Model-based remotely-sensed imagery interpretation
- 1 August 1988
- journal article
- research article
- Published by Taylor & Francis in International Journal of Remote Sensing
- Vol. 9 (8), 1347-1356
- https://doi.org/10.1080/01431168808954941
Abstract
We present a model-based remotely-sensed image interpretation expert system embeded in a knowledge-based geographic information system (K. BIS). The KBIS consists of four sub-systems: a pictorial data base system, an image interpretation expert system, a computer-aided planning system and a computer-aided cartographic system. The image interpretation expert system represents ecological knowledge and other expert knowledge by frames. Its reasoning process consists of a forward reasoning based on the Bayes classification of Landsat imagery, a backward reasoning using frame knowledge and reasoning using a spatial consistency model. A forest inventory study was conducted in Shaxian county, in the southern part of China, using this expert system. The results have shown a significant improvement. Building image interpretation expert systems within knowledge-based pictorial systems is very convenient and efficient because there are well-organized data, knowledge and procedures available.Keywords
This publication has 1 reference indexed in Scilit:
- Stratification of natural vegetation for forest and rangeland inventory using Landsat digital imagery and collateral dataInternational Journal of Remote Sensing, 1981