Skip to main content
SpringerLink
Log in

Construction of an ecological resistance surface model and its application in urban expansion simulations

  • Published:
Journal of Geographical Sciences Aims and scope Submit manuscript

Abstract

Urban expansion models are useful tools to understand urbanization process and have been given much attention. However, urban expansion is a complicated socio-economic phenomenon that is affected by complex and volatile factors involving in great uncertainties. Therefore, the accurate simulation of the urban expansion process remains challenging. In this paper, we make an attempt to solve such uncertainty through a reversal process and view urban expansion as a process wherein the urban landscape overcomes resistance from other landscapes. We developed an innovative approach derived from the minimum cumulative resistance (MCR) model that involved the introduction of a relative resistance factor for different source levels and the consideration of rigid constraints on urban expansion caused by ecological barriers. Using this approach, the urban expansion ecological resistance (UEER) model was created to describe ecological resistance surfaces suitable for simulating urban expansion and used to simulate urban expansion in Guangzhou. The study results demonstrate that the ecological resistance surface generated by the UEER model comprehensively reflects ecological resistance to urban expansion and indicates the spatial trends in urban expansion. The simulation results from the UEER-based model were more realistic and more accurately reflected ecological protection requirements than the conventional MCR-based model. These findings can enhance urban expansion simulation methods.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Adriaensen F, Chardon J P, De Blust G et al., 2003. The application of ‘least-cost’ modelling as a functional landscape model. Landscape and Urban Planning, 64: 233–247.

    Article  Google Scholar 

  • Al-Ahmadi K, See L, Heppenstall A et al., 2009. Calibration of a fuzzy cellular automata model of urban dynamics in Saudi Arabia. Ecological Complexity, 6: 80–101.

    Article  Google Scholar 

  • Barredo J I, Kasanko M, McCormick N et al., 2003. Modelling dynamic spatial processes: Simulation of urban future scenarios through cellular automata. Landscape and Urban Planning, 64: 145–160.

    Article  Google Scholar 

  • Berling-Wolff S, Wu J, 2004. Modeling urban landscape dynamics: A case study in Phoenix, USA. Urban Ecosystems, 7(3): 215–240.

    Article  Google Scholar 

  • Chardon J P, Adriaensen F, Matthysen E, 2003. Incorporating landscape elements into a connectivity measure: A case study of speckled wood butterfly. Landscape Ecology, 18: 561–573.

    Article  Google Scholar 

  • Cheng J, Masser I, 2003. Modelling urban growth patterns: A multiscale perspective. Environment and Planning A, 35: 679–704.

    Article  Google Scholar 

  • Costanza R, Ruth M, 1998. Using dynamic modeling to scope environmental problems and build consensus. Environmental Management, 22: 183–195.

    Article  Google Scholar 

  • Couclelis H, 1987. Cellular dynamics: How individual decisions lead to global urban change. European Journal of Operational Research, 30(3): 344–346.

    Article  Google Scholar 

  • Clarke K C, Hoppen S, Gaydos L, 1997. A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay area. Environment and Planning B: Planning and Design, 24: 247–261.

    Article  Google Scholar 

  • Foltête J C, Berthier K, Cosson J F, 2008. Cost distance defined by a topological function of landscape. Ecological Modelling, 210(1/2): 104–114.

    Article  Google Scholar 

  • Grimm N B, Grove J M, Pickett S T A et al., 2000. Integrated approaches to long-term studies of urban ecological systems. BioScience, 50(7): 571–584.

    Article  Google Scholar 

  • Haregeweyn N, Fikadu G, Tsunekawa A et al., 2012. The dynamics of urban expansion and its impacts on land use/land cover change and small-scale farmers living near the urban fringe: A case study of Bahir Dar, Ethiopia. Landscape and Urban Planning, 106(2): 149–157.

    Article  Google Scholar 

  • He C, Okada N, Zhang Q et al., 2006. Modeling urban expansion scenarios by coupling cellular automata model and system dynamic model in Beijing, China. Applied Geography, 26: 323–345.

    Article  Google Scholar 

  • He C, Okada N, Zhang Q et al., 2008. Modelling dynamic urban expansion processes incorporating a potential model with cellular automata. Landscape and Urban Planning, 86: 79–91.

    Article  Google Scholar 

  • Knaapen J P, Scheffer M, Harms B, 1992. Estimating hatitat isolation in landscape planning. Landscape and Urban Planning, 23: 1016.

    Article  Google Scholar 

  • Lambin E, Geist J, 2001. Global land use and land cover change: What have we learned so far? Global Change News Letter, 46: 27–30.

    Google Scholar 

  • Li L, Sato Y, Zhu H, 2003. Simulating spatial urban expansion based on a physical process. Landscape and Urban Planning, 64: 67–76.

