Comparison of optical, radar, and hybrid soil moisture estimation models using experimental data

Different soil moisture estimation models have been developed based on using optical, radar, or a combination of optical and radar data. However, it is not clear which of these models is more suitable to estimate soil moisture in vegetated areas. Soil moisture is estimated in sparse vegetated areas using both optical and synthetic aperture radar (SAR) images. Also a hybrid model that is based on a combination of SAR and optical derived indices is used to decrease the effects of vegetation cover on SAR backscatter coefficients. The results show that the SAR model is more accurate than the optical model. However, after using the hybrid model and removing vegetation cover effects from radar backscattering coefficient, the accuracies improve. This shows that the hybrid model is the most accurate model and can be used as a suitable model to estimate soil moisture.

[1]  T. Carlson,et al.  Thermal remote sensing of surface soil water content with partial vegetation cover for incorporation into climate models , 1995 .

[2]  T. Carlson,et al.  A method to make use of thermal infrared temperature and NDVI measurements to infer surface soil water content and fractional vegetation cover , 1994 .

[3]  Jeffrey P. Walker,et al.  Active microwave remote sensing for soil moisture measurement: a field evaluation using ERS‐2 , 2004 .

[4]  S. Running,et al.  Developing Satellite-derived Estimates of Surface Moisture Status , 1993 .

[5]  Martha C. Anderson,et al.  Vegetation water content mapping using Landsat data derived normalized difference water index for corn and soybeans , 2004 .

[6]  Yong Fan,et al.  Empirically Adopted IEM for Retrieval of Soil Moisture From Radar Backscattering Coefficients , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[7]  F. Ulaby,et al.  Microwave Backscatter Dependence on Surface Roughness, Soil Moisture, and Soil Texture: Part I-Bare Soil , 1978, IEEE Transactions on Geoscience Electronics.

[8]  F. Ulaby,et al.  Vegetation modeled as a water cloud , 1978 .

[9]  Wolfram Mauser,et al.  Coupled modelling of land surface microwave interactions using ENVISAT ASAR data , 2004 .

[10]  R. Gillies.  A verification of the 'triangle' method for obtaining surface water content and energy fluxes from remote measurements of Normalized Difference Vegetation Index (NDVI) and surface radiant temperature , 1997 .

[11]  J. C. Price.  Using spatial context in satellite data to infer regional scale evapotranspiration , 1990 .

[12]  Jiancheng Shi,et al.  Snow mapping in alpine regions with synthetic aperture radar , 1994, IEEE Trans. Geosci. Remote. Sens..

[13]  Michael T. Manry,et al.  A robust statistical-based estimator for soil moisture retrieval from radar measurements , 1997, IEEE Trans. Geosci. Remote. Sens..

[14]  Yisok Oh,et al.  Quantitative retrieval of soil moisture content and surface roughness from multipolarized radar observations of bare soil surfaces , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[15]  Thomas J. Schmugge,et al.  Remote estimation of soil moisture availability and fractional vegetation cover for agricultural fields , 1990 .

[16]  Samuel N. Goward,et al.  Observed relation between thermal emission and reflected spectral radiance of a complex vegetated landscape , 1985 .

[17]  W. Kustas,et al.  A verification of the 'triangle' method for obtaining surface soil water content and energy fluxes from remote measurements of the Normalized Difference Vegetation Index (NDVI) and surface e , 1997 .

[18]  Niko E. C. Verhoest,et al.  Correlation between Ground Measured Soil Moisture and RADARSAT-1 derived Backscattering Coefficient over an Agricultural Catchment of Navarre (North of Spain) , 2005 .

[19]  B. Markham,et al.  Summary of Current Radiometric Calibration Coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI Sensors , 2009 .

[20]  D. Vidal-Madjar,et al.  Estimation of soil and crop parameters for wheat from airborne radar backscattering data in C and X bands , 1994 .

[21]  Mehdi Hosseini,et al.  Multi-index-based soil moisture estimation using MODIS images , 2011 .

[22]  Richard K. Moore,et al.  Radar remote sensing and surface scattering and emission theory , 1986 .

[23]  Thomas J. Jackson,et al.  Mapping surface roughness and soil moisture using multi-angle radar imagery without ancillary data , 2008 .