An object-based cellular automata model to mitigate scale dependency

Lecture Notes in Geoinformation and Cartography

Volumn 0, Issue 9783540770572, 2008, Pages 43-73

  Marceau, D J ^a   Moreno, N ^a,b  

^a UNIVERSITY OF CALGARY   (Canada)

^b UNIVERSIDAD DE LOS ANDES   (Venezuela)

Author keywords

Land use change; Raster based cellular automata model; Scale dependency; Vector based raster based cellular automata model

Indexed keywords

CELLULAR AUTOMATA; LAND USE; MATHEMATICAL TRANSFORMATIONS; VECTOR SPACES;

CELLULAR AUTOMATA MODELING; GEOMETRIC TRANSFORMATIONS; LAND-USE CHANGE; REALISTIC SIMULATION; SCALE DEPENDENCY; SPATIAL CONFIGURATION; SPATIAL STRUCTURE; VECTOR STRUCTURES;

ROBOTS;

EID: 84940464506     PISSN: 18632246     EISSN: 18632351     Source Type: Book Series    
DOI: 10.1007/978-3-540-77058-9_3     Document Type: Article

References (103)

1. Ahern, F.J., D.N.N. Horler, J. Cihlar, W.J. Bennett, and E. MacAulay. 1983. “Digital Processing to Improve Classification Results at Resolutions of 5 to 50 Meters”. In Proceedings of the SPIE Symposium on Techniques for Extraction from Remotely Sensed Images, Rochester, NY, 16-19. August, pp. 153-170.
2. Allen, T.F.H., and T.B. Starr. 1982. Hierarchy Perspective for Ecological Complexity. University of Chicago Press, Chicago.
3. Almeida, C. M. d., M. Batty, A.M.V. Monteiro, G. Câmara, B.S. Soares-Filho, G.C. Cerqueira, and C.L. Pennachin. 2003. “Stochastic cellular automata modeling of urban land use dynamics: empirical development and estimation”, Computers, Environment and Urban Systems, Vol. 27, pp. 481-509.
4. Bach, L. 1981. “The Problem of Aggregation and Distance for Analysis of Accessibility and access Opportunity in Location-Allocation Models”, Environment and Planning A, Vol. 13, pp. 955-978.
5. Band, L. E. and I. D. Moore. 1995. “Scale: landscape attributes and geographical information systems”, Hydrological Processes, Vol. 9, pp. 401-422.
6. Batty, M., Y. Xie, and A. Sun. 1999. “Modeling urban dynamics through GISbased cellular automata”, Computers, Environment and Urban Systems, Vol. 23, pp. 205-233.
7. Benenson, I., and P.M. Torrens. 2004. “Geosimulation: object-based modeling of urban phenomena”, Computers, Environment and Urban Systems, Vol. 28, pp. 1-8.
8. Benson, B.J., and M.D. McKenzie. 1995. “Effects of Sensor Spatial Resolution on Landscape Structure Parameters”, Landscape Ecology, Vol. 10, No. 2, pp. 113-120.
9. Bian, L., and S.J. Walsh. 1993. “Scale Dependencies of Vegetation and Topography in a Mountainous Environment of Montana”, The Professional Geographer, Vol. 45, No. 1, pp. 1-11.
10. Bruneau, P., C. Gascuel-Odoux, P. Robin, Ph. Merot, and K. Beven. 1995. “Sensitivity to Space and Time Resolution of a Hydrological Model Using Digital Elevation Data”, Hydrological Processes, Vol. 9, pp. 69-81.
11. Cao, C., and N.S.-N. Lam. 1997. “Understanding the Scale and Resolution Effects in Remote Sensing and GIS”. In Scale in Remote Sensing in GIS, Quattrochi, D.A. and M.F. Goodchild, eds., pp. 57-72.
12. Chang, K. T. and B. W. Tsai. 1991. “The effect of DEM resolution on slope and aspect mapping”, Cartography and Geographic Information Science, Vol. 18, No. 1, pp. 69-77.
13. Chen, Q., and A.E. Mynett. 2003. “Effects of cell size and configuration in cellular automata based prey-predator modeling”, Simulation Modeling Practice and Theory, Vol. 11, pp. 609-625.
14. Clarke, W.A.V., and K.L. Avery. 1976. “The Effects of Data Aggregation in Statistical Analysis”, Geographical Analysis, Vol. 28, pp. 428-438.
