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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 #294625
Title: Mapping land-surface fluxes of carbon, water and energy from field to regional scales

Author
item Schull, Mitchell
item Anderson, Martha
item Kustas, William - Bill
item Gao, Feng
item HOUBORG, RASMUS - European Commission-Joint Research Centre (JRC)

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 4/15/2013
Publication Date: 4/30/2013
Citation: Schull, M.A., Anderson, M.C., Kustas, W.P., Gao, F.N., Houborg, R. 2013. Mapping land-surface fluxes of carbon, water and energy from field to regional scales [abstract]. 2013 NASA Terrestrial Ecology Science Team Meeting, Scripps Seaside Forum, April 30 - May 2, 2013, La Jolla, CA.

Interpretive Summary:

Technical Abstract: A framework for routine mapping of land-surface fluxes of carbon, water, and energy at the field to regional scales has been established for drought monitoring, water resource management, yield forecasting and crop-growth monitoring. The framework uses the ALEXI/DisALEXI suite of land-surface models in conjunction with remotely sensed data from Landsat, MODIS (MODerate resolution Imaging Spectroradiometer), and GOES (Geostationary Operational Environmental Satellite). In order to obtain high resolution in both space and time, we employ the use of the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) to obtain time-continuous datasets of land-surface fluxes at Landsat spatial resolution using Landsat (30 m) high spatial and MODIS high temporal resolutions. Thermal infrared (TIR) data provides valuable information about the sub-surface moisture status, and land-surface temperature can be an effective substitute for in-situ surface moisture observations and a valuable metric for constraining land-surface fluxes at sub-field scales. We use a multi-scale thermal-based land surface modeling framework to facilitate regional to local downscaling of carbon, water and energy fluxes by using a combination of shortwave reflective and TIR imagery from GOES, MODIS and Landsat. In addition biophysical vegetation properties are retrieved at 30 m resolution using a blended surface reflectance dataset as input to the REGularized canopy reFLECtance (REGFLEC) tool. REGFLEC facilitates retrievals of leaf chlorophyll (Cab), a biophysical parameter that has been recognized as a key parameter to quantify variability in photosynthetic efficiency. Cab is used here to estimate the spatial-temporal variations in nominal light-use-efficiency (LUEn), a fundamental parameter that modulates the flux of carbon and water in the land-surface modeling framework. The thermal-based modeling system has been applied to regions of rain fed and irrigated soy and corn agricultural landscapes within the continental U.S. and flux simulations have been compared with flux tower observations.