|Le Vine, David|
|Starks, Patrick - Pat|
Submitted to: IEEE Transactions on Geoscience and Remote Sensing
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/24/1999
Publication Date: N/A
Citation: N/A Interpretive Summary: Surface soil moisture retrieval algorithms based on remotely sensed microwave observations, developed and verified at high spatial resolution, were evaluated in a regional scale experiment. Using previous investigations as a base, the Southern Great Plains Hydrology Experiment (SGP97) was designed and conducted to extend the algorithm to courser resolutions, larger regions with more diverse conditions, and longer time periods. That is conditions similar to satellite based applications. The L-band Electronically Scanned Thinned Array Radiometer (ESTAR) was used for daily mapping of surface soil moisture over an area greater than 10,000 km2 for a one month period. Results show that the soil moisture retrieval algorithm performed the same as in previous investigations, demonstrating consistency of both the retrieval and the instrument. This result showed that for the coarser resolution used here that the theory and techniques employed in the algorithm apply at this scale. The conclusions support a satellite based implementation and are a highly significant contribution to both hydrolic and remote sensing studies.
Technical Abstract: Microwave radiometry at long wavelengths can be used to measure and monitor surface soil moisture. A key issue in implementing this approach has been the inherent spatial resolution problem of long wavelength microwave radiometry at spacecraft altitudes. Synthetic aperture radiometry can solve this problem with spatial resolutions on the order of 10 to 30 km. A major objective of this investigation was to evaluate the extension of high resolution soil moisture retrieval algorithms to coarser resolutions. To answer this question, a large scale field experiment called the Southern Great Plains 1997 (SGP97) Hydrology Experiment was conducted. An L-band passive microwave sensor was used to map surface soil moisture over 10,000 km2 for one month. Calibration of the ESTAR was verified using ground observations and results of previous experiments in this region. An established soil moisture algorithm was implemented using ancillary data bases. Soil moisture images show consistent spatial structure that was dominated by rainfall distribution with soil texture and vegetation levels having a secondary effect. Results clearly demonstrated the performance of both the ESTAR instrument and the soil moisture algorithm. It was concluded that the algorithms can be extrapolated from higher resolution ground experiments to satellite scales.