15. Cushnie, J.L. 1987. “The Interactive Effect of Spatial Resolution and Degree of Internal Variability within Land-Cover Types on Classification Accuracies”, International Journal of Remote Sensing, Vol. 8, No. 1, pp.15-29.
16. Daubechies, I. 1988. “Orthonormal bases of compactly supported wavelets”, Communications on Pure and Applied Mathematics, Vol. 41, pp. 906-966.
17. Dietzel, C., and K. Clarke, K. 2006. “The effect of disaggregating land use categories in cellular automata during model calibration and forecasting”, Computers, Environment and Urban Systems, Vol. 30, No. 1, pp. 78-101.
18. Donoho, D.L., and X. Huo. 2000. “Beamlets and multiscale image analysis”, In Lecture Notes in computational Science and Engineering: Multiscale and Multiresolution Methods, Springer, pp. 149-196.
19. Durieux, L., J. Kropacek, G.D. De Grandi and F. Achard. 2006. “Object-oriented wavelet multi-resolution image analysis of the Siberia GBFM radar mosaic combined with MERIS imagery for continental scale land cover mapping”. First International Conference on Object-Based Image Analysis (OBIA 2006), Salzburg University, Austria, July 4-5.
20. ESRI. (2005). "ArcGIS 9. Desktop GIS. ."
21. Favier, C., J. Chave, A. Fabing, D. Schwartz, and M.A. Dubois. 2004. “Modelling forest-savanna mosaic dynamics in man-influenced environments: effects of fire, climate and soil heterogeneity”, Ecological Modelling, Vol. 171, pp. 85-102.
22. Flache, A., and R. Hegselmann. 2001. “Do irregular grids make a difference? Relaxing the spatial regularity assumption in cellular models of social dynamics”, Journal of Artificial Societies and Social Simulation, Vol. 4, No. 4, http://jasss.soc.surrey.ac.uk/4/4/6.html.
23. Fotheringham, A.S. 1989. “Scale-Independent Spatial Analysis”, In Accuracy of Spatial Databases, Goodchild, M., S. Gopal, Eds, Taylor and Francis, pp. 221-228.
24. Fotheringham, A.S., and D.W.S. Wong. 1991. “TheModifiable Areal Unit Problem in Multivariate Statistical Analysis”, Environment and Planning A, Vol. 23, pp.1025-1044.
25. Friedl, M.A. 1997. “Examining the Effects of Sensor Resolution and Sub-pixel Heterogeneity on Spectral Vegetation Index: Implications for Biophysical Modeling”, In Scale in Remote Sensing in GIS, Quattrochi, D.A. and M.F. Goodchild, eds., pp.113-139.
26. Friedl, M.A. 1997. “Examining the Effects of Sensor Resolution and Sub-Pixel Heterogeneity on Spectral Vegetation Indices: Implication for Biophysical Modeling”. In Scale in Remote Sensing in GIS, Quattrochi, D.A. and M.F. Goodchild, eds., pp. 113-139.
27. Frihida, A., D.J. Marceau, and M. Thériault. 2002. “Spatio-temporal objectoriented data model for disaggregate travel behaviour”, Transactions in GIS, Vol. 6, No. 3, pp. 277-294.
28. Gao, J. 1997. “Resolution and accuracy of terrain representation by grid DEMs at a micro-scale”, International Journal of Geographical Information Science, Vol. 11, No. 2, pp. 199-212.
29. Gehlke, C.E., and K. Biehl. 1934. “Certain Effects of Grouping Upon the size of the Correlation Coefficient in Census Tract Material”, Journal of American Statistical Association Supplement, Vol. 29, pp. 169-170.
30. Grimm, V. 1999. “Ten years of individual-based modelling in ecology: what have we learned and what could we learn in the future”, Ecological Modelling, Vol. 115, pp. 129-148.
