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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 #337605

Research Project: Leveraging Remote Sensing, Land Surface Modeling and Ground-based Observations ... Variables within Heterogeneous Agricultural Landscapes

Location: Hydrology and Remote Sensing Laboratory

Title: Unmanned airborne thermal and mutilspectral imagery for estimating evapotranspiration in irrigated vineyards

Author
item NIETO, H. - Institute De Recerca I Tecnologia Agroalimentaries (IRTA)
item BELLVERT, J. - Institute De Recerca I Tecnologia Agroalimentaries (IRTA)
item Kustas, William - Bill
item Alfieri, Joseph
item Gao, Feng
item Prueger, John
item TORRES, A. - Utah State University
item HIPPS, L.E. - Utah State University
item ELRAAB, M. - Collaborator
item SONG, L. - Southwest University

Submitted to: Geoscience and Remote Sensing Symposium Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: 3/13/2017
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Thermal-infrared remote sensing of land surface temperature (LST) provides valuable information for quantifying rootzone water availability, evapotranspiration (ET) and crop condition. This paper describes the most recent modifications applied to the robust but relatively simple LST-based energy balance model, the Two-Source Energy Balance (TSEB), which solves for the soil/substrate and canopy temperatures that achieves a balance in the radiation and turbulent heat flux exchange with the lower atmosphere for the soil/substrate and vegetation elements. As a result, the TSEB modeling framework is applicable to a wide range in atmospheric and canopy cover conditions. This work illustrates the utility of high resolution LST data providing within-field variability in energy fluxes and evapotranspiration (ET), including modifications made in TSEB to be adapted for structurally complex crops, such as vineyards. Such high resolution spatial information is being used in precision farming applications to assess the impacts of within variability in soil texture, water availability and other stress factors on plant condition and productivity.