Estimation of soybean yield from assimilated optical and radar data into a simplified agrometeorological model
The aim of this article is to evaluate the potential of optical and multi-polarization SAR images for soybean yield estimation by their assimilations into a simple agro-meteorological model. Satellite and ground data were acquired over two sites during the MCM'10 experiment. Optical and radar images were provided by Formosat-2, Spot-4, Spot-5 and Radarsat-2 satellites during the whole vegetation cycle of soybean. Results show that the assimilation of optical or SAR offer similar performances for the estimation of crop parameters (i.e. LAI and dry biomass) and crop yield (rRMSE = 18% in the worst case). Concerning SAR data, results highlighted the interest of using backscattering coefficients acquired at VV polarization (rRMSE = 2%).
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| Main Authors: | , , |
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| Format: | conference_item biblioteca |
| Language: | eng |
| Published: |
IEEE
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| Online Access: | http://agritrop.cirad.fr/595161/ http://agritrop.cirad.fr/595161/1/Baupetal_Igarss2015_.pdf |
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| Summary: | The aim of this article is to evaluate the potential of optical and multi-polarization SAR images for soybean yield estimation by their assimilations into a simple agro-meteorological model. Satellite and ground data were acquired over two sites during the MCM'10 experiment. Optical and radar images were provided by Formosat-2, Spot-4, Spot-5 and Radarsat-2 satellites during the whole vegetation cycle of soybean. Results show that the assimilation of optical or SAR offer similar performances for the estimation of crop parameters (i.e. LAI and dry biomass) and crop yield (rRMSE = 18% in the worst case). Concerning SAR data, results highlighted the interest of using backscattering coefficients acquired at VV polarization (rRMSE = 2%). |
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