31. Hall, O. and G. Hay. 2003. “A multiscale object-specific approach to digital change detection”, International Journal of Applied Earth Observations and Geoinformation, Vol. 4, pp. 311-327.
32. Hay, G. and G. Castilla. 2006. “Object-based image analysis: strengths, weaknesses, opportunities and threats (SWOT)”. First International Conference on Object-Based Image Analysis (OBIA 2006), Salzburg University, Austria, July 4-5.
33. Hay, G.J. and D.J. Marceau. 2004. “Multiscale object-specific analysis (MOSA): An integrative approach for multiscale analysis”. In: Remote Sensing Image Analysis: Including the Spatial Domain, S. de Jong and F. van der Meer, eds, Kluwer Academic Publishers, pp. 71-92.
34. Hay, G., G. Castilla, M. Wulder and J. R. Ruiz. 2005. “An automated object-based approach for the multiscale image segmentation of forest scenes”, International Journal of Applied Earth Observations and Geoinformation, Vol. 7, pp. 339-359.
35. Hay, G.J., P. Dubé, A. Bouchard, and D.J. Marceau. 2002. “A Scale-Space Primer for Exploring and quantifying Complex Landscape”, Ecological Modelling, Vol. 153, Nos. 1/1, pp. 27-49.
36. Hu, S., and D. Li. 2004. “Vector Cellular Automata Based Geographical Entity”, 12th International Conference on Geoinformatics-Geoespatial Information Research: Bridging the Pacific and Atlantic., University of Gävle, Sweden.
37. Hunt, L., and B. Boots. 1996. “MAUP Effects in the Principal Axis Factoring Technique”, Geographical Systems, Vol. 3, pp. 101-121.
38. Irons, J.R., B.L. Markham, R.F. Nelson, D.L. Toll, D.L. Williams, R.S. Latty, and M.L. Stauffer. 1985. “The Effects of Spatial Resolution on the Classification of Thematic Mapper Data”, International Journal of Remote Sensing, Vol. 6, No. 8, pp. 1385-1403.
39. Jantz, C. A., and S.J. Goetz. 2005. “Analysis of scale dependencies in an urban land-use-change model”, International Journal of Geographical Information Science, Vol. 19, No. 2, pp. 217-241.
40. Jarvis, P.G. 1995. “Scaling Processes and Problems”, Plant, Cell and Environment, Vol. 18, pp. 1079-1089.
41. Jenerette, G. D., and J. Wu. 2001. “Analysis and simulation of land-use change in the central Arizona-Phoenix region, USA”, Landscape Ecology, Vol. 16, pp. 611-626.
42. Kershaw, K.A. 1957. “The Use of Cover and Frequency in the Detection of Pattern in Plant Communities”, Ecology, Vol. 38, pp. 291-299.
43. Kim, M. and M. Madden. 2006. “Determination of optimal scale parameter for alliance-level forest classification of multispectral IKONOS images”. First International Conference on Object-Based Image Analysis (OBIA 2006). Salzburg University, Austria, July 4-5.
44. Klinger, A. 1971. “Pattern and search statistics”. In Optimizing Methods in Statistics, J.S. Rustagi, eds., Academic Press, pp. 303-339.
45. Klinger, A. and C.R. Dyer. 1976. “Experiments in picture representation using regular decomposition”, Computer Graphics Image Processing, Vol. 5, pp. 65-105.
46. Kocabas, V., and S. Dragicevic. 2006. “Assessing cellular automata model behavior using a sensitivity analysis approach”, Computers, Environment and Urban Systems, Vol. 30, No. 6, pp. 921-953.
47. Kok, K. and A. Veldkamp. 2001. “Evaluating impact of spatial scales on land use pattern analysis in Central America”, Agriculture, Ecosystems and Environment, Vol. 85, pp. 205-221.
48. Latty, R.S. and R.M. Hoffer. 1981. “Computer-Based Classification Accuracy Due to the Spatial Resolution Using Per-Point versus Per-Field Classification Techniques”. Symposium of Machine Processing of Remotely Sensed Data, pp. 384-392.
