Skip to main content

Advertisement

SpringerLink
Log in

Scenario-based evaluation of urban development sustainability: an integrative modeling approach to compromise between urbanization suitability index and landscape pattern

  • Published:
Environment, Development and Sustainability Aims and scope Submit manuscript

Abstract

Sustainability analysis of urban complex systems, as an interdisciplinary study, necessitates integrative modeling approaches for analyzing relationships between land parameters and landscape patterns. The present paper emphasizes applicability of dynamic and scenario-based investigation of urban environments for understanding the interactions between urbanization suitability and landscape pattern. Combining parameter modification and model integration approaches for introducing growth alternatives, a basis was established for detailed assessment of the Karaj urban context, Iran. SLEUTH’s probabilistic images of future urbanized lands of two growth scenarios (historical trend-based urban growth and compact urban growth) were simultaneously employed as dynamic factors for urbanization suitability mapping and landscape pattern analysis of the years 2011, 2020, 2030 and 2040. Findings of the present studies showed while historical trend-based urban expansion occupied more land resources, this growth option resulted in a more manageable pattern of urban landscape in terms of its connectivity and compactness as well as possessing higher urbanization suitability index across the study time frame. This study addresses utility of scenario-based analysis of urban areas that furnishes urban planners with insights into cumulative impacts of an ongoing urbanization process under different environmental circumstances.

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

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  • Akın, A., Clarke, K. C., & Berberoglu, S. (2014). The inclusion of historical exclusion on the calibration of the SLEUTH urban growth model. International Journal of Applied Earth Observation and Geoinformation, 27, 156–168.  

    Article  Google Scholar 

  • Asgarian, A., Amiri, B. J., & Sakieh, Y. (2014). Assessing the effect of green cover spatial patterns on urban land surface temperature using landscape metrics approach. Urban Ecosystems. doi: 10.1007/s11252-014-0387-7.

  • 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(2), 247–261.

    Article  Google Scholar 

  • Deng, J. S., Wang, K., Hong, Y., & Qi, J. G. (2009). Spatiotemporal dynamics and evolution of land use change and landscape pattern in response to rapid urbanization. Landscape and Urban Planniing, 92(3–4), 187–198.

    Article  Google Scholar 

  • Dezhkam, S., Amiri, B. J., Darvishsefat, A. A., & Sakieh, Y. (2014). Simulating urban growth dimensions and scenario prediction through sleuth model: A case study of Rasht County, Guilan, Iran. GeoJournal, 79(5), 591–604.

    Article  Google Scholar 

  • Dietzel, C., Oguz, H., Hemphill, J. J., Clarke, K. C., & Gazulis, N. (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.

    Article  Google Scholar 

  • Eastman, R. (2009). Idrisi Taiga version. 16.01 Clark Laboratories, Clark University, Worcester, MA.

  • Feng, H. H., Liu, H. P., & Lü, Y. (2012). Scenario prediction and analysis of urban growth using SLEUTH model. Pedosphere, 22(2), 206–216.

    Article  Google Scholar 

  • Gandhi, S. I., & Suresh, V. M. (2012). Prediction of urban sprawl in Hyderabad city using spatial model, remote sensing and GIS techniques geography. International Journal of Scientific Research, 1(2), 80–82.  

    Article  Google Scholar 

  • Hasani Sangani, M., Amiri, B. J., Alizadeh Shabani, A., Sakieh, Y., & Ashrafi, S. (2014). Modeling relationships between catchment attributes and river water quality in southern catchments of the Caspian Sea. Environmental Science and Pollution Research. doi: 10.1007/s11356-014-3727-5.

  • Herold, M., Goldstein, N. C., & Clarke, K. C. (2003). The spatiotemporal form of urban growth: Measurement, analysis and modeling. Remote Sensing of Environment, 86(3), 286–302.

    Article  Google Scholar 

  • Iranian Statistics Center (2012). General census of population and housing of Karaj City.

