Abstract:
The Production Estimates and Crop Assessment Division (PECAD) of USDA's Foreign Agricultural Service (FAS) is responsible for global crop condition assessments and estimates of area, yield, and production for grains, oilseeds, and cotton. The primary mission of PECAD is to produce the most objective and accurate assessment of the global agricultural production outlook and ... the conditions affecting food security in the world. Regional analysts use a Geographic Information System (GIS) to collect market intelligence, and forecast reliable global production numbers for grains, oil seeds and cotton.
The FAS has a global network of attach's that provide on-the-ground reports of observed crop and contextual information. Also, the FAS regional analysts travel extensively in the countries they cover to more fully develop the context and constraints within which their assessments are made. Other contextual information such as official governmental reports, trade and news sources play a significant role in interpreting how these factors will affect price and policies and other econometric analyses. PECAD's final production estimate, produced by the 10th day of each month and cleared by the World Agricultural Outlook Board, is based on an all source convergence of evidence methodology. The final production estimates are used in a variety of ways:
- Official USDA statistics - Principle Federal Economic Indicators - Crop conditions and early warning alerts - Agricultural monitoring and food security - Foreign aid assessments for food import needs - Disaster monitoring and relief efforts related to food aid - Commercial market trends and analysis - Trade policy and exporter assistance
PECAD relies on remote sensing data from satellite sensors (Figure 2) as an important source of data for its GIS. Selected data sets provide daily, weekly, and targeted coverage with resolutions ranging from 1km to less than 1m. The data is stored on a terabyte server accessible to each analyst workstation. The most common data formats used operationally with ArcGIS at PECAD are TIFF and compressed MrSID images.
The Crop Condition Data Retrieval and Evaluation database (CADRE) is the main decision support tool used in the GIS by PECAD analysts. CADRE is a global grid-based, geospatial database that stores daily, monthly, and decadal (10-day) data. The sources for this data are the Air Force Weather Agency (AFWA) and the World Meteorological Organization (WMO). PECAD takes this source data and models precipitation, temperature, soil moisture and crop stages. To measure vegetative vigor, PECAD calculates vegetation index numbers (VINs) from satellite derived data. The data is imported into 1/8 degree mesh grid cells (Figure 3) and can be categorized by:
Time-series data sets: - Daily WMO station data (precipitation, min and max temperatures) - Daily agrometeorological data derived from station and satellite data include precipitation; min and max temperatures; snow depth; solar and longwave radiation; potential and actual evapo-transpiration. - Biweekly and decadal vegetation index (VINs) derived from Local Area Coverage (LAC), approx 1.1-km pixels and Global Area Coverage (GAC), approx 8-km pixels from the NOAA-AVHRR satellite series.
Normal baseline data sets: - Normal precipitation and temperature values for WMO stations (from WMO and NOAA) - Normal precipitation, temperature, potential evaporation, and elevation values imported into1/8 mesh grid cells from UNEP/GRID-Geneve - Soil-water holding capacity based upon the United Nations Food and Agriculture Organization's (FAO) Digital Soil Map of the World at 1:5M scale - Biweekly VIN normals or averages for the GAC data set. Crop Information and Models: - Crop type and average start of season - Average yield and area planted - Percent crop production within a country - Two-layer soil moisture algorithm - Crop calendars (based on growing-degree days) - Crop stress or alarm models for corn and wheat (based on soil moisture and temperature thresholds) - Crop water production functions to estimate relative yield reductions (yield reduction models) - Crop stage models by Ritchie (1991).
CADRE extraction routines: - Automated maps and graphs generated every 10 days for diaplay - Interactive ARCVIEW 3.2 scripts for displaying station and grid cell data - Interactive CADRE X-tract program for displaying graphs
The Crop Explorer web application features near-real-time global crop condition information based on the satellite imagery and weather data processed by PECAD. The web mapping application uses Cold Fusion, Java, ArcIMS, SQL Server, and ArcSDE to manage and store the geospatial data. ArcSDE relationships are set up between PECAD "regions" and the various feature classes used by the maps (e.g. rivers, administrative boundaries, etc.). The Crop Explorer ArcIMS MapService is built using these same ArcSDE features. During a map generation request, the grid-cell layer feature class is joined to the appropriate attribute data such as precipitation, soil moisture, or temperature. Java is used to build the necessary AXL code to make the request to ArcIMS. Cold Fusion manages the map display in the web browser.
Thematic maps of major crop growing regions depict vegetative vigor, precipitation, temperature, and soil moisture. Time-series charts depict growing season data for specific agro-meteorological zones. Regional crop calendars and crop area maps are also available for selected regions. U.S. producers, traders, researchers, and the public can use Crop Explorer to visualize this information with a web browser. Regional droughts or excessively wet conditions can be easily identified by the amount of ground-surface "greenness" as depicted by the Normalized Difference Vegetation Index (NDVI), a measure of vegetative vigor derived from AVHRR satellite imagery. In addition, daily satellite image composites originating from the NASA MODIS Rapid Response System are now directly linked to selected agricultural regions within Crop Explorer.
Kaplan, A., M. Cane, Y. Kushnir, A. Clement, M. Blumenthal, and B. Rajagopalan, Analyses of global sea surface temperature 1856-1991, Journal of Geophysical Research, 103, 18,567-18, 589, 1998.
Cane, M.A., A.C. Clement, A. Kaplan, Y. Kushnir, R. Murtugudde, D. Pozdnyakov, R. Seager, and S.E. Zebiak., 1997: 20th century sea surface temperature trends. Science, 275, 957--960.
