NDLI: Sub-pixel variability of remotely sensed soil moisture: an inter-comparison study of SAR and ESTAR

Content Provider	IEEE Xplore Digital Library
Author	Bindlish, R. Barros, A.P. Barros, A.P.
Copyright Year	1999
Description	Author affiliation: Dept. of Civil & Environ. Eng., Pennsylvania State Univ., University Park, PA, USA (Bindlish, R.)
Abstract	Soil moisture was retrieved from radar data using an inverse model based on the integral equation model (IEM). ESTAR images of brightness temperature obtained during the same period were inverted independently for soil moisture. The results at individual sampling sites were first compared against gravimetric soil moisture observations for Washita '94, and the RMS errors for both applications were between 3% and 4%. Subsequently, the authors investigated the use of high resolution SAR-derived soil moisture fields to estimate sub-pixel variability in ESTAR derived fields. The objective was to determine whether scaling arguments can be used to disaggregate ESTAR data to finer spatial resolution based on the geomorphic layout of the landscape. The differences in the ESTAR and SAR retrieved soil moisture were related to the amount of vegetation present at that pixel. Furthermore, they also investigated the problem of consistency between the two systems. For this purpose, SAR-derived soil moisture was aggregated to ESTAR resolution, and these estimates were used along with land surface attributes to derive the corresponding brightness temperature fields (i.e., backward retrieval). Estimated and observed brightness temperature fields were compared and analyzed to establish the aggregation kernel inherent to ESTAR, that is, how the instrument actually processes/integrates sub-pixel variability.
Starting Page	1917
Ending Page	1920
File Size	473476
Page Count	4
File Format	PDF
ISBN	0780352076
DOI	10.1109/IGARSS.1999.774986
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1999-06-28
Publisher Place	Germany
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Soil moisture Brightness temperature Spatial resolution Information retrieval Radar imaging Radar remote sensing Inverse problems Integral equations Image sampling Vegetation mapping
Content Type	Text
Resource Type	Article

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