  • Jantz, C. A., Goetz, S. J., Donato, D., & Claggett, P. (2010). Designing and implementing a regional urban modeling system using the SLEUTH cellular urban model. Computers, Environment and Urban Systems, 34(1), 1–16.

    Article  Google Scholar 

  • Jantz, C. A., Goetz, S. J., & Shelley, M. K. (2003). Using the SLEUTH urban growth model to simulate the impacts of future policy scenarios on urban land use in the Baltimore-Washington metropolitan area. Environment and Planning B: Planning and Design, 31(2), 251–271.

    Article  Google Scholar 

  • Luo, G., Yin, C., Chen, X., Xu, W., & Lu, L. (2010). Combining system dynamic model and CLUE-S model to improve land use scenario analyses at regional scale: A case study of Sangong watershed in Xinjiang, China. Ecological Complexity, 7(2), 198–207.

    Article  Google Scholar 

  • Mahiny, A. S., & Clarke, K. C. (2012). Guiding SLEUTH land-use/land-cover change modeling using multicriteria evaluation: Towards dynamic sustainable land-use planning. Environment and Planning B: Planning and Design, 39(5), 925–944.

    Article  Google Scholar 

  • Mahiny, A. S., & Clarke, K. C. (2013). Simulating hydrologic impacts of urban growth using SLEUTH, multi criteria evaluation and runoff modeling. Journal of Environmental Informatics, 22(1), 27–38.

    Article  Google Scholar 

  • Mahiny, A. S., & Gholamalifard, M. (2007). Dynamic spatial modeling of urban growth through cellular automata in a GIS environment. International Journal of Environmental Research, 1(3), 368–377.

    Google Scholar 

  • Makhdoum, F. M. (2007). Fundamental of land use planning. Tehran: University of Tehran Press.

    Google Scholar 

  • McGarigal, K., & Marks, B. J. (1995). FRAGSTATS: Spatial pattern analysis program for quantifying landscape structure. USDA Forest Service.

  • Menard, A., & Marceau, D. J. (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, 79(3–4), 253–265.

    Article  Google Scholar 

  • Onsted, J. A., & Chowdhury, R. R. (2014). Dose zoning matter? A comparative analysis of landscape change in Redland, Florida using cellular automata. Landscape and Urban Planning, 121, 1–18.

    Article  Google Scholar 

  • Onsted, J. A., & Clarke, K. C. (2012). The inclusion of differentially assessed lands in urban growth model calibration: A comparison of two approaches using SLEUTH. International Journal of Geographical Information Science, 26(5), 881–898.

    Article  Google Scholar 

  • Rafiee, R., Mahiny, A. S., Khorasani, N., Darvishsefat, A. A., & Danekar, A. (2009). Simulating urban growth in Mashad City, Iran through the SLEUTH model (UGM). Cities, 26, 19–26.

    Article  Google Scholar 

  • Riveira, I. S., & Maseda, R. C. (2006). A review of rural land-use planning models. Environment and Planning B: Planning and Design, 33(2), 165–183.

    Article  Google Scholar 

  • Rounsevell, M. D. A., Ewert, F., Reginster, I., Leemans, R., & Carter, T. R. (2005). Future scenarios of European agricultural land use: II. Projecting changes in cropland and grassland. Agriculture, Ecosystem & Environment, 107(2–3), 117–135.

    Article  Google Scholar 

  • Saaty, T. L. (1980). The analytic hierarchy process: Planning, priority setting, resource allocation. New York: McGraw Hill.

    Google Scholar 

  • Sakieh, Y. (2013). Urban sustainability through Urban growth modeling and land suitability analysis (Karaj Case Study). M.Sc., Thesis, University of Tehran.

  • Santé, I., García, A. M., Miranda, D., & Crecente, R. (2010). Cellular automata model for the simulation of real-world urban processes: A review and analysis. Landscape and Urban Planning, 96(2), 108–122.

