2,419
Views
176
CrossRef citations to date
0
Altmetric
Articles

Modeling urban land-use dynamics in a fast developing city using the modified logistic cellular automaton with a patch-based simulation strategy

, , &
Pages 234-255 | Received 26 Mar 2013, Accepted 01 Aug 2013, Published online: 18 Sep 2013

References

  • Brown, D.G., et al., 2005. Path dependence and the validation of agent-based spatial models of land use. International Journal of Geographical Information Science, 19 (2), 153–174.
  • Clarke, K. and Gaydos, L., 1998. Loose-coupling a cellular automaton model and GIS: long-term urban growth prediction for San Francisco and Washington/Baltimore. International Journal of Geographical Information Science, 12 (7), 699–714.
  • Definiens Developer 7.0, 2003. Definiens Developer Version 7 [online]. http://www.ecognition.com/document/definiens-developer-version-7 [Accessed 8 June 2012].
  • Dietzel, C. and Clarke, K., 2007. Toward optimal calibration of the SLEUTH land use change model. Transactions in GIS, 11 (1), 29.
  • Dietzel, C., et al., 2005. Diffusion and coalescence of the Houston Metropolitan Area: evidence supporting a new urban theory. Environment and Planning B: Planning and Design, 32 (2), 231–246.
  • Fang, S., et al., 2005. The impact of interactions in spatial simulation of the dynamics of urban sprawl. Landscape and Urban Planning, 73 (4), 294–306.
  • Fragkias, M. and Seto, K., 2009. Evolving rank-size distributions of intra-metropolitan urban clusters in South China. Computers, Environment and Urban Systems, 33 (3), 189–199.
  • García, A.M., et al., 2012. A comparative analysis of cellular automata models for simulation of small urban areas in Galicia, NW Spain. Computers, Environment and Urban Systems, 36 (4), 291–301.
  • Han, J., et al., 2009. Application of an integrated system dynamics and cellular automata model for urban growth assessment: a case study of Shanghai, China. Landscape and Urban Planning, 91 (3), 133–141.
  • Jokar Arsanjani, J., et al., 2013. Integration of logistic regression, Markov chain and cellular automata models to simulate urban expansion. International Journal of Applied Earth Observation and Geoinformation, 21, 265–275.
  • Li, X., et al., 2012. Calibrating cellular automata based on landscape metrics by using genetic algorithms. International Journal of Geographical Information Science, 27 (3), 594–613.
  • Li, X., Yang, Q.S., and Liu, X.P., 2008. Discovering and evaluating urban signatures for simulating compact development using cellular automata. Landscape and Urban Planning, 86 (2), 177–186.
  • Li, X. and Yeh, A.G., 2002. Neural-network-based cellular automata for simulating multiple land use changes using GIS. International Journal of Geographical Information Science, 16 (4), 323–343.
  • Li, X. and Yeh, A.G.O., 2000. Modelling sustainable urban development by the integration of constrained cellular automata and GIS. International Journal of Geographical Information Science, 14 (2), 131–152.
  • Li, X. and Yeh, A.G.O., 2004. Data mining of cellular automata’s transition rules. International Journal of Geographical Information Science, 18 (8), 723–744.
  • Liu, X., et al., 2012. An integrated approach of remote sensing, GIS and swarm intelligence for zoning protected ecological areas. Landscape Ecology, 27 (3), 447–463.
  • Liu, X., et al., 2008. Simulating complex urban development using kernel-based non-linear cellular automata. Ecological Modelling, 211 (1–2), 169–181.
  • Liu, X., et al., 2010. Simulating land-use dynamics under planning policies by integrating artificial immune systems with cellular automata. International Journal of Geographical Information Science, 24 (5), 783–802.
  • Ménard, A. and Marceau, D.J., 2012. Exploration of spatial scale sensitivity in geographic cellular automata. Environment and Planning B: Planning and Design, 32 (5), 693–714.
