A physically-based model for retrieving foliar biochemistry and leaf orientation using close-range imaging spectroscopy

REMOTE SENSING OF ENVIRONMENT

卷:177

Article

Jay, Sylvain¹  Bendoula, Ryad¹  Hadoux, Xavier^2,3  Feret, Jean-Baptiste⁴  Gorretta, Nathalie¹ 

[1] Irstea, UMR ITAP, 361 Rue JF Breton, F-34196 Montpellier, France

[2] Royal Victorian Eye & Ear Hosp, Ctr Eye Res Australia, Melbourne, Vic 3002, Australia

[3] Univ Melbourne, Dept Surg, Ophthalmol, Melbourne, Vic, Australia

[4] Irstea, UMR TETIS, Maison Teledetect, 500 Rue JF Breton, F-34093 Montpellier, France

关键词: Close-range;    COSINE;    Hyperspectral;    Imaging spectroscopy;    Leaf optical properties;    Pigment retrieval;    PROCOSINE;    PROSPECT;    Radiative transfer;    Vegetation;   

DOI  :  10.1016/j.rse.2016.02.029

来源: Elsevier

【 摘 要 】

Radiative transfer models have long been used to characterize the foliar content at the leaf and canopy levels. However, they still do not apply well to close-range imaging spectroscopy, especially because directional effects are usually not taken into account. For this purpose, we introduce a physical approach to describe and simulate the variation in leaf reflectance observed at this scale. Two parameters are thus introduced to represent (1) specular reflection at the leaf surface and (2) local leaf orientation. The model, called COSINE (ClOse-range Spectral ImagiNg of lEaves), can be coupled with a directional-hemispherical reflectance model of leaf optical properties to relate the measured reflectance to the foliar content. In this study, we show that, when combining COSINE with the PROSPECT model, the overall PROCOSINE model allows for a robust submillimeter retrieval of foliar content based on numerical inversion and pseudo-bidirectional reflectance factor hyperspectral measurements. The relevance of the added parameters is first shown through a sensitivity analysis performed in the visible and near-infrared (VNIR) and shortwave infrared (SWIR) ranges. PROCOSINE is then validated based on VNIR and SWIR hyperspectral images of various leaf species exhibiting different surface properties. Introducing these two parameters within the inversion allows us to obtain accurate maps of PROSPECT parameters, e.g., the chlorophyll content in the VNIR range, and the equivalent water thickness and leaf mass per area in the SWIR range. Through the estimation of light incident angle, the PROCOSINE inversion also provides information on leaf orientation, which is a critical parameter in vegetation remote sensing. (C) 2016 Elsevier Inc. All rights

【 授权许可】

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