49. Lau, K. H., and B.H. Kam. 2005. “A cellular automata model for urban land-use simulation”, Environment and Planning B: Planning and Design, Vol. 32, pp. 247-263.
50. Li, H. and F. Reynolds. 1997. “Modeling effects of spatial pattern, drought, and grazing on rates of rangeland degradation: a combined Markov and cellular automaton approach”. Scale in Remote Sensing and GIS. D. Quattrochi and M. F. Goodchild, eds, CRC Press, pp. 211-230.
51. Li, X., and A. G.-o. Yeh. 2000. “Modelling sustainable urban development by the integration of constrained cellular automata and GIS”, International Journal of Geographical Information Science, Vol. 14, pp. 131-152.
52. Li, X., and A. G.-o. Yeh. 2002. “Neural-network-based cellular automata for simulating multiple land use changes using GIS”, International Journal of Geographical Information Science, Vol. 16, No. 4, pp. 323-343.
53. Lindeberg, T. 1994. “Scale-space theory: A basic tool for analyzing structures at different scales”, Journal of Applied Statistics, Vol. 21, No. 2, pp. 225-270.
54. Makin, J., R. G. Healey, and S. Dowers. 1997. “Simulation modelling with objectoriented GIS: a prototype application to the time geography of shopping behaviour”, Geographical Systems, Vol. 4, No. 4, pp. 397-429.
55. Mandelbrot, B.B. 1967. “The Fractal geometry of nature”, Science, Vol. 156, pp. 636-642.
56. Marceau, D.J., 2007. “What can be learned from multi-agent systems?”, In: Monitoring, Simulation and Management of Visitor Landscapes, R. Gimblett, ed., University of Arizona Press. (submitted).
57. Marceau, D.J. 1992. The Problem of Scale and Spatial Aggregation in Remote Sensing: An Empirical Investigation Using Forestry Data. Unpublished Ph.D. Thesis, Department of Geography, University of Waterloo, 180 p.
58. Marceau, D.J., 1999. “The Scale Issue in the Social and Natural Sciences”. Canadian Journal of Remote Sensing, Vol. 25, No. 4, pp. 347-356.
59. Marceau, D.J., and G.J. Hay, 1999. “Remote sensing contributions to the scale issue”, Canadian Journal of Remote Sensing, Vol. 25, No. 4, pp. 357-366.
60. Marceau, D.J., D.J. Gratton, r. Fournier, and J.P. Fortin. 1994. “Remote Sensing and the Measurement of Geographical Entities in a Forested Environment; Part 2: The Optimal Spatial Resolution”, Remote Sensing and Environment, Vol. 49, No. 2, pp. 105-117.
61. Marceau, D.J., P.J. Howarth, D.J. Gratton. 1994. “Remote Sensing and the Measurement of Geographical Entities in a Forested Environment; Part 1: The Scale and Spatial Aggregation Problem”, Remote Sensing and Environment, Vol. 49, No. 2, pp. 93-104.
62. Markham, B.L., and J.R.G. Townshend. 1981. “Land Cover Classification Accuracy as a Function of Sensor Spatial Resolution”. Proceedings of the Fifteenth International Symposium on Remote Sensing of Environment, Ann Arbor, Michigan, pp. 1075-1090.
63. McCarthy, H.H., J.C. Hook, and D.S. Knos. 1956. The Measurement of Association in Industrial Geography. Department of Geography, State University of Iowa, Iowa City.
64. McGarigal, K., B. Marks, E. Ene, and C. Holmes. 1995. “Fragstats”. University of Massachusetts. http://www.umass.edu/landeco/research/fragstats/fragstats.html.
65. McNulty, S.G., J.M. Vose, and W.T. Swank. 1997. “Scaling Predicted Pine Forest Hydrology and Productivity Across the Southern United States”. In Scale in Remote Sensing in GIS, Quattrochi, D.A. and M.F. Goodchild, eds., pp. 187-209.
