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United States Department of Agriculture

Agricultural Research Service

Research Project: USING REMOTE SENSING & MODELING FOR EVALUATING HYDROLOGIC FLUXES, STATES, & CONSTITUENT TRANSPORT PROCESSES WITHIN AGRICULTURAL LANDSCAPES Title: Aircraft data collection in support of NASA's earth observing satellite missions

Authors
item MLADENOVA, ILIANA
item JACKSON, THOMAS

Submitted to: BARC Poster Day
Publication Type: Abstract Only
Publication Acceptance Date: March 21, 2011
Publication Date: April 27, 2011
Citation: Mladenova, I., Jackson, T.J. 2011. Aircraft data collection in support of NASA's earth observing satellite missions [abstract]. Abstract 38, BARC Poster Day.

Technical Abstract: NASA's Earth observing missions have been providing global information on soil moisture, vegetation, and precipitation that is crucial for hydrological and agricultural applications. For example, accurate soil moisture information is a key component in land surface and agricultural models used for water, energy and carbon cycle estimation, climate/weather prediction, and flood/drought monitoring. To satisfy this demand, NASA is planning to launch a new soil moisture mission called Soil Moisture Passive Active (SMAP). The mission will provide high resolution soil moisture data at almost an order of magnitude better spatial resolution than we have today. It will provide operational radar-based and a combined radiometer-radar derived soil moisture product, in addition to the traditional radiometer-based retrieval. SMAP algorithms are currently under development and testing. This requires microwave data sets that are compatible with the mission system characteristics. As a result, several extensive field campaigns have been undertaken for gathering these critical data sets. This presentation reports on the Canadian Soil Moisture Experiment (CanEx), conducted during the month of June 2010 in Saskatchewan, Canada. In particular, the radar data acquired as a part of CanEx. Aircraft-based radars such as the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR), which was flown during CanEx, offer an effective way of collecting the spatial and temporal data needed for the SMAP algorithm development and validation. However, UAVSAR observes the ground at a wide range of incidence angles (20º–65º) whereas SMAP will operate at a fixed angle of 40º. Thus, an angular adjustment must be made to the aircraft data. Here, we propose a normalization approach that is based on a histogram matching procedure. The multi-incidence UAVSAR radar data were modified to approximate the response at 40º by utilizing the lowest two central moments, the mean and variance. Evaluation was conducted using actual backscatter data observed at 40º. This was made possible due to the large overlap between the seven flight lines that were flown over the domain, which provided coverage of the same point on the ground at various angles. Improvement in the root mean square error indicated that the technique successfully accounts for the incidence angle effect and was able to adequately correct throughout the whole incidence angle range of the UAVSAR system. Along with providing data that matches the SMAP configuration, the technique may be beneficial in terms of reducing the number of flight lines, which would eventually result in more cost-effective field campaigns.

Last Modified: 9/29/2014
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