Market Impacts on Land-Use Change: An Agent-Based Experiment

Annals of the Association of American Geographers

Volumn 104, Issue 3, 2014, Pages 460-484

  Sun, Shipeng ^a   Parker, Dawn C ^b   Huang, Qingxu ^c   Filatova, Tatiana ^d   Robinson, Derek T ^b   Riolo, Rick L ^e   Hutchins, Meghan ^e   Brown, Daniel G ^e  

^a UNIVERSITY OF MINNESOTA   (United States)

^b UNIVERSITY OF WATERLOO   (Canada)

^c BEIJING NORMAL UNIVERSITY   (China)

^d UNIVERSITY OF TWENTE   (Netherlands)

^e UNIVERSITY OF MICHIGAN   (United States)

Author keywords

agent based modeling; land markets; land use change

Indexed keywords

COMPETITION (ECONOMICS); DECISION MAKING; EXPERIMENTAL STUDY; LAND MARKET; LAND USE CHANGE; MARKET SYSTEM;

NORTH AMERICA;

EID: 84899733890     PISSN: 00045608     EISSN: 14678306     Source Type: Journal    
DOI: 10.1080/00045608.2014.892338     Document Type: Article

References (98)

1. Adams, J.S. 1984. The meaning of housing in America. Annals of the Association of American Geographers 74 (4): 515-26.
2. Alonso, W. 1964. Location and land use: Toward a general theory of land rent. Cambridge, MA: Harvard University Press.
3. Anderson, S.T., and S.E. West. 2006. Open space, residential property values, and spatial context. Regional Science and Urban Economics 36 (6): 773-89.
4. Axelrod, R. 1997. Advancing the art of simulation in the social sciences. In Simulating social phenomena, ed. R. Conte, R. Hegselmann, and P. Terna, 21-40. Berlin: Springer.
5. Axtell, R. 2005. The complexity of exchange. Economic Journal 115 (504): F193-F210.
6. Batty, M., and P.A. Longley. 1986. The fractal simulation of urban structure. Environment and Planning A 18 (9): 1143-79.
7. Benenson, I. 1998. Multi-agent simulations of residential dynamics in the city. Computers, Environment and Urban Systems 22 (1): 25-42.
8. Benenson, I., and P. Torrens. 2004. Geosimulation: Object-based modeling of urban phenomena. Computers, Environment and Urban Systems 28 (1-2): 1-8.
9. Bockstael, N.E. 1996. Modeling economics and ecology: The importance of a spatial perspective. American Journal of Agricultural Economics 78 (5): 1168-80.
10. Brown, D.G., S.E. Page, R. Riolo, and W. Rand. 2004. Agent-based and analytical modeling to evaluate the effectiveness of greenbelts. Environmental Modelling & Software 19 (12): 1097-109.
11. Brown, D.G., and D.T. Robinson. 2006. Effects of heterogeneity in residential preferences on an agent-based model of urban sprawl. Ecology and Society 11 (1): 46-67.
12. Brown, D.G., D.T. Robinson, L. An, J.I. Nassauer, M. Zellner, W. Rand, R. Riolo, S.E. Page, B. Low, and Z. Wang. 2008. Exurbia from the bottom-up: Confronting empirical challenges to characterizing a complex system. Geoforum 39 (2): 805-18.
13. Capozza, D.R., and R.W. Helsley. 1989. The fundamentals of land prices and urban growth. Journal of Urban Economics 26 (3): 295-306.
14. Caruso, G., D. Peeters, J. Cavailhès, and M. Rounsevell. 2007. Spatial configurations in a periurban city: A cellular automata-based microeconomic model. Regional Science and Urban Economics 37 (5): 542-67.
15. Carver, S.J. 1991. Integrating multi-criteria evaluation with geographical information systems. International Journal of Geographical Information Systems 5 (3): 321-39.
16. Cheshire, P., and S. Sheppard. 1995. On the price of land and the value of amenities. Economica 62 (246): 247-67.
17. Crooks, A.T. 2008. Constructing and implementing an agent-based model of residential segregation through vector GIS. UCL Working Paper Series, Paper 133, University College of London, London, UK.
18. Diappi, L., and P. Bolchi. 2008. Smith's rent gap theory and local real estate dynamics: A multi-agent model. Computers, Environment and Urban Systems 32 (1): 6-18.
19. DiPasquale, D., and W.C. Wheaton. 1996. Urban economics and real estate markets. Englewood Cliffs, NJ: Prentice Hall.
