Extended Validation of AMSR-E Soil Moisture Products
PI: Thomas J. Jackson
Institution: USDA ARS Hydrology Laboratory and Remote Sensing Lab
Bldg. 007, BARC West, Rm 104
Beltsville, MD 20705
- Venkat Lakshmi, University of South Carolina
- David D. Bosch, USDA ARS Southeast Watershed Research Lab
- David C. Goodrich, USDA ARS Southwest Watershed Research Center
- Mark Seyfried, USDA ARS Northwest Watershed Research Center
- Patrick J. Starks, USDA ARS Grazinglands Research Lab
EOS Team: AMSR-E
NASA EOS-PSO funding through FY02: $187,767
The EOS Aqua AMSR-E soil moisture product will be the first attempt at routinely
mapping surface soil moisture. Soil moisture products from the AMSR-E have to
be validated because the retrieval algorithms utilize formulations, parameters
and ancillary data that have not been thoroughly developed and verified. Validating
these soil moisture products at the scale of the AMSR-E footprint will be difficult.
The current validation plan adequately addresses some aspects through episodic
field campaigns. Longer-term observations in diverse environments are needed
to understand variations in the soil moisture-brightness temperature relationships
that arise from seasonal variations of vegetation and validate the retrieval
for a range of conditions. Addressing these issue with existing networks is
not adequate since the spatial density of measurements these networks provide
cannot be used to estimate the mean and variance of the AMSR footprint retrieval,
which is required for validation.
We propose to extend and strengthen the current validation plan by adding well calibrated, real time, and publicly available observations of the average soil moisture for U.S. watersheds in different climate and physiographic regions that will be used to quantify the accuracy of the AMSR-E products on a continuous long term basis of this product. Four ARS watersheds will provide data in this project. These are located in Arizona, Georgia, Idaho, and Oklahoma. (see Figure). The project will provide well calibrated real time surface soil moisture from the SCAN stations in each watershed, provide a watershed average soil moisture using supplemental sampling within thirty days, and contribute to the development of a sound theoretical basis for scaling from a single station (SCAN) to the integrated watershed/footprint average.
Results of the project will contribute to quantifying the accuracy of the soil moisture product over the entire year. A robust validation will lead to increased reliability, acceptance and use of the soil moisture data in land surface hydrology and climate studies.