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地表土壤水分含量的时空分布信息是十分重要的,常常作为水文模型、气候模型、生态模型的输入参数,同时,也是干旱预报、农作物估产等工作的重要指标。被动微波遥感是监测土壤含水量最有效的手段之一。相比红外与可见光,它具有波长长,穿透能力强的优势。相比主动微波雷达,被动微波辐射计具有监测面积大、周期短,受粗糙度影响小,对土壤水分更为敏感,算法更为成熟的优势。目前,已研究出许多反演土壤水分的方法,本课题的主要内容是借助AMSR-E土壤水分影像数据、MODIS归一化植被指数(NDVI)影像数据和MODIS分类影像数据,利用ENVI软件进行遥感图像数据处理,运用统计分析方法建立NDVI与土壤水分的经验模型,研究中国西部地区稀疏植被覆盖区土壤水分的反演。
Spatial and temporal distribution of surface soil moisture content information is very important, and often as a hydrological model, climate model, ecological model input parameters, but also an important indicator of drought forecast, crop assessment and so on. Passive microwave remote sensing is one of the most effective means of monitoring soil moisture content. Compared with infrared and visible light, it has the advantages of long wavelength, penetrating ability. Compared with the active microwave radar, passive microwave radiometer has the advantages of large monitoring area, short period, small influence of roughness, more sensitive to soil moisture and more mature algorithm. At present, many methods for inverting soil moisture have been developed. The main contents of this project are based on AMSR-E soil moisture image data, MODIS normalized vegetation index (NDVI) image data and MODIS classification image data, remote sensing using ENVI software Image data processing, the establishment of empirical models of NDVI and soil moisture using statistical analysis methods to study the inversion of soil moisture in sparse vegetation coverage areas in western China.