GADAS (Global Agricultural and Disaster Assessment System)
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1.
United States Department of Agriculture
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2.
Foreign Agricultural Service
Description
The International Production Assessment Division (IPAD), found under the program area of the Global Market Analysis (GMA) within USDA's Foreign Agricultural Service (FAS), developed the GADAS (Global Agricultural and Disaster Assessment System).
FAS-IPAD leverages cutting-edge technology, utilizing satellite imagery and remote sensing data to provide insightful agricultural estimates on a global scale. Monthly, FAS-IPAD delivers estimates on area, yield, and production for 17 key grain, oilseed, and cotton commodities across more than 160 countries. These estimates are informed by reporting from FAS's worldwide offices, official statistics of foreign governments, and analysis of economic data and satellite imagery, including post-disaster assessments.
GADAS is a powerful web-based visualization tool based on an ArcGIS platform that integrates near real-time Earth Observation data to monitor global agricultural conditions and rapidly assess the impacts of natural disasters on agricultural production. GADAS has more than 1,000 data layers including environmental, satellite imagery, disaster, and associated data sets that can be interactively visualized or downloaded as charts or maps. The data sets can be used together with user uploaded data and geo-processing tools to enhance analysis and collaborate with colleagues. These datasets in GADAS make analysis easier because the work associated with obtaining the data, managing the geospatial products, and sharing them are all contained in a single environment. USDA highlights GADAS as a ready-to-use application for international analysis.
To access GADAS, please use the following link: https://geo.fas.usda.gov/GADAS/index.html
Discover GADAS for:
- Global Agricultural Monitoring and Forecasting
- Comparative Climatic and Vegetation Analysis
- Environmental Change Detection
- Drought Monitoring
- Natural Disaster Assessment
- Tracking Historical Storm Events
- Highlighting Regional Agricultural Disaster Risks
- Spatial Modeling for Potential Impacts
- Delineation of Land Use Worldwide
- Time-series weather and agrometeorological data graphs
- Time-series commodity data graphs