    Article  Google Scholar 

  • Li X, 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: 131–152.

    Article  Google Scholar 

  • Li X, Yeh A G O, 2002. Neural-network-based cellular automata for simulating multiple land use changes using GIS. International Journal of Geographical Information Science, 16: 323–343.

    Article  Google Scholar 

  • Liu X, Li X, Shi X et al., 2008. Simulating complex urban development using kernel-based non-linear cellular automata. Ecological Modelling, 211: 169–181.

    Article  Google Scholar 

  • López E, Bocco G, Mendoza M et al., 2001. Predicting land-cover and land use change in the urban fringe: A case in Morelia city, Mexico. Landscape and Urban Planning, 55: 271–285.

    Article  Google Scholar 

  • Mundia C N, Murayama Y, 2010. Modeling spatial processes of urban growth in African cities: A case study of Nairobi City. Urban Geography, 31(2): 259–272.

    Article  Google Scholar 

  • Nagendra H, Munroe D K, Southworth J et al., 2004. From pattern to process: Landscape fragmentation and the analysis of land use/land cover change. Agriculture, Ecosystems and Environment, 101: 111–115.

    Article  Google Scholar 

  • Pain G, Baudry J, Burel F et al., 2000. Land Pop: Un outil d’étude de la structure spatiale des populations animals fragmentées. Revue Internationale de Géomatique, 10: 89–106.

    Google Scholar 

  • Pickett S T A, Cadenasso M L, Grove J M et al., 2001. Urban ecological systems: Linking terrestrial ecological, physical, and socioeconomic components of metropolitan areas. Annual Review of Ecology and Systematics, 32: 127–157.

    Article  Google Scholar 

  • Ray N, Burgman M A, 2006. Subjective uncertainties in habitat suitability maps. Ecological Modelling, 195: 172–186.

    Article  Google Scholar 

  • Ray N, Lehmann A, Joly P, 2002. Modeling spatial distribution of amphibian populations: A GIS approach based on habitat matrix permeability. Biodivers. Conserv., 11: 2143–2165.

    Article  Google Scholar 

  • Stevens D, Dragicevic S, Rothley K, 2007. iCity: A GIS-CA modelling tool for urban planning and decisionmaking. Environmental Modelling & Software, 22: 761–773.

    Article  Google Scholar 

  • Verburg P H, de Koning G H J, Kok K et al., 1999a. A spatial explicit allocation procedure for modelling the pattern of land use change based upon actual land use. Ecological Modelling, 116: 45–61.

    Article  Google Scholar 

  • Verburg P H, Schot P, Dijst M et al., 2004. Land use change modelling: Current practice and research priorities. GeoJournal, 61(4): 309–324.

    Article  Google Scholar 

  • Verburg P H, Veldkamp A, Fresco L O, 1999b. Simulation of changes in the spatial pattern of land use in China. Applied Geography, 19: 211–233.

    Article  Google Scholar 

  • Weber C, Puissant A, 2003. Urbanization pressure and modeling of urban growth: Example of the Tunis Metropolitan Area. Remote Sensing of Environment, 86: 341–352.

    Article  Google Scholar 

  • Weddell P, 2002. Urbanism: Modeling urban development for land use, transportation, and environment planning. Journal of American Planning Association, 68(3): 297–313.

    Article  Google Scholar 

  • White R, 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: 1175–199.

    Article  Google Scholar 

  • Wu F, Webster C J, 1998. Simulation of land development through the integration of cellular automata and multicriteria evaluation. Environment and Planning B: Planning and Design, 25: 103–126.

    Article  Google Scholar 

  • Yu K J, 1996. Security patterns and surface model in landscape ecological planning. Landscape and Urban Planning, 36: l–17.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Guangzhou Institute of Geography, Guangzhou, 510070, China

    Yuyao Ye, Yongxian Su, Hong-ou Zhang & Qitao Wu

  2. School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510275, China

    Kai Liu

Authors
  1. Yuyao Ye
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yongxian Su
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hong-ou Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Kai Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Qitao Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hong-ou Zhang.

Additional information

Foundation: National Natural Science Foundation of China, No.41001385; 12th Five-year National Science Supported Planning Project, No.2012BAJ15B02

Author: Ye Yuyao (1980–), PhD and Associate Professor, specialized in sustainable regional development and urban planning.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ye, Y., Su, Y., Zhang, Ho. et al. Construction of an ecological resistance surface model and its application in urban expansion simulations. J. Geogr. Sci. 25, 211–224 (2015). https://doi.org/10.1007/s11442-015-1163-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11442-015-1163-1

Keywords

Search

Navigation