20. Ettema, D. 2011. A multi-agent model of urban processes: Modelling relocation processes and price setting in housing markets. Computers, Environment and Urban Systems 35 (1): 1-11.
21. Ettema, D., K. Jong, H. Timmermans, and A. Bakema. 2007. PUMA: Multi-agent modelling of urban systems. In Modelling land-use change: Progress and applications, ed. E. Koomen, J. Stillwell, A. Bakema, and H.J. Scholten, 237-58. Dordrecht, The Netherlands: Springer.
22. Ewing, R., R. Pendall, and D. Chen. 2003. Measuring sprawl and its transportation impacts. Transportation Research Record: Journal of the Transportation Research Board 1831:175-83.
23. Feitosa, F.F., Q.B. Le, and P.L. G. Vlek. 2011. Multi-agent simulator for urban segregation (MASUS): A tool to explore alternatives for promoting inclusive cities. Computers, Environment and Urban Systems 35 (2): 104-15.
24. Filatova, T., D. Parker, and A. van der Veen. 2009. Agent-based urban land markets: Agent's pricing behavior, land prices and urban land use change. Journal of Artificial Societies and Social Simulation 12 (1): 3.
25. Filatova, T., A. van der Veen, and D. Parker. 2008. Introducing preference heterogeneity into a monocentric urban model: An agent-Based land market model. Paper presented at Second World Congress on Social Simulation, Fairfax, VA.
26. Filatova T. van der Veen A. Parker D. 2009. Land market interactions between heterogeneous agents in a heterogeneous landscape: Tracing the macro-scale effects of individual trade-offs between environmental amenities and disamenities. Canadian Journal of Agricultural Economics 57 (4): 431-57.
27. Filatova, T., A. Voinov, and A. van der Veen. 2011. Land market mechanisms for preservation of space for coastal ecosystems: An agent-based analysis. Environmental Modelling and Software 26 (2): 179-90.
28. Fossett, M. 2006. Ethnic preferences, social distance dynamics, and residential segregation: Theoretical explorations using simulation analysis. The Journal of Mathematical Sociology 30 (3): 185-273.
29. Fossett, M., and D.R. Dietrich. 2009. Effects of city size, shape, and form, and neighborhood size and shape in agent-based models of residential segregation: Are Schelling-style preference effects robust? Environment and Planning B: Planning and Design 36 (1): 149-69.
30. Fujita, M., and J.-F. Thisse. 2002. Economics of agglomeration: Cities, industrial location, and regional growth. Cambridge, UK and New York: Cambridge University Press.
31. Galster, G., R. Hanson, M.R. Ratcliffe, H. Wolman, S. Coleman, and J. Freihage. 2001. Wrestling sprawl to the ground: Defining and measuring an elusive concept. Housing Policy Debate 12 (4): 681-717.
32. Geoghegan, J. 2002. The value of open spaces in residential land use. Land Use Policy 19 (1): 91-98.
33. Goodman, A.C., and T.G. Thibodeau. 2003. Housing market segmentation and hedonic prediction accuracy. Journal of Housing Economics 12 (3): 181-201.
34. Grevers, W. 2007. Land markets and public policy. Enschede, The Netherlands: University of Twente.
35. He, H., B. DeZonia, and D. Mladenoff. 2000. An aggregation index (AI) to quantify spatial patterns of landscapes. Landscape Ecology 15 (7): 591-601.
36. Helbich, M., W. Brunauer, J. Hagenauer, and M. Leitner. 2013. Data-driven regionalization of housing markets. Annals of the Association of American Geographers 103 (4): 871-89.
37. Henderson, J.V., and J.-F. Thisse. 1999. On the pricing strategy of a land developer. Journal of Urban Economics 45:1-16.
38. Huang, Q., D.C. Parker, T. Filatova, and S. Sun. Forthcoming. A review of urban residential choice models using agent-based modeling. Environment and Planning B: Planning & Design.
39. Irwin, E.G. 2010. New directions for urban economic models of land use change: Incorporating spatial dynamics and heterogeneity. Journal of Regional Science 50 (1): 65-91.
