遥感数据和作物模型集成方法与应用前景

    Methods for integration of remote sensing data and crop model and their prospects in agricultural application

    • 摘要: 为了促进遥感数据和作物模型集成这一新方法在农业领域中更广泛的应用,在分析遥感数据和作物模型农业应用中各自优缺点的基础上,阐明二者结合的必要性,并介绍了遥感数据和作物模型的3种集成方式。回顾了遥感数据和作物模型同化的研究进展,并重点分析了遥感数据和作物模型结合在农作物产量预测、品质遥感预报、精准施肥管理决策、精准灌溉决策等领域的应用潜力,最后指出了当前遥感数据和作物模型结合中存在遥感定量化、参数集和驱动数据的获取、最优化算法选择和改进、作物模型的完善和订正等问题,有望随着遥感数据源的丰富、定量遥感和作物模型的发展、以及同化理论的进一步完善得到解决。

       

      Abstract: In order to widen application of the new method for integration of remote sensing data and crop model in agriculture, in this paper the advantages and limits of the application of remote sensing and crop simulation model in agriculture were analyzed, and it is necessary to integrate both of them in application, firstly. Then three methods of integration remote sensing and crop model were introduced and research progress of assimilation of remote sensing data and crop model was reviewed. The prospects of assimilation approaches were analyzed for its application in crop yield forecasting, crop quality prediction, precision fertilization and irrigation management decision-making. At last, some questions for integration of remote sensing and crop model were presented, such as remote sensing quantification, parameter and forcing data set acquiring, optimization algorithms selection and improvement, crop model perfection and correction. These questions may be resolved with more sources of remote sensing data, and with the development of Quantitative Remote Sensing, crop model and assimilation theory.

       

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