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Title: AIRBORNE OBSERVATIONS OF SOIL MOISTURE AND VEGETATION DURING SGP99 USING THE PALS SENSOR

Author
item NJOKU, ENI - NASA, JPL
item WILSON, WILLIAM - NASA, JPL
item YEUH, SIMON - NASA, JPL
item Jackson, Thomas
item LAKSHIMI, VENKAT - UNIV OF SOUTH CAROLINA

Submitted to: Sring Meeting American Geographical Union Washington DC
Publication Type: Abstract Only
Publication Acceptance Date: 4/5/2000
Publication Date: N/A
Citation: N/A

Interpretive Summary: None.

Technical Abstract: A new airborne sensor has been developed recently to investigate the benefits of multichannel active and passive microwave remote sensing of soil moisture. The sensor is the Passive/Active L/S-band (PALS) sensor designed to be flown on a C-130 aircraft. PALS was flown for the first time during the 1999 Southern Great Plains experiment (SGP99) in Oklahoma and acquired data over several flight lines in conjunction with ground samplin of soil moisture and other surface characteristics. The PALS contribution to SGP99 results is a set of calibrated brightness temperature and radar backscatter data that can be used to study the dual-polarized passive and active sensitivity to soil moisture and vegetation at L and S bands. PALS data will be used with other L and C-band airborne sensors flown at different altitudes during SGP99 to study calibration, spatial scaling, and frequency-dependent effects at 1 to 7 GHz. PALS data from the 6 days of flights over field sites in the Little Washita basin confirm the high sensitivity to soil moisture at L-band and the increased sensitivity to vegetation at S-band. The observed correlation of the L-band horizontally polarized brightness temperatures with in-situ sampled soil moisture is very high (correlation coefficient >0.92) since the majority of fields sampled had bare or pasture vegetation cover with biomass less than 0.5 kg m-2. Adjacent east-west flight lines were flown on each day of the mission enabling images of the Little Washita area to be produced for each radiometer and radar sensor channel. These images show sensor channel-dependent spatial patterns of wetting and drying that are linked to the soil, vegetation, and topography of the basin.