66. Meetemeyer, V., and E.O. Box. 1987. “Scale Effects in Landscape Studies”. In Landscape Heterogeneity and Disturbance, M.G. Turner, ed., Springer-Verlag, pp. 15-34.
67. Meetemeyer. V. 1989. “Geographical Perspectives of Space, Time, and Scale”, Landscape Ecology, Vol. 3, Nos. 3/4, pp. 163-173.
68. Ménard, A., and D.J. Marceau. 2005. “Exploration of spatial scale sensitivity in geographic cellular automata”, Environment and Planning B: Planning and Design, Vol. 32, pp. 693-714.
69. Ménard, A., and D.J. Marceau. 2007. “Simulating the impact of forest management scenarios in an agricultural landscape of southern Quebec, Canada, using a geographic cellular automata”, Landscape and Urban Planning, Vol. 79, Nos. 3/4, pp. 253-265.
70. Moody, A., and C.E. Woodcock. 1995. “The Influence of Scale and the Spatial Characteristics of Landscapes on Land-Cover Mapping Using Remote Sensing”, Landscape Ecology, Vol. 10, No. 6, pp. 363-379.
71. Moreno, N. and D.J. Marceau, 2006. “A vector-based cellular automata model to allow changes of polygon shape”, In Proceedings of The 2006 SCS International Conference on Modeling and Simulation-Methodology, Tools, Software Applications, R. Huntsinger, H. Vakilzadian and T. Ören, eds, July 31-August 2, 2006, Calgary, Canada, pp. 85-92.
72. Moreno, N. and D.J. Marceau, 2007. “Modeling land-use changes using a novel vector-based cellular automata model”, In Proceedings of the 18th IASTED International Conference on Modelling and Simulation, May 30-June 1, 2007, Montreal, Quebec.
73. O’Neill, R.V., D.L. De Angelis, J.B. Waide, and T.F.H. Allen. 1986. A Hierarchical Concept of Ecosystems. Princeton University Press, Princeton, New Jersey.
74. Openshaw, S. 1977. “A Geographical Solution to Scale and Aggregation Problems in Region-Building, Partitioning and Spatial Modelling”, Institute of British Geographers, Transactions, New Series, Vol. 2, pp. 459-472.
75. Openshaw, S. 1978. “An Empirical Study of Some Zone-Design Criteria”, Environment and Planning A, Vol. 10, pp.781-794.
76. Openshaw, S. 1984. The Modifiable Areal Unit Problem. Concepts and Techniques in Modern Geography (CATMOG), no. 38.
77. Parrott, L. and R. Kok. 2000. “Incorporating complexity in ecosystem modeling”, Complexity International, Vol. 7, pp. 1-19.
78. Platt, T., and K.L. Denman. 1975. “Spectral analysis in ecology”, Annals of Rev. Ecological System, Vol. 6, pp. 189-210.
79. Putman, S.H., and S.-H. Chung. 1989. “Effects of Spatial System Design on Spatial Interaction Models, 1: The Spatial System Definition Problem”, Environment and Planning A, Vol. 21, pp. 27-46.
80. Qi, Y., and J. Wu. 1996. “Effects of Changing Spatial Resolution on the Results of Landscape Pattern Analysis Using Spatial Autocorrelation Indices”, Landscape Ecology, Vol. 11, pp. 39-49.
81. Rietkerk, M., S.C. Dekker, P.C.D. Ruiter, and J.V.D Koppel. 2004. “Self-Organized Patchiness and Catastrophic Shifts in Ecosystems”, Review, Vol. 305, pp. 1926-1929.
82. Sadowski, F.G., W.A. Malila, J.E. Sarno, and R.F. Nalepka. 1977. “The Influence of Multispectral Scanner Spatial Resolution on Forest Feature Classification”. Proceedings of the 11th International Symposium on Remote Sensing of Environment, 25-29. April, Ann Arbor, pp. 1279-1288.
83. Shi, W., B. Yang, and Q. Li. 2003. “An object-oriented data model for complex objects in three-dimensional geographical information systems”, International Journal of Geographical Information Science, Vol. 17, No. 5, pp. 411-430.