40. Irwin, E.G., and N.E. Bockstael. 2002. Interacting agents, spatial externalities and the evolution of residential land use patterns. Journal of Economic Geography 2 (1): 31-54.
41. Irwin, E., and J. Geoghegan. 2001. Theory, data, methods: Developing spatially explicit economic models of land use change. Agriculture, Ecosystems, and Environment 85:7-23.
42. Jackson, J., B. Forest, and R. Sengupta. 2008. Agent-based simulation of urban residential dynamics and land rent change in a gentrifying area of Boston. Transactions in GIS 12 (4): 475-91.
43. Jayaprakash, C., K. Warren, E. Irwin, and K. Chen. 2009. The interaction of segregation and suburbanization in an agent-based model of residential location. Environment and Planning B: Planning and Design 36 (6): 989-1007.
44. Kii, M., and K. Doi. 2005. Multiagent land-use and transport model for the policy evaluation of a compact city. Environment and Planning B: Planning and Design 32 (4): 485-504.
45. Koomen, E., J. Stillwell, A. Bakema, H. Scholten, W. Loibl, T. Tötzer, M. Köstl, and K. Steinnocher. 2007. Simulation of polycentric urban growth dynamics through agents: Model concept, application, results and validation. In Modelling land-use change: Progress and applications, 219-35. Dordrecht, The Netherlands: Springer.
46. Lambin, E.F., B.L. Turner, H.J. Geist, S.B. Agbola, A. Angelsen, J.W. Bruce, O.T. Coomes, et al. 2001. The causes of land-use and land-cover change: Moving beyond the myths. Global Environmental Change 11 (4): 261-69.
47. Li, X., and X. Liu. 2007. Defining agents' behaviors to simulate complex residential development using multicriteria evaluation. Journal of Environmental Management 85 (4): 1063-75.
48. Ligmann-Zielinska, A. 2009. The impact of risk-taking attitudes on a land use pattern: An agent-based model of residential development. Journal of Land Use Science 4 (4): 215-32.
49. Ligmann-Zielinska, A., and P. Jankowski. 2010. Exploring normative scenarios of land use development decisions with an agent-based simulation laboratory. Computers, Environment and Urban Systems 34:409-23.
50. Loibl, W., and T. Toetzer. 2003. Modeling growth and densification processes in suburban regions-Simulation of landscape transition with spatial agents. Environmental Modelling & Software 18 (6): 553-63.
51. Lubowski, R.N., A.J. Plantinga, and R.N. Stavins. 2006. Land-use change and carbon sinks: Econometric estimation of the carbon sequestration supply function. Journal of Environmental Economics and Management 51 (2): 135-52.
52. Lubowski R.N. Plantinga A.J. Stavins R.N. 2008. What drives land-use change in the United States? A national analysis of landowner decisions. Land Economics 84 (4): 529-50.
53. Magliocca, N., E. Safirova, V. McConnell, and M. Walls. 2011. An economic agent-based model of coupled housing and land markets (CHALMS). Computers, Environment and Urban Systems 35 (3): 183-91.
54. Manson, S.M. 2003. Validation and verification of multi-agent models for ecosystem management. In Complexity and ecosystem management: The theory and practice of multi-agent approaches, ed. M. Janssen, 63-74. Northampton, MA: Edward Elgar.
55. Manson S.M. 2005. Agent-based modeling and genetic programming for modeling land change in the southern Yucatán peninsular region of Mexico. Agriculture, Ecosystems & Environment 111 (1-4): 47-62.
56. Manson S.M. 2006. Land use in the southern Yucatán peninsular region of Mexico: Scenarios of population and institutional change. Computers, Environment and Urban Systems 30 (3): 230-53.
57. Manson S.M. 2007. Challenges in evaluating models of geographic complexity. Environment and Planning B: Planning and Design 34 (2): 245-60.
58. Manson, S.M., and D. O'Sullivan. 2006. Complexity theory in the study of space and place. Environment and Planning A 38 (4): 677-92.
