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 - 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 - 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 -