Coupling canopy functioning and radiative transfer models for remote sensing data assimilation
| Autor: | Laurent Prévot, D. Troufleau, Nadine Bruguier, Nadine Brisson, Frédéric Baret, Habiba Chauki, Marie Weiss, Albert Olioso |
|---|---|
| Přispěvatelé: | Station de bioclimatologie, Institut National de la Recherche Agronomique (INRA), Unité de bioclimatologie |
| Jazyk: | angličtina |
| Rok vydání: | 2001 |
| Předmět: |
Canopy
Atmospheric Science 010504 meteorology & atmospheric sciences COUVERTURE VEGETALE 01 natural sciences Data assimilation Atmospheric radiative transfer codes [SDV.SA.SF]Life Sciences [q-bio]/Agricultural sciences/Silviculture forestry Radiative transfer Leaf area index [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environment Water content 0105 earth and related environmental sciences Remote sensing 2. Zero hunger Global and Planetary Change Forestry 04 agricultural and veterinary sciences 15. Life on land 040103 agronomy & agriculture 0401 agriculture forestry and fisheries Environmental science Plant cover Crop simulation model INDICE FOLIAIRE Agronomy and Crop Science |
| Zdroj: | Agricultural and Forest Meteorology Agricultural and Forest Meteorology, 2001, 108 (2), pp.113-128. ⟨10.1016/S0168-1923(01)00234-9⟩ Agricultural and Forest Meteorology, Elsevier Masson, 2001, pp.113-128 |
| ISSN: | 0168-1923 |
| DOI: | 10.1016/S0168-1923(01)00234-9⟩ |
| Popis: | Crop functioning models (CFM) are used in many agricultural and environmental applications. Remote sensing data assimilation appears as a good tool to provide more information about canopy state variables in time and space. It permits a reduction in the uncertainties in crop functioning model predictions. This study presents the first step of the assimilation of optical remote sensing data into a crop functioning model. It consists in defining a coupling strategy between well known and validated crop functioning and radiative transfer models (RTM), applied to wheat crops. The radiative transfer model is first adapted to consistently describe wheat, considering of four layers in the canopy that contain different vegetation organs (soil, yellow leaves and senescent stems, green leaves and stems, green and senescent ears). The coupling is then performed through several state variables: leaf area index, leaf chlorophyll content, organ dry matter and relative water content. The relationships between the CFM outputs (agronomic variables) and RTM inputs (biophysical variables) are defined using experimental data sets corresponding to wheat crops under different climatic and stress conditions. The coupling scheme is then tested on the data set provided by the Alpilles–ReSeDA campaign. Results show a good fitting between the simulated reflectance data at top of canopy and the measured ones provided by SPOT images corrected from atmospheric and geometric effects, with a root mean square error lower than 0.05 for all the wavebands. |
| Databáze: | OpenAIRE |
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