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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #307023
Title: Mapping daily water use and vegetation stress at field to global scales using multi-satellite thermal infrared imagery

Author
item Anderson, Martha
item HAIN, C. - University Of Maryland
item Gao, Feng
item Semmens, Kathryn
item Kustas, William - Bill
item Schull, Mitchell
item Yang, Yun

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 7/7/2014
Publication Date: 9/17/2014
Citation: Anderson, M.C., Hain, C., Gao, F.N., Semmens, K.A., Kustas, W.P., Schull, M.A., Yang, Y. 2014. Mapping daily water use and vegetation stress at field to global scales using multi-satellite thermal infrared imagery [abstract]. Evapotranspiration Seminar, Alameda del Obispo, Cordoba, Spain.

Interpretive Summary:

Technical Abstract: Satellite retrievals of land-surface temperature (LST) derived from thermal infrared (TIR) imagery have proven to have significant value in constraining diagnostic models of surface energy balance and evapotranspiration (ET). A multi-scale ET retrieval system has been developed, built upon the Two-Source Energy Balance (TSEB) land-surface model that uses LST observations to estimate ET and the partitioning between evaporation and transpiration sub-components. This talk will focus on regional applications of the TSEB to TIR imagery from multiple satellite platforms. Polar orbiting systems like Landsat collect 60-100 m resolution TIR imagery every 8-16 days, providing spatiotemporal capabilities for monitoring realtime ET and vegetation stress/drought globally at the scale of human management – nominally, the field scale. Recent experiments have demonstrated that the temporal sampling of high resolution TIR imaging systems can be further enhanced by fusing lower spatial (1-5 km) but higher temporal resolution (~hourly to daily) ET retrievals using TIR data from the Moderate Resolution Imaging Spectroradiometer (MODIS) systems on board the Terra and Aqua satellite platforms (1km) and from geostationary (GEO) satellites. We describe implementations of a prototype Landsat-MODIS-GEO ET data fusion over rainfed and irrigated agricultural fields in the U.S. and demonstrate added value in comparison with a simple Landsat-only interpolation scheme – particularly when a rainfall event occurs between Landsat overpasses. Potential applications for fused ET datasets will be discussed, with societal benefits in the areas of food and water security and drought monitoring.