84. Shi, W., and M.Y.C. Pang. 2000. “Development of Voronoi-based cellular automata-an integrated dynamic model for Geographical Information Systems”, International Journal of Geographical Information Science, Vol. 14, No. 5, pp. 455-474.
85. Soucy-Gonthier, N., Marceau, D., Delage, M., Cogliastro, A., Domon, G., and Bouchard, A. (2003). "Détection de l’évolution des superficies forestières en Montérégie entre juin 1999 et août 2002 à partir d’images satellitaires Landsat TM." Agence forestière de la Montérégie.
86. Stevens, D., S. Dragicevic, S., and K. Rothley. 2007. “iCity: A GIS-CA modelling tool for urban planning and decision making”, Environmental Modelling & Software, Vol. 22, pp. 761-773.
87. Straatman, B., R. White, and G. Engelen. 2004. “Towards an automatic calibration procedure for constrained cellular automata”, Computers, Environment and Urban Systems, Vol. 28, pp. 149-170.
88. Torrens, P. and D. O’Sullivan. 2001. “Cellular automata and urban simulation: where do we go from here?”, Environment and Planning B, Vol. 28, pp. 163-168.
89. Turner, D.P., R. Dodson, and D. Marks. 1996. “Comparison of Alternative Spatial Resolutions in the Application of a Spatially Distributed Biogeochemical Model over Complex Terrain”, Ecological Modeling, Vol. 90. pp. 53-67.
90. Turner, M.G., R.V. O’Neil, R.H. Gardner, and B.T. Milne. 1989. “Effects of Changing spatial Scale on the analysis of Landscape Pattern”, Landscape Ecology, Vol. 3, pp. 153-162.
91. Usher, M.B. 1969. “The Relation Between Mean Square and Block Size in the Analysis of Similar Patterns”, Journal of Ecology, Vol. 57, pp. 505-514.
92. Visvalingam, M. 1991. “Areal Units and the Linking of Data: Some Conceptual Issues”, In Spatial Analysis and Spatial Policy Using Geographic Information Systems, L. Worrall, ed., Belhaven Press, pp. 12-37.
93. Wachowicz, M. 1999. Object-oriented design for temporal GIS, Taylor and Francis. Walsh, S.J. A.
94. Moody, T.R. Allen, and D.G. Brown. 1997. “Scale Dependence of NDVI and its Relationship to Mountains Terrain”. In Scale in Remote Sensing in GIS, Quattrochi, D.A. and M.F. Goodchild, eds., pp. 27-55.
95. White, R., and G. Engelen. 2000. “High-resolution integrated modelling of the spatial dynamics of urban and regional systems”, Computers, Environment and Urban Systems, Vol. 24, pp. 383-400.
96. White, R., G. Engelen, and I. Uljee. 2000. “Modelling land use change with linked cellular automata and socio-economic models: a tool for exploring the impact of climate change on the island of St Lucia”. In Spatial Information for Land Use Management, M.J. Hill, and R.J. Aspinall, eds., pp. 189-204.
97. Wiens, J.A. 1989. “Spatial Scaling in Ecology”, Functional Ecology, Vol. 3, pp. 385-397.
98. Wolfram, S. 1984. “Cellular automata as models of complexity”, Nature, Vol. 311, pp. 419-424.
99. Wu, 2004
100. Wu, F. 2002. “Calibration of stochastic cellular automata: the application to ruralurban land conversions”, International Journal of Geographical Information Science, Vol. 16, No. 8, pp. 795-818.
101. Wu J., and O.L. Loucks. 1995. “ From Balance of Nature to Hierarchical Patch Dynamics: A Paradigm Shift in Ecology”, The Quarterly Review of Biology, Vol. 70, pp. 439-466.
102. Yule, G.U., and M.G. Kendall. 1950. An Introduction to the Theory of Statistics. Griffin.
103. Zhang, X., N. A. Drake, and J. Wainwright. 2004. “Scaling issues in environmental modeling”. Environmental Modeling: Finding simplicity in complexity. J. Wainwright and M. Mulligan, eds., Wiley, pp. 319-334.