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Estimation of soybean yield from assimilated optical and radar data into a simplified agrometeorological model

机译:根据同化光学和雷达数据估算大豆产量,并简化为农业气象模型

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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%).
机译:本文的目的是通过将它们同化成一个简单的农业气象模型,来评估光学和多极化SAR图像在估计大豆产量中的潜力。在MCM'10实验期间,在两个站点上采集了卫星和地面数据。在整个大豆种植周期中,Formosat-2,Spot-4,Spot-5和Radarsat-2卫星提供了光学和雷达图像。结果表明,光学或SAR的同化为估计作物参数(即LAI和干生物量)和作物产量(最坏情况下rRMSE = 18%)提供了相似的性能。关于SAR数据,结果突出显示了使用在VV极化(rRMSE = 2%)时获得的反向散射系数的兴趣。

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