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United States Department of Agriculture

Agricultural Research Service


item Sano, E.
item Huete, A.
item Moran, Mary - Susan

Submitted to: Revista Brasileira De Ciencia Do Solo
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/23/1999
Publication Date: N/A
Citation: Sano, E.E., Huete, A.R., Moran, M.S. 1999. Estimation of surface roughness in a semiarid region from C-band ERS-1 synthetic aperture radar data. Revista Brasileira de Ciencia do Solo 23:903-908.

Interpretive Summary: Resource managers are often interested in the storage and loss of water over large areas of land. Information on soil roughness is important to these managers because it controls water infiltration, the distribution of rainfall runoff and the evaporation of water from the surface. For example, rougher soils slow the water runoff and trap water to improve water infiltration. Measurement of soil roughness by conventional methods is expensive and labor intensive. In this study, a new method for measurement of soil roughness over large areas is proposed. Images obtained with radar sensors on satellites were easy to obtain and found to be very sensitive to soil roughness. Accurate maps of soil roughness were derived from these images over a large area in southeastern Arizona. This approach could be used to improve the information available to resource managers for making decisions about scarce water supplies.

Technical Abstract: In this study, we investigated the feasibility of using the C-band European Remote Sensing Satellite (ERS-1) synthetic aperture radar (SAR) data to estimate surface soil roughness in a semiarid rangeland. Radar backscatter coefficients were extracted from a dry and a wet season SAR image and were compared with 47 in situ soil roughness measurements obtained in the rocky soils of the Walnut Gulch Experimental Watershed, southeastern Arizona, US Both the dry and the wet season SAR data showed exponential relationships w root mean square (RMS) height measurements. The dry C-band ERS-1 SAR data were strongly correlated (R2 = 0.80), while the wet season SAR data have somewhat higher secondary variation (R2 = 0.59). This lower correlation wa probably provoked by the stronger influence of soil moisture, which may be negligible in the wet season SAR data. We concluded that the single configuration C-band SAR data is useful to estimate surface roughness of ro osoils in a semiarid rangeland.

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