遥感与作物生长模型数据同化在水稻上的应用进展

Review on Data Assimilation of Remote Sensing and Crop Growth Models in Rice

遥感和作物生长模型在农业资源监测、作物产量预测等方面发挥着重要作用。遥感监测是获取大面积地表信息的最有效手段,作物生长模型则是在机理层面上对作物产量进行建模,可以实现单点尺度作物生长发育的动态模拟。但两者各有优缺点,而遥感信息和作物生长模型的数据同化可以有效结合两者的优势,实现大尺度、高精准的农业监测与预报。运用文献分析法从作物生长模型、卫星遥感、数据同化研究进展、遥感与作物模型数据同化在水稻上的研究进展,以及遥感与作物生长模型数据同化研究趋势等方面进行了概述。为今后开展水稻遥感与作物生长模型同化研究提供思路,为农作物长势监测和产量预测提供技术支持。

Remote sensing and crop growth models play an irreplaceable role in agricultural resource monitoring and crop yield prediction.Remote sensing monitoring is the most effective method to obtain large-area surface information.The crop growth models model crop yield at the mechanism level,which could realize dynamic simulation of crop growth at a single point scale.But the two have their own advantages and disadvantages,and the assimilation of remote sensing information and crop growth models could effectively combine their respective advantages to achieve large-scale and high-precision agricultural monitoring and forecasting.This article summarized the research progress of crop growth models,satellite remote sensing,data assimilation,remote sensing and crop model data assimilation on rice,and research trends of remote sensing and crop growth model data assimilation.To provide ideas for the future research on rice remote sensing and crop growth model assimilation,and to provide technical support for crop growth monitoring and yield budget.