微波遥感测量土壤水分的方法主要分主动和被动两种，它们都是基于干燥土壤和水体之间介电常数的巨大差异。估算植被覆盖土壤表面土壤水分必须要考虑地表粗糙度和植被覆盖影响的问题。植被覆盖土壤表面的后向散射包括来自植被的体散射，来自地表的面散射和植被与地表间的交互作用散射项。本研究建立了一个半经验公式模型，用来计算体散射项，综合时间序列的主动和被动微波数据，消除植被覆盖的影响，估算地表土壤水分的变化状况。并应用1997年美国SGP‘97综合实验中的机载800m分辨辐射计ESTAR数据计算表面反射系数，综合Radarsat的SCAN-SAR数据得到体散射项，然后，由NOAA/AVHRR和TM计算得到的NDVI值加权分配50m分辨率的体散射项，最后计算50m分辨率的表面反射系数的变化值，从而得到土壤水分的变化情况，验证数据表明该计算结果与实测值一致。

Soil moisture is a highly variable component in land surface hydrology and plays a critical role in agriculture and hydrometeorology. It also plays an important role in the interactions between the land surface and the atmosphere, as well as the partitioning of precipitation into runoff and ground water storage. Two basic microwave approaches are used to measure soil moisture, one is passive which is based on radiometry and the other is active and uses radar. Both approaches utilize the large contrast between the dielectric constant of dry soil and water. Two systems are complementary. The passive microwave systems include frequent coverage, low data rates, and simpler data processing, but with poor resolution . In the case of the active microwave systems, the advantages include high resolution, but this comes at the expence of higher data rates and more complex processing. In this study, we showed the estimation of soil moisture with vegetation cover integrated passive and active microwave data.A total backscattering amoumt for a vegetated surface include volume, surface, and surface-volume interaction scattering terms. The direct volume scattering is considered to be controlled mainly by vegetation; surface scattering term is controlled by soil dielectric component and roughness. The backscattering model here is based on without surface-volume interaction scattering terms. Im attempt to use active microwave remote sensors in estimation of soil moisture, we are mainly facing two major problems: effects of surface roughness and vegetation cover. For a given sensor, we assume the roughness under the condition of no change during data acquisitions. The main problem for retrieval surface dielectric properties is separate the volume scattering item from total backscattering.With the time-serial soil moisture map from L band passive microwave radiomerty, the Electronically Scanned Thinned Array Radiometer (ESTAR)at Southern Great Plains 1997(SGP'97), we calculated the surface reflectivity with 800m resolution. The volume scattering items at 800m resolution can be derived using multi-temporal resample calibration Radarsat SAR and surface reflectivity data. Weighting the ratio of NDVI at different resolution from NOAA/ANHRR and TM, the surface reflectivity wity 50m resolution can be estimated according to the total backscattering and volume scattering , then soil moisture be mapped at 50m resolution. The deriving results showed the same trend of soul moisture change comparing with the field measurement.