The Role of Artificial Intelligence in the Integration of Remotely Sensed Data with Geographic Information Systems
Abstract
Although databases for geographic information systems (GIS) have been developed to manage digital map data, the integration of remotely sensed imagery and other collateral non-map information is rarely performed. For the most part, the use of sophisticated intelligent spatial databases, in which the user can query interactively about map, terrain, or associated imagery, is unknown in the GIS and cartographic community. In standard GIS systems, the ability to formulate complex queries requiring dynamic computation of factual and geometric properties is severely limited, often reflecting its origin as collections of thematic map overlays. Spatial database research requires the integration of ideas and techniques from many disciplines such as computer graphics, computational geometry, database methodology, image analysis, photogrammetry, and artificial intelligence. This paper discusses some ideas on how the scope of geographic information systems can be expanded by using artificial intelligence techniques which may remedy deficiencies in user interfaces, spatial data representation and its utilization. We draw on ongoing research at this university for examples of these techniques in the areas of image/map database and knowledge-based image interpretation.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 01, 1987
- Accession Number
- ADA188744
Entities
People
- David M. Mckeown Jr.
Organizations
- Carnegie Mellon University