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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 #320773

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

Location: Hydrology and Remote Sensing Laboratory

Title: Monitoring of water use, drought and yield impacts using imagery from multiple satellites

item Anderson, Martha
item JURECKA, FRANTISEK - Mendel University
item TRNKA, M. - Mendel University
item HLAVINKA, P. - Mendel University
item Gao, Feng
item HAIN, C. - University Of Maryland
item Yang, Yun
item Holmes, Thomas
item Crow, Wade
item Kustas, William - Bill

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 9/7/2015
Publication Date: 9/7/2015
Citation: Anderson, M.C., Jurecka, F., Trnka, M., Hlavinka, P., Gao, F.N., Hain, C., Yang, Y., Holmes, T.R., Crow, W.T., Kustas, W.P. 2015. Monitoring of water use, drought and yield impacts using imagery from multiple satellites. Meeting Abstract.Evaluation of drought and drought impacts through interdisciplinary methods , abstract for the 2015 InterDrought Project Summer School, Mikulov, Czech Republic, June 7-13 2015. CD-ROM CD-ROM..

Interpretive Summary:

Technical Abstract: Agricultural monitoring systems require information with continuous spatial and temporal sampling, ideally collected at daily timesteps and at spatial scales from county level down to field scale. While remote sensing data significantly improve on the spatial sampling provided by ground-based observation networks, no single satellite provides both the high spatial and temporal resolution required for agricultural decision making. Here we describe a data fusion approach for combining estimates of evapotranspiration (ET) generated from multiple satellites for monitoring daily crop water use at field scale, as well as for providing early warning of developing crop stress and associated yield anomalies. The key diagnostic inputs to the modeling system are multi-scale satellite retrievals of land-surface temperature, which serve as a proxy indicator of the surface moisture status within an energy balance framework. Example applications of these tools for drought monitoring and yield forecasting over the Czech Republic are presented, and future steps are outlined to investigate utility for integration within the InterDrought suite of agricultural monitoring tools.