遥感信息与作物生长模型结合研究进展

遥感能周期性地获取大范围的地表作物信息,通过适当的反演方法能够定量地提供作物在区域尺度上的生长状况;而作物生长模型可以在单点尺度上模拟出作物生长发育的动态变化,对作物长势以及产量变化的做出机理性解释。将遥感信息与作物生长模型结合能实现二者优势互补,已成为目前作物长势监测和估产研究中的重要方法。本文总结了遥感信息和作物生长模型结合的两种主要方法,即驱动法和同化法,介绍了两种方法的常用算法、优缺点及国内外的应用情况,同时总结了将二者结合的研究趋势以及目前研究中存在的一些问题,旨在为后续遥感信息与作物生长模型结合的研究提供一定理论参考。

Review on the combination of remote sensing information and crop growth model

Remote sensing can obtain crop information in large area periodically and provide quantitative information of crop growth with appropriate inversion method. Crop growth models can realize the dynamic simulation of crop growth and development on a single point scale and can provide internal mechanism explanation for crop growth and yield changes. The combination of remote sensing information and crop growth model can give full play to the advantages of both and has been a critical measure of crop growth monitoring and yield estimating. The two main methods of combining remote sensing information with crop growth model were summarized. They are driving method and assimilation method. The definition, common algorithms, advantages and disadvantages of different methods, as well as the application situation in Domestic and Overseas were introduced. At the same time, the research trends of this combination and some problems existing in the current research were also summarized. This paper aims to provide a theoretical reference for the following research on the combination of remote sensing information and crop growth model.