College of Land Science and Technology China Agricultural University Beijing China;
College of Land Science and Technology Key Laboratory of Agricultural Information Acquisiton Technology China Agricultural University Beijing China;
Agriculture; Optical imaging; Optical sensors; Soil moisture; Remote sensing; Synthetic aperture radar; Yield estimation;
机译:通过将三种远程感测的反射数据集吸收到耦合WOFOST - 扶梯模型中,评估冬小麦产量的区域估计
机译:将Sentinel-1和Sentinel-2数据中获取的土壤水分吸收到WOFOST模型中,以改善冬小麦的产量估算
机译:通过将单个Landsat遥感LAI纳入WOFOST模型,在田间尺度上改善枣果树的产量估算
机译:将SAR和光学遥感数据同化到WOFOST模型,提高冬小麦产量估计
机译:使用精准农业和遥感技术优化软红冬小麦的氮素管理,谷物蛋白和谷物品质。
机译:从Sentinel-1和Sentinel-2数据将叶面积指数和土壤水分联合吸收到WOFOST模型中进行冬小麦产量估算
机译:从哨兵-1和Sentinel-2数据中检索的土壤水分进入Wofost模型,以提高冬小麦产量估计