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 - 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 - 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 - 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 - 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 -