2007 AGU Fall Meeting, December 10-14,San Francisco, CA
Integrating NASA Satellite-Derived Precipitation and Soil Moisture Data
Into the Digital-NGP Decision Support System for Agriculture
William Teng, Xiaodong Zhang, Melissa Soriano
The usefulness of NASA satellite-derived data for agricultural decision support systems (DSS) depends on the specific applications and their spatial and temporal resolution requirements. For globally oriented DSS, such as the U.S. Department of Agriculture’s Crop Explorer, the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has demonstrated the operational usefulness of NASA precipitation data, by providing seamless, dynamic, context-sensitive Web services via the Agricultural Online Visualization and Analysis System (AOVAS). The latter is a component of the GES DISC’s Agricultural Information System (AIS), which enables the remote, interoperable, operational access to distributed data (e.g., near-real-time satellite-derived rainfall), by using the GrADS-Data Server (GDS) and the Open Geospatial Consortium (OGC)-compliant MapServer. The latter allows the access of AIS data from any OGC-compliant client, such as the Earth-Sun System Gateway (ESG) or Google Earth. AOVAS is one of a family of “Giovanni” (GES-DISC Interactive Online Visualization ANd aNalysis Infrastructure) instances, which enable users to perform interactive visualization and analysis online without downloading any data. For more regionally or locally oriented DSS, such as the Digital-NGP (Northern Great Plains), an online GIS database system for archiving and distributing remote sensing images developed by the Upper Midwest Aerospace Consortium, the usefulness of NASA data is less clear. For agricultural users from the regional down to the local (including precision farming) levels, answers to two key questions are needed: when and how. The “how” is addressed with spatial distribution (e.g., an image), particularly at the sub-field resolution. An example is the new capability of the Digital-NGP to deliver maps of management zones, using remote sensing images and field data provided by users. “When” is basically a time series question, the answer to which is primarily determined by weather and climate. Phenology of local crops will likely shift in response to global and regional climate changes, therefore it is important to track temporal variations of temperature and moisture for timely decision making. The objective of this study is to determine the extent to which NASA data and services can be usefully integrated into the Digital-NGP, i.e., can integration help to better answer the two key questions. The objective will be approached by availing the Digital-NGP of existing capabilities of Giovanni-AOVAS and AIS, as well as the capabilities of a new Giovanni-Soil Moisture instance.
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