In order to provide a sound basis upon which to evaluate our testbed system, it is important that the testbed support a collection of items frequently accessed by a variety of user classes. Hence we will initially base the testbed system upon several collections of spatially-indexed data that are not only important, but which also represent diversity of content, coverage, and type. In particular, these datasets involve coverages that range from local, through regional and national, to international levels; they include both datasets and metadatasets; and they contain images, digitized pictures, and digitized maps of both raster and vector type.
We have found that users focus their most frequent requests for spatial data on their local area, with regional, national, and world areas following in relative order of importance.
As an example of a local area data set, we will use Santa Barbara County, California. This will include portions of such major national data sets as DEM (digital elevation model) data, DLG (digital line graph), DOQ's (Digital Orthophoto Quads), 1990 Census data (both boundary line files and statistics), AVHRR, Spot, Landsat data. Added to these digital data sets will be information requiring conversion from analog to digital, such as original aerial photography from the Map and Imagery Teledyne Collection. This collection contains flights from the late 1920s to the present. It is a heavily used and sought after by environmental, geologic and legal interests.
We will employ at least three data sets that represent phenomena at the regional level. A first example is the South Florida Ecosystem Restoration Initiative Data Set. The purpose of the Everglades Ecosystem Restoration Initiative is to restore and maintain the elements of the ecosystem to most resemble the natural functions of a healthy, balanced, and functioning estuarine and marine environment. Participating agencies include USGS, National Biological Survey, Fish and Wildlife, NOAA, EPA, SCS, DOT, Army Corps of Engineers, Florida Dept. of Environmental Protection, and South Florida Mgt. District. Layers will include Digital Orthophotoquads, very high resolution digital elevation data, species-level habitat data for wildlife and plants, and classified land cover and land characteristics information. Although this is intended primarily for agency research, USGS has agreed that these data will be made available to the Alexandria Project as production is completed.
A second regional dataset that is part of a GIS-based analysis of Biodiversity in California is being constructed in an ongoing effort by many groups, including the Idaho Cooperative Fish and Wildlife Research Unit, The Nature Conservancy, Department of Fish and Game in California, Idaho and Oregon, to protect what remains of the California's biological diversity. The biodiversity assessment of California uses existing digital geographical data sets on land use, land cover, land ownership, topography, species ranges and locations of species, and Thematic Mapper satellite data. The digital cartographic databases that are produced will be archived at the UCSB Map and Imagery Laboratory.
A third regional dataset relating to the Sierra Nevada Ecosystem Project (SNEP), which is a study requested by, and partially funded by Congress, is intended to provide a comprehensive ecosystem assessment of the entire Sierra Nevada. The project will entail a detailed scientific assessment by an independent panel of 18 scientists integrating state-of-the-science knowledge on the biological, physical, and socioeconomic environment of the region for use in developing a set of management alternatives to maintain the health and sustainability of the ecosystem, while providing resources to meet human needs. The Biogeography Lab holdings include Remotely Sensed Imagery, Digital Elevation Data, Vegetation Data, Vertebrate Species, Land Ownership/Management, and Fire history maps. Additionally, Census TIGER data will be used. Other thematic spatial data will be layered as available.
As an example of a national data set, we plan to build a multi-layered archive consisting of: Digital Orthophoto Quads (DOQ) 1:12,500 digital images rectified to the USGS 1:24,000 topographic maps; AVHRR - one-half kilometer imagery; TIGER - the boundary line files generated for the 1990 census; DLG's - 1:100,000 digital planimetric maps; and DEM's - (1:250,000 and 1:24,000) digital elevation maps.
As examples of a world data set, we plan to commence with three initial sets of information: Digital Chart of the World (DCW), which is a new, comprehensive 1:1,000,000-scale vector digital GIS base map of the world consisting of topological layered data, based primarily on the 270 sheets comprising the 1:1,000,000 Operational Navigational Chart series produced by the Defense Mapping Agency. Geographic Names Processing System (GNPS) is a compendium of foreign geographic names, compiled by the U.S. Board on Geographic Names. Geographic Names Information System (GNIS) is a digital-database gazetteer, compiled by the U.S. Geological Survey (USGS), comprising approximately 1,400,000 place names, both physical and cultural. It includes every feature that appears on the USGS 7.5' topographic series sheets at 1:24,000-scale. Other examples of world-scale information collections will be constructed. For example, it is planned to construction an information set that relates to the geology, hydrology, climatology, and biology of the entire Amazon basin. This will be of great value in supporting EOS related research at both UCSB and other universities.
Wherever possible, existing digital metadata datasets will be ingested into the system: MARCMap (MAchine Readable Cataloging) records from the Library of Congress; map records for U.S.-government-produced maps, 1976-present; map records from MELVYL (the online catalogue of the University of California Libraries); geodex records from the American Geographical Society Collection (University of Wisconsin-Milwaukee Library) which are sheet-level records for U.S. and foreign-country large and medium-scale topographic map series; Map-series level records, a dataset maintained by the Map Library, SUNY-Stony Brook of Landsat imagery metadata, 1972-present NASA (Ames) High Altitude Missions Aerial Photography dataset.