4.7 Article

Comparison of ground-based and remotely-sensed surface soil moisture estimates over complex terrain during SMEX04

Journal

REMOTE SENSING OF ENVIRONMENT
Volume 112, Issue 2, Pages 314-325

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2006.10.028

Keywords

Soil Moisture Experiment 2004; North American monsoon; watershed soil moisture variability; aircraft remote sensing; topographic control; semiarid hydrology

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Comparisons to ground-based surface soil moisture estimates are necessary to evaluate the capability of remote sensors to determine Soil moisture and its spatiotemporal variability. Soil moisture can be especially variable in regions of complex terrain which exhibit large variations in vegetation, soil properties and hydrologic conditions. The objective of this study is to evaluate the spatiotemporal variability of soil moisture in a mountainous basin in northwestern Mexico. Soil moisture estimates from ground sampling over a topographic transect and high resolution retrievals from the Polarimetric Scanning Radiometer are compared during a two week period in August 2004 as part of the Soil Moisture Experiment 2004. Results indicate that the soil moisture estimates exhibit similar variability with mean water content. Statistical analysis, however, reveals clear differences in soil moisture in the basin, in particular for wet periods and high elevations. Despite these differences, the temporal persistence of soil moisture from the estimates agrees well and indicates locations that capture the basin-averaged conditions. Furthermore, the spatiotemporal soil moisture characteristics from the two products are linked to terrain attributes. As a result, a hypsometric technique is shown to improve comparisons between basin-averaged values derived from ground data and remote sensing, as compared to arithmetic averaging. To our knowledge, this study is the first attempt to evaluate PSR/CX retrievals with respect to ground observations over a region of high topographic and vegetation variability using statistical, time-stability and terrain analysis techniques. (C) 2007 Elsevier Inc. All rights reserved.

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