Digital twin forestry as an informatics framework integrating remote sensing ecosystem modelling and data assimilation
系统综述数字孪生林业，提出遥感与生态模型同化耦合框架。
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#数据同化
Assessment of bias correction techniques for satellite soil moisture data assimilation in the dry season of Southeastern South America
评估南美干旱季卫星土壤湿度同化中的偏差校正方法，提出基于均质土壤纹理和滑动窗口的改进CDF匹配。
Improving regional winter wheat yield estimation by assimilating cross-scale heterogeneity information from UAV and satellite remote sensing
构建跨尺度数据同化框架，融合无人机与卫星遥感提升区域冬小麦产量估算精度。
Multi-source data assimilation of Sentinel-2 reflectance and SMAP soil moisture into APSIM for maize biomass estimation
将Sentinel-2反射率与SMAP土壤水分同化进APSIM模型，提升玉米生物量估算精度。
Integrating Satellite Data into Near-Term, Iterative Water Temperature Forecasting Workflows Improves the Scalability of Freshwater Forecasts
将卫星数据同化进FLARE模型，提升无传感器湖泊水温预报的可扩展性。
Improving Maize Yield Estimation Accuracy by Integrating Satellite Remote Sensing Data and the WOFOST Model Through Data Assimilation
通过数据同化整合卫星遥感与WOFOST模型，提高夏玉米产量估算精度。