODIS-estimated equivalent water thickness and ground measured leaf fuel moisture (LFM) content (r2=0.7), demonstrating that these inversion methods could potentially be used for global monitoring of leaf water content in vegetation. KW - Radiative transfer KW - Water content KW - Leaf fuel moisture KW - Equivalent water thickness KW - MODIS KW - Reflectance KW - Model inversion ER - TY - JOUR ID - zhang2006 AU - Zhang, X. AU - Yan, G. AU - Li, Q. AU - Li, Z. L. AU - Wan, H. AU - Guo, L. TI - Evaluating the fraction of vegetation cover based on NDVI spatial scale correction model UR - ://WOS:000244182300014 DO - 10.1080/01431160600658107 T2 - International Journal of Remote Sensing PY - 2006 DA - Dec SN - 0143-1161 VL - 27 IS - 23-24 SP - 5359-5372 N1 - Times Cited: 4 AB - Vegetation index (VI) is an important variable for retrieving the vegetation biophysical parameters. With different kinds of remote sensing data sets, it is easy to get the VI at different spatial and temporal resolutions. However, the main concern is whether the relationship existing at some scale between the VI and biophysical parameters is still applicable to other scales. This paper first presents a method to correct the spatial scaling effect of NDVI by mathernatic analysis, and then analyses NDVI scale sensitivity with data front a spectral database. The result shows that the NDVI obtained by reflectance up-scaling is larger than the Up-scaled NDVI from NDVI itself in most situations. The NDVI scaling effect is more significant when water exists in a pixel, and increases with the increase in the difference of the sum of visible reflectance and near-infrared (NIR) reflectance between the vegetation and soil. Finally, a method is proposed to estimate the fraction or vegetation cover (FVC) on the basis of the NDVI spatial scaling correction model. The method is accurate enough to assess the FVC taking into account the scaling effect. ER - TY - JOUR ID - zheng2009 AU - Zheng, Guang AU - Moskal, L. Monika TI - Retrieving Leaf Area Index (LAI) Using Remote Sensing: Theories, Methods and Sensors UR - http://www.mdpi.com/1424-8220/9/4/2719 T2 - Sensors PY - 2009 SN - 1424-8220 VL - 9 SP - 2719-2745 KW - LAI KW - Optical instruments KW - Radar ER - TY - ELEC ID - idb AU - Henrich, V. AU - Krauss, G. AU - Götze, C. AU - Sandow, C. TI - The IndexDatabase UR - https://www.indexdatabase.de/ CY - Bonn PY - 2011 DA - 2011 ER -