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 - galv_o2005 AU - Galvão, Lênio Soares AU - Formaggio, Antônio Roberto AU - Tisot, Daniela Arnold TI - Discrimination of sugarcane varieties in Southeastern Brazil with EO-1 Hyperion data UR - http://www.sciencedirect.com/science/article/pii/S0034425704003669 DO - 10.1016/j.rse.2004.11.012 T2 - Remote Sensing of Environment PY - 2005 SN - 0034-4257 VL - 94 IS - 4 SP - 523-534 AB - Hyperspectral data acquired by the Hyperion instrument, on board the Earth Observing-1 (EO-1) satellite, were evaluated for the discrimination of five important Brazilian sugarcane varieties (RB72-454, SP80-1816, SP80-1842, SP81-3250, and SP87-365). The radiance values were converted into surface reflectance images by a MODTRAN4-based technique. To discriminate varieties with similar reflectance values, multiple discriminant analysis (MDA) was applied over the data. To obtain an adequate discriminant function, a stepwise method was used to select the best variables among surface reflectance values, ratios of reflectance, and several spectral indices potentially sensitive to changes in chlorophyll content, leaf water, and lignin-cellulose. Results showed that the five Brazilian sugarcane varieties were discriminated using EO-1 Hyperion data. Differences in canopy architecture affected sunlight penetration and reflectance, resulting in a higher reflectance for planophile (e.g., SP81-3250) than erectophile (e.g., SP80-1842) sugarcane plants. The variety SP80-1842 presented lower reflectance values, deeper lignin-cellulose absorption bands at 2103 nm and 2304 nm, shallower leaf liquid water absorption bands at 983 nm and 1205 nm, and lower leaf liquid water content than the other sugarcane varieties. To discriminate this cultivar, a single near-infrared (NIR) band threshold was used. To discriminate the other four sugarcane varieties with similar reflectance values, MDA was used producing a classification accuracy of 87.5% for a hold-out set of pixels. The comparison between the ground truth data and the MDA-derived classification image confirmed the model' capacity to differentiate the varieties accurately. The best results were obtained for the cultivar SP87-365 that presented the lowest spectral variability in the discriminant space. Some misclassified areas were associated with the cultivars SP80-1816 and SP81-3250 that showed the highest spectral variability. KW - Hyperspectral remote sensing KW - Sugarcane varieties KW - Hyperion KW - Discriminant analysis KW - Agriculture KW - Crops ER - TY - JOUR ID - kooistra2003 AU - Kooistra, L. AU - Leuven, R. S. E. W. AU - Wehrens, R. AU - Nienhuis, P. H. AU - Buydens, L. M. C. TI - A comparison of methods to relate grass reflectance to soil metal contamination UR - http://dx.doi.org/10.1080/0143116031000080769 DO - 10.1080/0143116031000080769 T2 - International Journal of Remote Sensing PY - 2003 DA - 2003/01/01 SN - 0143-1161 VL - 24 IS - 24 SP - 4995-5010 AB - Grass-dominated vegetation covers large areas of the Dutch river floodplains. Remotely sensed data on the conditions under which this vegetation grows may yield information about the degree of soil contamination. This paper explores the relationship between grassland canopy reflectance and zinc (Zn) contamination in the soil under semi-field conditions. A field radiometer was used to record reflectance spectra of perennial ryegrass (Lolium perenne) in an experimental field with Zn concentrations in the soil ranging from 32 to 1800mgkg?1. Several spectral vegetation indices (VIs) and a multivariate approach using partial least squares (PLS) regression were investigated to evaluate their potential use in estimating Zn contamination levels. Compared to the best PLS model (RMSEP = 181.4 mg kg?1), the narrow band vegetation index MSAVI2mm performed better (RMSEP = 162.9 mg kg?1). Both MSAVI2mm and PLS gave a high user accuracy for the strongly contaminated soil class (100% and 91%, respectively), while the total accuracy was satisfactory (60% and 55%, respectively). Results from this feasibility study indicate the potential of using remote sensing techniques for the classification of contaminated areas in river floodplains. But as the results from this study may be both resolution- and location-dependent, research on field and image scale is now required to test the established relations and to assess their susceptibility to seasonal influences, species heterogeneity, and increased levels of spectral noise. 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 -