  • McGarigal, K., et al., 2012. FRAGSTATS v4: spatial pattern analysis program for categorical and continuous maps. Computer software program produced by the authors at the University of Massachusetts, Amherst. [online]. Available from: http://www.umass.edu/landeco/research/fragstats/fragstats.html [Accessed 2 February 2013].
  • Meentemeyer, R.K., et al., 2013. FUTURES: multilevel simulations of emerging urban–rural landscape structure using a stochastic patch-growing algorithm. Annals of the Association of American Geographers, 103 (4), 785–807.
  • Parker, D. and Meretsky, V., 2004. Measuring pattern outcomes in an agent-based model of edge-effect externalities using spatial metrics. Agriculture, Ecosystems & Environment, 101 (2–3), 233–250.
  • Pontius, R., et al., 2007. Accuracy assessment for a simulation model of Amazonian deforestation. Annals of the Association of American Geographers, 97 (4), 677–695.
  • Pontius, R., et al., 2008. Comparing the input, output, and validation maps for several models of land change. The Annals of Regional Science, 42 (1), 11–37.
  • Samat, N., 2006. Characterizing the scale sensitivity of the cellular automata simulated urban growth: a case study of the Seberang Perai Region, Penang State, Malaysia. Computers, Environment and Urban Systems, 30 (6), 905–920.
  • Santé, I., et al., 2010. Cellular automata models for the simulation of real-world urban processes: a review and analysis. Landscape and Urban Planning, 96 (2), 108–122.
  • Scaramuzza, P., Micijevic, E., and Chander, G., 2004. SLC gap-filled products: phase one methodology [online]. Available from: https://landsat.usgs.gov/documents/SLC_Gap_Fill_Methodology.pdf [Accessed 20 March 2013].
  • Seto, K. and Fragkias, M., 2005. Quantifying spatiotemporal patterns of urban land-use change in four cities of China with time series landscape metrics. Landscape Ecology, 20 (7), 871–888.
  • Silva, E. and Clarke, K., 2002. Calibration of the SLEUTH urban growth model for Lisbon and Porto, Portugal. Computers, Environment and Urban Systems, 26 (6), 525–552.
  • Sui, D. and Zeng, H., 2001. Modeling the dynamics of landscape structure in Asia’s emerging desakota regions: a case study in Shenzhen. Landscape and Urban Planning, 53 (1–4), 37–52.
  • USGS, 2004. Phase 2 gap-fill algorithm: SLC-off gap-filled products gap-fill algorithm methodology [online]. Available form: http://www.ga.gov.au/image_cache/GA4861.pdf [Accessed 20 March 2013].
  • Van Dessel, W., Van Rompaey, A., and Szilassi, P., 2011. Sensitivity analysis of logistic regression parameterization for land use and land cover probability estimation. International Journal of Geographical Information Science, 25 (3), 489–508.
  • White, R., 2006. Pattern based map comparisons. Journal of Geographical Systems, 8 (2), 145–164.
  • White, R. and Engelen, G., 1993. Cellular automata and fractal urban form: a cellular modelling approach to the evolution of urban land-use patterns. Environment and Planning A, 25, 1175–1175.
  • White, R. and Engelen, G., 1997. Cellular automata as the basis of integrated dynamic regional modelling. Environment and Planning B, 24, 235–246.
  • White, R., Engelen, G., and Uljee, I., 1997. The use of constrained cellular automata for high-resolution modelling of urban land-use dynamics. Environment and Planning B, 24, 323–344.
  • White, R., Uljee, I., and Engelen, G., 2012. Integrated modelling of population, employment and land-use change with a multiple activity-based variable grid cellular automaton. International Journal of Geographical Information Science, 26 (7), 1251–1280.
  • Wolfram, S., 1984. Cellular automata as models of complexity. Nature, 311 (4), 419–424.
  • Wu, F.L., 2002. Calibration of stochastic cellular automata: the application to rural-urban land conversions. International Journal of Geographical Information Science, 16 (8), 795–818.
  • Yang, Q.S., Li, X., and Shi, X., 2008. Cellular automata for simulating land use changes based on support vector machines. Computers & Geosciences, 34 (6), 592–602.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.