Application of a Bayesian network in a GIS based decision making system

International Journal of Geographical Information Science

Volumn 12, Issue 1, 1998, Pages 23-46

  Stassopoulou, A ^a   Petrou, M ^a   Kittler, J ^a  

^a UNIVERSITY OF SURREY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN ANALYSIS; BAYESIAN NETWORK; DATA ACCURACY; DECISION MAKING; DECISION SUPPORT SYSTEM; DESERTIFICATION; GIS; UNCERTAINTY;

MEDITERRANEAN;

EID: 0031896928     PISSN: 13658816     EISSN: None     Source Type: Journal    
DOI: 10.1080/136588198241996     Document Type: Article

References (29)

1. ABRAMSON, B., 1994, The design of belief network-based systems for price forecasting. Computers and Electronic Engineering, 20, 163-180.
2. ASPINALL, R., 1992, An inductive modelling procedure based on Bayes' theorem for analysis of pattern in spatial data. International Journal of Geographical Information Systems, 6, 105-121.
3. BOLTON, M., 1979, A Guide to Soil Mechanics (London: Macmillan).
4. BONHAM-CARTER, G. F., 1991, Geographic Information Systems for Geoscientists: Modelling with GIS (Oxford: Pergamon) pp. 267-337.
5. CHARNIAK, E., 1991, Bayesian networks without tears. AI Magazine, 12, 50-63.
6. CHUVIECO, E., and CONGALTON, R. G., 1989, Application of remote sensing and geographic information systems to forest fire hazard mapping. Remote Sensing of Environment, 29, 147-159.
7. DUCKSBURY, P. G., 1993, Parallel texture region segmentation using a Pearl Bayes Network. In Proceedings of the 4th British Machine Vision Conference, Surrey, U.K., September 1993 (BMVA Press), pp. 187-195.
8. FISHER, P. F., 1991, First experiments in viewshed uncertainty: The accuracy of the viewshed area. Photogrammetric Engineering and Remote Sensing, 57, 1321-1327.
9. GOLDMAN, R. P., and CHERNIAK, E., 1993, A language construction of belief networks. Pattern Analysis and Machine Intelligence, 15, 196-208.
10. GONG, S., and BUXTON, H., 1993, From contextual knowledge to computational constraints. In Proceedings of the 4th British Machine Vision Conference, Surrey, U.K., September 1993 (BMVA Press), pp. 229-238.
11. GRUNBLATT, J., OTTICHILO, W. K., and SINANGE, R. K., 1992, A GIS approach to desertification assessment and mapping. Journal of Arid Environments, 23, 81-102.
12. GU, Y., PEIRIS, D., CRAWFORD, J., MCNICOL, J., MARSHALL, B., and JEFFERIES, R., 1994, An application of belief networks to future crop production. In Proceedings of the 10th Conference on Artificial Intelligence for Applications, San Antonio, Texas, 1994, pp. 305-309.
13. HAAS, T. C., 1991, A Bayesian belief network advisory system for aspen regeneration. Forest Science, 37, 627-654.
14. HAMILTON, P. W., ANDERSON, N., BARTELS, P. H., and THOMPSON, D., 1994, Expert system support using Bayesian belief networks in the diagnosis of fine needle aspiration biopsy specimens of the breast. Journal of Clinical Pathology, 47, 329-336.
15. HECKERMAN, D., BREESE, J. S., and ROMMELSE, K., 1995, Decision-theoretic troubleshooting. Communications of the ACM, 38, 49-56.
16. HENRION, M., 1989, Some practical issues in constructing Belief Networks. In Uncertainty in Artificial Intelligence (3), edited by Kanal, L. N., Levitt, T. S. and Lemmer, J. F., (London: Elsevier Science Publisher), pp. 161-173.
17. HUNTER, G. J., and GOODCHILD, F., 1995, Dealing with error in spatial databases: A simple case study. Photogrammetric Engineering and Remote Sensing, 61, 529-537.
18. KIM, J., and PEARL, J., 1983, A computational model for causal and diagnostic reasoning in inference systems. In Proceedings of the 8th International Joint Conference on Artificial Intelligence, pp. 190-193.
19. KIM, J. H., and PEARL, J., 1987, Convince: A conversational inference consolidation engine. I.E.E.E. Transactions on Systems, Man and Cybernetics, 17, 120-132.
20. MORGAN, R. P. C., 1986, Soil Erosion and Conservation (Harlow: Longman).
21. OLESEN, K. G., KJAERULFF, U., JENSEN, F., JENSEN, F. V., FALCK, B., ANDREASSEN, S., and ANDERSEN, S. K., 1989, A munin network for the median nerve-a case study on loops. Applied Artificial Intelligence, 3, 385-403.
22. PEARL, J., 1986, Fusion, propagation, and structuring in Belief Networks. Artificial Intelligence, 29, 241-288.
23. PEARL, J., 1988, Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference (Morgan Kaufmann Publishers).
24. PEARL, J., 1993, Belief networks revisited. Artificial Intelligence, 59, 49-56.
25. PICKUP, G., 1994, Modelling patterns of defoliation by grazing animals in rangelands. Journal of Applied Ecology, 31, 231-246.
26. PICKUP, G., and CHEWINGS, V. H., 1994, Identifying and measuring land degradation process using remote sensing. In The Use of Remote Sensing for Land Degradation and Desertification Monitoring in the Mediterranean Basin: State of the Art and Future Research, European Commission Experts Workshop, Valencia, Spain, June 1994, pp. 135-147.
27. SADER, S. A., AHL, D., and LIOU, W., 1995, Accuracy of Landsat-TM and GIS rule-based methods for forest wetland classification in Maine. Remote Sensing of the Environment, 53, pp. 133-144.
28. SHAFER, G. A., 1976, Mathematical Theory of Evidence (Princeton, N.J.: Princeton University Press).
29. SUERMONDT, H. J., and COOPER, G. F., 1991, Initialisation for the method of conditioning in Bayesian belief networks. Artificial Intelligence, 50, 83-94.