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GLAM System - Cloud-Based Global Agricultural Monitoring

GLAM in Pakistan
What We Do

The project’s objective is to enhance the agricultural monitoring and the crop-production estimation capabilities of the USDA Foreign Agriculture Service (FAS) using the new generation of NASA satellite observations.

Location

Global 

How Satellites Make This Work

USDA Foreign Agricultural Service (FAS) crop analysts use the GLAM web-based information-analysis and data-delivery system, to track the evolution of the growing season by monitoring crop conditions and tracking factors impairing agricultural productivity. To this end, GLAM developed customized web based information-analysis and data-delivery system to monitor crop conditions and to locate and track the factors impairing agricultural productivity. This system has been scaled and updated to meet the needs of various organizations around the world at regional and national scales. This system provides crop analysts with a suite of MODIS and VIIRS temporal composites of vegetation index data, false color imagery, and a dynamic crop mask. These data products are supplemented by the CHIRPS (Climate Hazards Group InfraRed Precipitation plus Station data) rainfall composites provided by the USGS Climate Hazards Group. Complementing these data products is a range of web-based analysis tools that allow analysts to interrogate these data and to drill down to the pixel level of detail. Using these data and tools analysts track the evolution of the growing season, make inter-annual comparisons of season dynamics and inform decision makers of agricultural conditions and impediments to worldwide food-security.

 

Related CGAMR Project:

Global Agricultural Monitoring: Transitioning NPP VIIRS Observations into the USDA FAS Decision Support System

The NASA Science Applications Program, through support of the Global Agricultural Monitoring (GLAM) project, has successfully transitioned MODIS data into the operational Decision Support Systems (DSS) of the FAS, replacing the AVHRR as the primary source of global satellite observations. This proposal's primary objective is to continue NASA's role of transitioning NASA satellite data from research to operations by preparing NPP VIIRS data for inclusion in the operational FAS DSS. The approach will be to replicate the current MODIS FAS capabilities with the VIIRS.

Lead
Alyssa Whitcraft, University of Maryland
Team Members
Inbal Becker-Reshef, University of Maryland
Christopher Justice, University of Maryland
Michael Humber, University of Maryland
Dan O'Neill, University of Maryland
John Keniston, University of Maryland