基于改进水云模型的土壤水分反演研究

Study on Soil Moisture Inversion Based on Advanced Water Cloud Model

提出了一种基于改进的水云模型的主动微波遥感土壤水分反演方法。首先,分别通过甘肃省张掖市祁连山中段的扁都口研究区的实测数据计算RVI、DVI、NDVI、NDWI、MSAVI等五种植被指数,建立适用于研究区的植被含水量经验方程,然后基于植被含水量经验方程构建水云模型,对总的地表后向散射系数中的植被影响进行改正,结合水云模型和AIEM模型,建立改进的土壤水分反演算法。从五种植被指数中选取与植被含水量相关性最高的三种植被指数,然后利用九组植被指数组合参与土壤水分反演,对比并选择反演结果精度较好的植被指数及其植被含水量经验方程。将文章方法与基于Jackson经验方程建立水云模型的反演算法进行了对比,结果表明,文章提出的改进水云模型的土壤水分反演算法精度较高,体现了该改进算法的优势与潜力。

An active microwave remote sensing soil moisture retrieval method based on improved water cloud model is proposed.First of all,based on the measured data of Biandukou study area in the middle part of Qilian Mountain in Zhangye City,Gansu Province,RVI,DVI,NDVI,NDWI and MSAVI are calculated,and the empirical equation of vegetation water content suitable for the study area is established.Then based on the empirical equation of vegetation water content,the water cloud model is constructed to correct the vegetation influence in the total surface backscattering coefficient.By combining water cloud model and AIEM model,an improved inversion algorithm of soil moisture is established.Three vegetation indices with the highest correlation with vegetation water content were selected from the five vegetation indexes,and then nine groups of vegetation indexes were used to participate in the inversion of soil moisture.And the vegetation index with better accuracy of inversion results and the empirical equation of vegetation water content are compared and selected.The method proposed in this paper is compared with the inversion algorithm of water cloud model based on Jackson empirical equation.The results show that the soil moisture inversion algorithm of the improved water cloud model proposed in this paper has higher accuracy,which reflects the advantage and potential of the improved algorithm.