植被覆盖地表土壤水分遥感反演

Retrieval methods of soil water content in vegetation covering areas based on multi-source remote sensing data

以地域特色突出的新疆渭干河-库车河三角洲绿洲为研究区,联合使用雷达数据和光学遥感数据,对干旱区绿洲土壤和植被水分信息进行提取。在同期光学遥感影像数据提取植被归一化差分水分指数基础上,利用"水-云模型"从雷达数据总的后向散射中去除植被影响,建立土壤后向散射系数与土壤含水量的关系,相关系数为HH极化R2=0.5227,HV极化R2=0.3277。结果表明利用C波段HH极化雷达影像数据结合光学影像数据,进行干旱半干旱地区棉花、玉米等农作物种植区地表土壤水分反演时,在中等覆盖条件下去除植被影响有较好的效果。

This paper takes the delta oasis of Weigan and Kuqa rivers in Xinjiang as the study area. Fusion image of SAR （Radar-sat image） combined with visible spectrum remote sensing image （TM image） is used to extract soil and vegetation water content in arid oasis. Based on the Normalized Difference Moisture Index extracted from homochronous visible spectrum remote sensing data, this thesis utilizes ＂water-cloud model＂ to wipe off vegetation influence from total backscattering coefficient of radar data and sets up the relationship between soil backscattering coefficient and soil moisture. Correlation coefficient for HH Polarization is R2 =0.5227, for HV Polarization is R2 =0.3277. Result shows that in arid and semi-arid area where the main crops are cotton and corn, the combination of C-band HH polarization radar data with visible image performs well in the study of removing vegetation influence while retrieving soil water content in medium vegetated areas.