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Communication dans un congrès

Synergy of remote sensing and process-based model for dynamic assessment of CO2 flux and biomass in agro-ecosystems

Abstract : Since both remote sensing and modeling methods have inherent limitations in estimating ecosystem dynamics, this study investigated the potential of synergy of remote sensing and process-based modeling. A comprehensive data set was constructed, which included ground-based and airborne remote sensing data in optical and thermal wavelength domains as well as CO2 flux by eddy covariance method, and plant and micrometeorological data over 8 years. Result showed that an approach to tune a soil-vegetation-atmospheric transfer model (SVAT model) using remotely-sensed data could allow accurate and dynamic assessment of important ecosystem variables such as biomass, CO2 flux, and soil moisture content.
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Communication dans un congrès
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https://hal.inrae.fr/hal-02761539
Déposant : Migration Prodinra <>
Soumis le : jeudi 4 juin 2020 - 05:47:24
Dernière modification le : lundi 31 août 2020 - 10:35:24

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  • HAL Id : hal-02761539, version 1
  • PRODINRA : 32109

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Yoshio Inoue, Albert Olioso. Synergy of remote sensing and process-based model for dynamic assessment of CO2 flux and biomass in agro-ecosystems. 39. Conference of the Remote Sensing Society of Japan, 2005, Japan. ⟨hal-02761539⟩

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