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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: Integration of GOES, MODIS and HyspIRI Thermal Satellite Imagery for Evaluationof Daily Evapotranspiration at the Sub-Field Scale

Authors
item Anderson, Martha
item Kustas, William
item Dulaney, Wayne
item Feng, Gao -
item Summer, David -

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: August 12, 2010
Publication Date: August 24, 2010
Citation: Anderson, M.C., Kustas, W.P., Dulaney, W.P., Feng, G., Summer, D. 2010. Integration of GOES, MODIS and HyspIRI thermal satellite imagery for evaluation of daily evapotranspiration at the sub-field scale [abstract]. 2010 HyspIRI Science Workshop. 2010 CDROM.

Technical Abstract: Development of robust algorithms for routine monitoring of evapotranspiration (ET) over large areas at spatial resolutions that discriminate individual agricultural fields (<100 m resolution) and small hydrologic features will benefit an array of water resource management applications. Land-surface temperature (LST) derived from thermal infrared (TIR) remote sensing has proven to be a valuable input to surface energy balance algorithms for estimating ET and serves as an effective proxy for spatially distributed surface moisture and precipitation measurements. Routine monitoring with the current suite of TIR sensors provides broad coverage of a range of spatiotemporal sampling scales. Geostationary satellites such as GOES provide 15 minute LST fields at 5-10 km spatial resolution, polar orbiting systems such as MODIS generate TIR data at 1km resolution every one-two days, while the HyspIRI TIR system will produce relatively high resolution (60 m) maps every 5 days or longer, depending on cloud cover. This paper will discuss a strategy for integrating GOES, MODIS and HyspIRI TIR and shortwave imagery to map daily ET at 60 m resolution. The methodology is based on the continental-scale Atmosphere-Land Exchange Inverse (ALEXI) surface energy balance algorithm, which maps hourly ET using GOES data. Associated flux disaggregation techniques (DisALEXI) downscales ALEXI fluxes using MODIS and Landsat TIR imagery (used as a proxy for HyspIRI data). Finally, a new spatial data fusion algorithm, STARFM, is used to merge the MODIS and HyspIRI-scale ET evaluations, generating daily predicted fields at the 60 m scale. In this way, we make full use of all available TIR data in interpolating surface moisture conditions between HyspIRI overpasses. The methodology has been tested over sites in southern Florida and Texas, representing areas where high-resolution time-continuous ET data are urgently needed for decision making by growers and water management agencies.

Last Modified: 12/19/2014
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