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Relation between ERS‐1 synthetic aperture radar data and measurements of surface roughness and moisture content of rocky soils in a semiarid rangeland
Author(s) -
Sano Edson E.,
Huete Alfredo R.,
Troufleau Denis,
Moran M. Susan,
Vidal Alain
Publication year - 1998
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/98wr00032
Subject(s) - water content , environmental science , synthetic aperture radar , soil water , soil science , surface roughness , remote sensing , infiltration (hvac) , surface runoff , vegetation (pathology) , hydrology (agriculture) , evapotranspiration , geology , meteorology , geography , medicine , ecology , physics , geotechnical engineering , pathology , quantum mechanics , biology
Surface roughness and soil moisture content control the distribution of rainfall into runoff, evapotranspiration, and infiltration. Satellite radar data have the potential to provide spatial and multitemporal estimates of these variables, depending upon the sensor configuration and field condition. The relation between the European Remote Sensing Satellite (ERS‐1) synthetic aperture radar (SAR) data and measurements of surface roughness and moisture content of rocky soils in a semiarid rangeland in southeast Arizona was analyzed in this study. A dry and a wet season C band SAR image were acquired and corrected for topographic effects. Field soil roughness and moisture content data were obtained from 47 sampling sites. An intensive soil moisture sampling campaign was also conducted at three sites to determine the number of samples necessary to estimate soil moisture content with 10% accuracy. Dry and wet season SAR data were found to be correlated ( r 2 =0.80 and 0.59, respectively) with root‐mean‐square (RMS) height measurements, while SAR data from the wet season image were poorly correlated with soil moisture. The results indicated that C band SAR data are promising for estimation of surface roughness in semiarid rangelands. However, they are less promising for soil moisture estimation, unless the effects of soil roughness and vegetation are removed. The acquisition of an adequate number of soil moisture samples to obtain representative soil moisture measurements is also a key issue in the validation of soil moisture retrieval from SAR data. In the study area, at least 17 samples per hectare were needed to obtain soil moisture estimates with 10% accuracy.