Coupling bayesian networks with CIS-based cellular automata for modeling land use change

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4197 LNCS, Issue , 2006, Pages 217-233

  Kocabas, Verda ^a   Dragicevic, Suzana ^a  

^a SIMON FRASER UNIVERSITY   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATA THEORY; DATABASE SYSTEMS; GEOGRAPHIC INFORMATION SYSTEMS; LAND USE; MATHEMATICAL MODELS; PROBABILITY;

BAYESIAN NETWORKS; CELLULAR AUTOMATA; GEOSPATIAL MODELING; HYBRID MODEL;

COMPUTER NETWORKS;

EID: 33750246669     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11863939_15     Document Type: Conference Paper

References (37)

1. Goodchild, M.E.: Geographic information science and systems for environmental management. Annu Rev Env Resour 28 (2003) 493-519
2. Longley, P.: Geographical information systems and science. Wiley, Chichester (2005)
3. Dragicevic, S., Marceau, D.J.: A fuzzy set approach for modeling time in GIS. International Journal of Geographical Information Science 14 (2000) 225-245
4. Allen, P.M.: Cities and regions as evolutionary complex systems. Geographical Systems 4 (1997) 103-130
5. Batty, M., Longley, P.: Fractal cities : a geometry of form and function. Academic Press, London ; San Diego (1994)
6. Portugali, J.: Self-organization and the city. Springer, Berlin ; New York (2000)
7. Yeh, A.G., Li, X.: A constrained CA model for the simulation and planning of sustainable urban forms by using GIS. Environment and Planning B-Planning & Design 28 (2001) 733-753
8. Torrens, P.M., O'Sullivan, D.: Cities, cells, and complexity: developing a research agenda for urban geocomputation. In: B.H.Carlisle, R.J.A.a. (ed.): 5th International Conference on GeoComputation. "GeoComputation CD-ROM". University of Greenwich, UK (2000)
9. White, R., Engelen, G.: High-resolution integrated modelling of the spatial dynamics of urban and regional systems. Computers, Environment and Urban Systems 24 (2000) 383-400
10. Batty, M.: Urban evolution on the desktop: simulation with the use of extended cellular automata. Environment and Planning A 30 (1998) 1943-1967
11. O'Sullivan, D., Torrens, P.M.: Cellular models of urban systems. University College London, The Centre for Advanced Spatial Analysis, London, UK (2000)
12. Wu, F., Webster, C.J.: Simulation of land development through the integration of cellular automata and multicriteria evaluation. Environment and Planning B-Planning & Design 25 (1998) 103-126
13. Li, X., Yeh, A.G.O.: Urban simulation using principal components analysis and cellular automata for land-use planning. Photogrammetric Engineering and Remote Sensing 68 (2002) 341-351
14. Yeh, A.G.O., Li, X.: Simulation of development alternatives using neural networks, cellular automata, and GIS for urban planning. Photogrammetric Engineering and Remote Sensing 69 (2003) 1043-1052
15. Charniak, E.: Bayesian Networks without Tears. Ai Mag 12 (1991) 50-63
16. Heckerman, D., Mamdani, A., Wellman, M.P.: Real-World Applications of Bayesian Networks - Introduction. Commun Acm 38 (1995) 24-26
17. Little, L.R., Kuikka, S., Punt, A.E., Pantus, F., Davies, C.R., Mapstone, B.D.: Information flow among fishing vessels modelled using a Bayesian network. Environmental Modelling & Software 19 (2004) 27-34
18. Stassopoulou, A., Petrou, M., Kittler, J.: Application of a Bayesian network in a GIS based decision making system. International Journal of Geographical Information Science 12 (1998) 23-45
19. Pearl, J.: Probabilistic reasoning in intelligent systems : networks of plausible inference. Morgan Kaufmann Publishers, San Mateo, Calif. (1988)
20. Buntine, W.L.: A guide to the literature on learning probabilistic networks from data. leee T Knowl Data En 8 (1996) 195-210
21. Jordan, M.I., Sejnowski, T.J.: Graphical models : foundations of neural computation. MIT Press, Cambridge, Mass. (2001)
22. Bayes, T., Price, R., Canton, J., Deming, W.E., Molina, E.G.: Facsimiles of two papers by Bayes I. An essay toward solving a problem in the doctrine of chances, with Richard Price's forward and discussion; Phil. Trans. Royal Soc., pp.370-418, 1763. With a commentary by Edward C. Molina. II. A letter on asymptotic series from Bayes to John Canton; pp.269-271 of the same volume. With a commentary by W. Edwards Deming. Hafner Pub. Co., New York (1963)
23. Batty, M.: Cellular automata and urban form: a primer. Journal of American Planning Association 63 (1997) 266-274
24. Zhou, J., Civco, D.L.: Using genetic learning neural networks for spatial decision making in GIS. Photogrammetric Engineering and Remote Sensing 62 (1996) 1287-1295
25. Neapolitan, R.E.: Learning Bayesian networks. Prentice Hall, Harlow (2003)
26. Varis, O.: A belief network approach to optimization and parameter estimation: application to resource and environmental management. Artif Intell 101 (1998) 135-163
27. Kocabas, V., Dragicevic, S.: Assessing cellular automata model behaviour using sensitivity analysis approach. Computers, Environment and Urban Systems (In Press)
28. Sanguesa, R., Burrell, P.: Application of Bayesian Network learning methods to Waste Water Treatment Plants. Appl Intell 13 (2000) 19-40
29. Buntine, W.L.: Operations for learning with graphical models. Journal of artificial intelligence research 2 (1994) 159-225
30. Heckerman, D., Geiger, D., Chickering, D.M.: Learning Bayesian Networks - the Combination of Knowledge and Statistical-Data. Mach Learn 20 (1995) 197-243
31. Cooper, G.F., Herskovits, E.: A Bayesian Method for the Induction of Probabilistic Networks from Data. Mach Learn 9 (1992) 309-347
32. Cheng, J., Greiner, R., Kelly, J., Bell, D., Liu, W.R.: Learning Bayesian networks from data: An information-theory based approach. Artif Intell 137 (2002) 43-90
33. Heckerman, D.: A tutorial on learning with Bayesian networks. In: Jordan, M.I. (ed.): Learning in graphical models. MIT Press, Cambridge, Mass. (1999) 301-354
34. Jensen, F.V., Lauritzen, S., Olesen, K.G.: Bayesian updating in causal probabilistic networks by local computations. Computational Statistics Quarterly 4 (1990) 269-282
35. Murphy, K.: The Bayes Net Toolbox for Matlab. Computing Science and Statistics 33 (2001)
36. Menard, A., Marceau, D.J.: Exploration of spatial scale sensitivity in geographic cellular automata. Environment and Planning B-Planning & Design 32 (2005) 693-714
37. Dietzel, C., Clarke, K.: The effect of disaggregating land use categories in cellular automata during model calibration and forecasting. Computers, Environment and Urban Systems 30 (2006) 78-101