PROSPECT-4 and 5: Advances in the leaf optical properties model separating photosynthetic pigments
- 作者：Jean-Baptiste Feret ; Christophe Franç ; ois ; Gregory P. Asner ; Anatoly A. Gitelson ; Roberta E. Martin ; Luc P.R. Bidel ; Susan L. Ustin ; Guerric le Maire ; Sté ; phane Jacquemoud
- 关键词：Leaf optical properties ; Radiative transfer model ; PROSPECT ; Hyperspectral data ; Pigments
- 刊名：Remote Sensing of Environment
- 出版年：2008
- 期刊代码：79_00344257
- 类别：ear
- 出版时间：16 June 2008
- 卷：112
- 期：6
- 页码：3030-3043
- 文件大小：1956 K
摘要
The PROSPECT leaf optical model has, to date, combined the effects of photosynthetic pigments, but a finer discrimination among the key pigments is important for physiological and ecological applications of remote sensing. Here we present a new calibration and validation of PROSPECT that separates plant pigment contributions to the visible spectrum using several comprehensive datasets containing hundreds of leaves collected in a wide range of ecosystem types. These data include leaf biochemical (chlorophyll a, chlorophyll b, carotenoids, water, and dry matter) and optical properties (directional–hemispherical reflectance and transmittance measured from 400 nm to 2450 nm). We first provide distinct in vivo specific absorption coefficients for each biochemical constituent and determine an average refractive index of the leaf interior. Then we invert the model on independent datasets to check the prediction of the biochemical content of intact leaves. The main result of this study is that the new chlorophyll and carotenoid specific absorption coefficients agree well with available in vitro absorption spectra, and that the new refractive index displays interesting spectral features in the visible, in accordance with physical principles. Moreover, we improve the chlorophyll estimation (RMSE = 9 µg/cm2) and obtain very encouraging results with carotenoids (RMSE = 3 µg/cm2). Reconstruction of reflectance and transmittance in the 400–2450 nm wavelength domain using PROSPECT is also excellent, with small errors and low to negligible biases. Improvements are particularly noticeable for leaves with low pigment content.