|Oldak, Anna - USDA/ARS CONTRACTOR|
|Bindlish, Rajat - USDA/ARS CONTRACTOR|
|Gasiewski, A - NOAA ENVIRON TECH LAB|
|Klein, M - NOAA ENVIRON TECH LAB|
|Yevgrafov, A - NOAA ENVIRON TECH LAB|
|Christiani, S - UNIV OF KARLSRUHE|
|Njoku, E - NASA-JPL|
Submitted to: International Geoscience and Remote Sensing Symposium Proceedings
Publication Type: Proceedings
Publication Acceptance Date: April 20, 2001
Publication Date: May 20, 2001
Interpretive Summary: There have been few large scale validation and mapping studies of soil moisture conducted using C-band passive microwave radiometers. Since this will be a component of many future research and operational satellite missions, efforts must be made to acquire appropriate data sets. The PSR/C and its SGP99 participation represent a significant contribution to algorithm development and validation. SGP99 was the first use of PSR/C. It was necessary to carefully evaluate the data quality and sensor calibration. Techniques were developed to remove RFI and normalize the multiple flight lines collected for mapping. Analysis of soil moisture and emissivity relationships support the general retrieval techniques proposed. The algorithms developed will be implemented as part of a global soil moisture mapping program with potential benefits to agricultural water management and climate analyses.
Technical Abstract: The Advanced Microwave Scanning Radiometer (AMSR) holds the great promise for soil moisture mapping in regions of low levels of vegetation. Soil moisture retrieval algorithms for AMSR have been proposed but have not been rigorously evaluated. The Southern Great Plains 1999 Experiment (SGP99) was designed to provide aircraft data sets for algorithm development and validation. Ground observations of soil moisture and related variables wer collected in conjunction with aircraft measurements using the NOAA Polarimetric Scanning Radiometer C-band scanhead (PSR/C). The PSR/C operates at a band identical to that of the 6.92 GHz channel of AMSR. Flights were conducted under a wide range of soil moisture conditions, thus providing a robust data set for validation.