机译:利用粒子滤波算法估算小麦面积的CERES-小麦模型对叶面积指数和表层土壤水分的吸收
Institute of Remote Sensing and Geographic Information System, College of Information and Electrical Engineering, China Agricultural University, Beijing, China;
Institute of Remote Sensing and Geographic Information System, College of Information and Electrical Engineering, China Agricultural University, Beijing, China;
Institute of Remote Sensing and Geographic Information System, College of Information and Electrical Engineering, China Agricultural University, Beijing, China;
Remote Sensing Information Center for Agriculture of Shaanxi Province, Xi'an, China;
Institute of Remote Sensing and Geographic Information System, College of Information and Electrical Engineering, China Agricultural University, Beijing, China;
Yield estimation; Remote sensing; Soil moisture; Irrigation; Correlation; Earth;
机译:集成卡尔曼滤波将时空叶面积指数同化到CERES-Wheat模型中,并进行不确定性评估,以改善冬小麦产量
机译:通过CERES-Wheat模型改进冬小麦产量估算,以不同的吸收方法和时空尺度吸收叶面积指数
机译:利用土地特征及CERES - 小麦模型同化冬小麦产量估计叶面积指数及植被温度条件指标
机译:利用改进的粒子滤波同化算法估算土壤湿度
机译:高分辨率的土壤水分变化估计及其同化为地表模型。
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:利用不同同化方法和时空尺度从CEREs小麦模型提高冬小麦产量估算同化叶面积指数
机译:小麦产量估算中叶面积指数和土壤水分的同化遥感观测:观测系统模拟实验。