[1] The radar backscattering coefficient is mainly determined by surface soil moisture, vegetation and land surface roughness under a given configuration of the satellite sensor. It is observed that the temporal variations of the three variables are different, the variation of vegetation and roughness are at the longer temporal scales corresponding to climate and cultivation practices, while so...

Surface soil moisture and the nature of the overlying vegetation both influence microwave emission from land surfaces significantly. One widely discussed but underused method for allowing for the effect of vegetation on soil-moisture retrievals from microwave observations is to use remotely sensed vegetation indices. This paper explores the potential for using the Normalised Difference Vegetati...

In this research, a back-propagation neural network was used to retrieve and map the surface soil moisture in Oklahoma (97d35'W, 36d15'N) from Synthetic Aperture Radar data acquired by RADARSAT-1 satellite. In addition to SAR backscattering, different vegetation-related information (vegetation optical depth and Normalized Difference Vegetation Index) have been added as additional inputs to the ...

[1] We present an unmixing method, based on genetic algorithm-soil-vegetationatmosphere-transfer modeling to extract subgrid information of soil and vegetation from remotely sensed soil moisture (downscaled; e.g., soil hydraulic properties, area fractions of soil-vegetation combinations, and unmixed soil moisture time series) that most land surface models use. The unmixing method was evaluated ...

This paper presents a microwave/optical synergistic methodology to retrieve soil moisture in an alpine prairie. The methodology adequately represents the scattering behavior of the vegetation-covered area by defining the scattering of the vegetation and the soil below. The Integral Equation Method (IEM) was employed to determine the backscattering of the underlying soil. The modified Water Clou...

Spatial distributed information of isochronal surface soil moisture is very important to compensate the inaccuracy of initial conditions and the uncertainty of parameters in hydrological models at the landscape scale. In this paper the conceptual procedure to derive spatial distributed surface soil moisture values from synthetic aperture radar data by using ancillary optical remote sensing data...

In arid ecosystems, variation in precipitation causes broad-scale spatial heterogeneity in soil moisture, but differences in soil texture, development, and plant cover can also create substantial local soil moisture heterogeneity. The boundary between inland desert sand dunes and adjacent desert habitats exhibits abrupt changes in soil and vegetation characteristics that may be associated with ...

The purpose of this study is to test the ability of the Land Surface Model SECHIBA to simulate water budget and particularly soil moisture at two different scales: regional and local. The model is forced by NLDAS data set at 1/8th degree resolution over the 1997–1999 period. SECHIBA gives satisfying results in terms of evapotranspiration and runoff over the US compared with four other land surf...

The Chinese HY-2, a satellite designed for ocean dynamic environment monitoring, was launched on August 16, 2011. The onboard scanning microwave radiometer (RM) is primarily designed for sea surface temperature and wind speed mapping. However, our objective of this investigation is to exploit the large amount of land observations of RM and to extend the mission scope to the retrieval of surface...

Within the frame of the project GeoBIRD (ESA contract 12950/98/NL/GD entitled "Retrieval of geoand bio-physical information from remote sensing data") an attempt was made to derive soil moisture by combining the microwave remote sensing model CLOUD and the land surface process model PROMET-V (PROcess oriented Modular Environment and Vegetation model. Three test sites in Europe, which show diffe...