59. Manson, S.M., S. Sun, and D. Bonsal. 2012. Agent-based modeling and complexity. In Agent-based models of geographical systems, ed. A.J. Heppenstall, A.T. Crooks, L.M. See, and M. Batty, 125-39: Dordrecht, The Netherlands: Springer.
60. McGarigal, K., S.A. Cushman, M.C. Neel, and E. Ene. 2002. FRAGSTATS: Spatial pattern analysis program for categorical maps. Amherst, MA: University of Massachusetts, Amherst. http://www.umass.edu/landeco/research/fragstats/fragstats.html
61. Miller, E., J.D. Hunt, J.E. Abraham, and P.A. Salvini. 2004. Microsimulating urban systems. Computers, Environment, and Urban Systems 28:9-44.
62. Miller E. Hunt J.D. Abraham J.E. Salvini P.A. 2008. Microsimulating urban systems. Computers, Environment and Urban Systems 28 (1-2): 9-44.
63. Nelson, E., S. Polasky, D.J. Lewis, A.J. Plantingall, E. Lonsdorf, D. White, D. Bael, and J.J. Lawler. 2008. Efficiency of incentives to jointly increase carbon sequestration and species conservation on a landscape. Proceedings of the National Academy of Sciences of the United States of America 105 (28): 9471-76.
64. Omer, I. 2005. How ethnicity influences residential distributions: An agent-based simulation. Environment and Planning B: Planning and Design 32 (5): 657-72.
65. O'Neill, R.V., J.R. Krummel, R.H. Gardner, G. Sugihara, B. Jackson, D.L. DeAngelis, B.T. Milne, et al. 1988. Indices of landscape pattern. Landscape Ecology 1 (3): 153-62.
66. O'Sullivan, D. 2002. Toward micro-scale spatial modeling of gentrification. Journal of Geographical Systems 4 (3): 251-74.
67. O'Sullivan, D., J. MacGill, and C. Yu. 2003. Agent-based residential segregation: A hierarchically structured spatial model. Paper presented at Agent 2003 conference on challenges in social simulation, University of Chicago, Chicago, IL.
68. Otter, H.S., A. van der Veen, and H.J. de Vriend. 2001. ABLOoM: Location behaviour, spatial patterns, and agent-based modelling. Journal of Artificial Societies and Social Simulation 4 (4). http://jasss.soc.surrey.ac.uk/4/4/2.html
69. Parker, D.C. Forthcoming. An economic perspective on agent-based models of land-use and land-cover change. In The Oxford handbook of land economics, ed. J.M. Duke and J. Wu. New York: Oxford University Press.
70. Parker, D.C., D.G. Brown, T. Filatova, R. Riolo, D.T. Robinson, and S. Sun. 2012. Do land markets matter? A modeling ontology and experimental design to test the effects of land markets for an agent-based model of ex-urban residential land-use change. In Agent-based models of geographical systems, ed. A.J. Heppenstall, A.T. Crooks, L.M. See, and M. Batty, 525-42. Dordrecht, The Netherlands: Springer.
71. Parker, D., and T. Filatova. 2008. A theoretical design for a bilateral agent-based land market with heterogeneous economic agents. Computers, Environment, and Urban Systems 32 (6): 454-63.
72. Parker, D.C., S.M. Manson, M.A. Janssen, M.J. Hoffmann, and P. Deadman. 2003. Multi-agent systems for the simulation of land-use and land-cover change: A review. Annals of the Association of American Geographers 93 (2): 314-37.
73. Parker, D.C., and V. Meretsky. 2004. Measuring pattern outcomes in an agent-based model of edge-effect externalities using spatial metrics. Agriculture, Ecosystems & Environment 101 (2-3): 233-50.
74. Parker, D.C., S. Sun, T. Filatova, N. Magliocca, Q. Huang, D.G. Brown, and R. Riolo. 2012. The implications of alternative developer decision-making strategies on land-use and land-cover in an agent-based land market model. Paper presented at the Sixth Biennial Meeting of International Congress on Environmental Modelling and Software, Leipzig, Germany.
75. Plantinga, A.J., R.N. Lubowski, and R.N. Stavins. 2002. The effects of potential land development on agricultural land prices. Journal of Urban Economics 52 (3): 561-81.
76. Randall, A., and E.N. Castle. 1985. Land resources and land markets. In Handbook of natural resources and energy economics: Vol. II, ed. A.V. Kneese and J.L. S. Sweeney, 571-619. Amsterdam: Elsevier.
