An experimental system for the integration of GIS data in knowledge-based image analysis for remote sensing of agriculture
This paper describes a knowledge-based system which has been developed for integrating easily-available geographical context information from a GIS in remotely-sensed image analysis. An experiment is described in which soil maps and buffered road networks have been used as additional data layers for classifying single date SPOT images for estimates of crop acreages. The map datasets have been digitised, co-registered to the satellite imagery, and manipulated using ARC/INFO. The knowledge base consists of both image context rules and geographical context rules. Probabilistic information from the image classifier and from the rule base is combined using the Dempster-Shafer model of evidential reasoning. Tests using ground data from the Département Loir-et-Cher, France, have shown that use of the knowledge-based system with GIS data gives an accuracy improvement of approximately 13 % compared to using a parametric image classifer alone.
Bibliographic Reference: Article: International Journal of Geographical Information Systems, Vol. 7 (1993) No. 3, pp. 247-262
Record Number: 199311446 / Last updated on: 1994-11-28
Original language: en
Available languages: en