遥感信息与棉花模型结合反演模型初始值和参数的方法研究

通过将遥感信息(叶面积指数LAI)与棉花模型结合,建立了遥感-棉花反演模型,用以反演棉花模型所需的初始数据和参数,解决模式在从单点扩展到区域应用时缺少初始输入的问题。反演的参数为播种期、种植密度、生育期施氮量和灌溉量。通过对反演模型检验,初步确定反演模型是正确的。另外,在区域上初步应用的结果表明,反演的参数和模拟的产量与实际情况吻合较好。

Study on Combinations of Remote Sensing and Cotton Model to Retrieve Initial Inputs and Parameters

A remote sensing and cotton inversion model has been established on the basis of assimilation theory,assimilating LAI,and taking three optimization methods(SCE,SA,DE),to combine of remote sensing and COSIM cotton model which is relatively developed well.The inversion model can retrieve initial inputs and parameters needed by cotton model.Therefore,the study can resolve the problems of lack of initial inputs when crop model is applied from spot to region.Inversed parameters are sowing date,planting population,amount of nitrogen and irrigation.Simulation test showed that the inversion model established in this paper was correct at great extent.In addition,we have tried to use the established remote sensing-COSIM cotton inversion model with SCE scheme to inverse parameters and predict cotton yield in 11 counties in north part of Xinjiang province.Generally speaking,the results from inversion model including yields and sowing dates,sowing density,nitrogen application amount,and irrigation amount in the application areas are largely consistent with the estimation of real situation.Quantitative comparison by observed and inversed values at two points shows that application results of remote sensing-COSIM cotton inversion model on the regional scale are better.Yield estimated errors of the two points are-5.8% and-5.1%,respectively,which are lower for large area yield prediction.If COSIM model can improve its simulation veracity,all kinds of errors of results will be much lower.