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Estimation of sunflower yield using multi-spectral satellite data (optical or radar) in a simplified agro-meteorological model

机译:在简化的农业气象模型中使用多光谱卫星数据(光学或雷达)估算向日葵产量

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This paper aims to compare the crop yield retrieval performances, obtained by assimilating the leaf area index derived from multi-temporal satellite signatures (i.e. reflectances and backscattering coefficients) into an agro-meteorological model. The study is based on the Multispectral Crop Monitoring experimental campaign, conducted in 2010 by the CESBIO laboratory. During the agricultural season of sunflower, regular satellite images were quasi-synchronously acquired by 6 sensors (Formosat-2, Spot-4/5, TerraSAR-X, Radarsat-2 and Alos), over a region located in the south west of France. Calibration and validation steps take advantage of the dense network of monitored fields. Among the wide range of the tested image configurations (multi-frequency and multi-polarization), promising results are offered by optical and co-polarized C-band (i.e. HH and VV) data for yield estimate, with correlation superior to 0.74.
机译:本文旨在比较通过将多时相卫星特征(即反射率和反向散射系数)得出的叶面积指数吸收到农业气象模型中而获得的农作物收成性能。该研究基于CESBIO实验室于2010年开展的多光谱作物监测实验活动。在向日葵的农业季节期间,在法国西南部的某个地区,通过6个传感器(Formosat-2,Spot-4 / 5,TerraSAR-X,Radarsat-2和Alos)准同步采集了常规卫星图像。 。校准和验证步骤利用了密集的受监视字段网络。在广泛的测试图像配置(多频和多极化)中,光学和共极化C波段(即HH和VV)数据可提供令人鼓舞的结果,以进行产量估算,相关性优于0.74。

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