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Subpixel variability of remotely sensed soil moisture: an inter-comparison study of SAR and ESTAR

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2 Author(s)
R. Bindlish ; SSAI, USDA/ARS Hydrology & Remote Sensing Lab., Beltsville, MD, USA ; A. P. Barros

The representation of subpixel variability in soil moisture estimates from passive microwave data was investigated through sensitivity analysis and by comparison against the spatial structure of soil moisture fields derived from radar data. This work shows that the subpixel variability not represented in brightness temperature fields is directly associated with the spatial organization of soil hydraulic properties and the spatial distribution of vegetation. The significant implication of this result is that the physical connection between soil moisture estimates at the pixel scale and local values within the pixel weakens strongly as the sensor resolution decreases. Subsequently, the application of scaling and fractal interpolation principles to downscale passive microwave data to the spatial resolution of radar data was investigated as a means to recover spatial structure. In particular, ESTAR soil moisture data was successfully downscaled from 200 to 40 m using only one radar frequency (e.g., L-band). This application suggests that the combined use of active and passive single-band microwave remote-sensing of soil moisture is a viable approach to improve the spatial resolution of soil moisture remote-sensing

Published in:

IEEE Transactions on Geoscience and Remote Sensing  (Volume:40 ,  Issue: 2 )