Research for Reducing the Labor Intensive Nature of High-Resolution Terrain Analysis Feature Extraction
Abstract
Based on terrain analyst productivity estimates of 1000 man-hours per 15 by 15 arc-minute area, the time required to complete a single terrain analysis of the world's land surface exceeds several hundred thousand man-years. Another dilemma arises from the way we currently store and use spatial data. Current geographic information system techniques emphasize a 'brute-force' search approach to spatial storage, query and analysis. If global high- resolution terrain data were available, the response time for certain 'brute- force' data base queries might approach the above time estimates for compilation. The following research strategies are discussed which address the high-resolution dilemmas. First, terrain feature extraction should be approached from a 'minimum compilation', 'maximum analysis' strategy. In other words, map only the key terrain components, and gather additional information by thorough analysis and inferencing from this compiled spatial data. This basic approach parallels techniques used extensively in manual photo-based terrain analysis. Secondly, knowledge needs to be incorporated into all phases of terrain data compilation, storage and analysis. Low-level geometric knowledge of spatial features can be used to organize and group data together that are important at a higher symbolic level of terrain understanding. Similarly, high-level knowledge and models of regional factors such as climate and geomorphology can be used to constrain 'brute-force' search, detect errors and handle incomplete information. Exploitation of terrain knowledge in digital spatial information technology can reduce the 'data-rich' requirement and 'knowledge poor' state of current systems.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 08, 1987
- Accession Number
- ADA192661
Entities
People
- Daniel Edwards
Organizations
- Geospatial Research Laboratory