77. Ripple, W.J., G.A. Bradshaw, and T.A. Spies. 1991. Measuring forest landscape patterns in the cascade range of Oregon, USA. Biological Conservation 57 (1): 73-88.
78. Robinson, D.T., and D.G. Brown. 2009. Evaluating the effects of land-use development policies on ex-urban forest cover: An integrated agent-based GIS approach. International Journal of Geographical Information Science 23 (9): 1211-32.
79. Robinson, D.T., S. Sun, M. Hutchins, R.L. Riolo, D.G. Brown, D.C. Parker, T. Filatova, W.S. Currie, and S. Kiger. 2013. Effects of land markets and land management on ecosystem function: A framework for modelling exurban land-change. Environmental Modelling & Software 45 (10): 129-40.
80. Sasaki, Y., and P. Box. 2003. Agent-based verification of von Thünen's location theory. Journal of Artificial Societies and Social Simulation 6 (2). http://jasss.soc.surrey.ac.uk/6/2/9.html
81. Saura, S., and J. Martinez-Millan. 2001. Sensitivity of landscape pattern metrics to map spatial extent. Photogrammetric Engineering and Remote Sensing 67 (9): 1027-36.
82. Store, R., and J. Kangas. 2001. Integrating spatial multi-criteria evaluation and expert knowledge for GIS-based habitat suitability modelling. Landscape and Urban Planning 55 (2): 79-93.
83. Sun, S., and S. Manson. 2012. Intraurban migration, neighborhoods, and city structure. Urban Geography 33 (7): 1008-29.
84. Tesfatsion, L. 2006. Agent-based computational economics: A constructive approach to economic theory. In Handbook of computational economics: Vol. 2: Agent-based computational economics, ed. L. Tesfatsion and K.L. Judd, 831-80. Amsterdam: Elsevier.
85. Torrens, P.M. 2006. Simulating sprawl. Annals of the Association of American Geographers 96 (2): 248-75.
86. Torrens P.M. 2007. A geographic automata model of residential mobility. Environment and Planning B: Planning and Design 34 (2): 200-22.
87. Torrens P.M. 2008. A toolkit for measuring sprawl. Applied Spatial Analysis and Policy 1 (1): 5-36.
88. Torrens, P.M., and I. Benenson. 2005. Geographic automata systems. International Journal of Geographical Information Science 19 (4): 385-412.
89. Veldkamp, A., and E.F. Lambin. 2001. Predicting land-use change. Agriculture, Ecosystems & Environment 85 (1): 1-6.
90. Verburg, P.H., A. Veldkamp, L. Willemen, K.P. Overmars, and J.C. Castella. 2004. Landscape level analysis of the spatial and temporal complexity of land-use change. Ecosystems and Land Use: Geophysical Monograph Series 153:217-30.
91. Waddell, P. 2002. UrbanSim: Modeling urban development for land use, transportation and environmental planning. Journal of the American Planning Association 68 (3): 297-314.
92. Wagner, P., and M. Wegener. 2007. Urban land use, transport and environment models: Experiences with an integrated microscopic approach. disP 170 (3): 45-56.
93. Weiss, M.A. 2002. The rise of the community builders: The American real estate industry and urban land planning. Washington, DC: Beard Books.
94. White, R., and G. Engelen. 1993. Cellular automata and fractal urban form: A cellular modelling approach to the evolution of urban land-use patterns. Environment and Planning A 25 (8): 1175-99.
95. Wu, J. 2004. Effects of changing scale on landscape pattern analysis: Scaling relations. Landscape Ecology 19 (2): 125-38.
96. Wu J. 2010. Economic fundamentals and urban-suburban disparities. Journal of Regional Science 50 (2): 570-91.
97. Wu, J., and A.J. Plantinga. 2003. The influence of public open space on urban spatial structure. Journal of Environmental Economics and Management 46 (2): 288-309.
98. Xie, Y., M. Batty, and K. Zhao. 2007. Simulating emergent urban form using agent-based modeling: Desakota in the Suzhou-Wuxian region in China. Annals of the Association of American Geographers 97 (3): 477-95.