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.