    Article  Google Scholar 

  • Silva, E. A., & Clarke, K. C. (2002). Calibration of the SLEUTH urban growth model for Lisbon and Porto, Portugal. Computers, Environment and Urban Systems, 26(6), 525–552.

    Article  Google Scholar 

  • Soares-Filho, B. S., Cerqueira, G. C., & Pennachin, C. L. (2002). DINAMICA—a stochastic cellular automata model designed to simulate the landscape dynamics in an Amazonian colonization frontier. Ecological Modelling, 154(3), 217–235.

    Article  Google Scholar 

  • Solecki, W. D., & Oliveri, C. (2004). Downscaling climatic change scenarios in an urban land use change model. Environmental Management, 72(1–2), 105–115.

    Google Scholar 

  • Stevens, D., & Dragicevic, S. (2007). A GIS-based irregular cellular automata model of land-use change. Environment and Planning B: Planning and Design, 34(4), 708–724.

    Article  Google Scholar 

  • Sullivan, D. O., & Torrens, P. M. (2000). Cellular models of urban systems, CASA working paper series, paper 22, available online at :www.casa.ucl.uk/. Accessed August 01, 2005.

  • Thapa, R. B., & Murayama, Y. (2009). Examining spatiotemporal urbanization patterns in Kathmandu Valley, Nepal: Remote sensing and spatial metrics approaches. Remote Sensing, 1(3), 534–556.

    Article  Google Scholar 

  • Thapa, R. B., & Murayama, Y. (2010). Drivers of urban growth in the Kathmandu Valley, Nepal: Examining the efficacy of the analytic hierarchy process. Applied Geography, 30(1), 70–83.

    Article  Google Scholar 

  • Thapa, R. B., & Murayama, Y. (2012). Scenario based urban growth allocation in Kathmandu Valley, Nepal. Landscape and Urban Planning, 105(1–2), 140–148.

    Article  Google Scholar 

  • Uy, P. D., & Nakagoshi, N. (2008). Application of land suitability analysis and landscape ecology to urban greenspace planning in Hanoi Vietnam. Urban Forestry & Urban Greening, 7(1), 25–40.

    Article  Google Scholar 

  • Verburg, P. H., Schulp, C. J. E., Witte, N., & Veldkamp, A. (2006). Downscaling of land use change scenarios to assess the dynamics of European landscapes. Agriculture, Ecosystem & Environment, 114(1), 39–56.

    Article  Google Scholar 

  • Verburg, P. H., Soepboer, W., Veldkamp, A., Limpiada, R., Espaldon, V., & Mastura, S. S. A. (2002). Modeling the spatial dynamics of regional land use: The CLUE-S model. Environmental Management, 30(3), 391–405.

    Article  Google Scholar 

  • WCED (World Commission on Environment and Development). (1987). Our common future. New York: Oxford University Press.

    Google Scholar 

  • Wey, W. M., & Hsu, J. (2014). New urbanism and smart growth: Toward achieving a smart National Taipei University District. Habitat International, 42, 164–174.

    Article  Google Scholar 

  • Wu, J. G. (2014). Urban ecology and sustainability: The state-of-the-science and future directions. Landscape and Urban Planning, 125, 209–221.

    Article  Google Scholar 

  • Xiang, W. N., & Clarke, K. C. (2003). The use of scenarios in land-use planning. Environment and Planning B: Planning and Design, 30(6), 885–909.

    Article  Google Scholar 

  • Yang, X., & Lo, C. P. (2003). Modeling urban growth and landscape changes in the Atlanta metropolitan area. International Journal of Geographical Information Science, 17(5), 463–488.

    Article  Google Scholar 

  • Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353.

    Article  Google Scholar 

  • Zhou, W., Huang, G., & Cadenasso, M. L. (2011). Does spatial configuration matter? Understanding the effects of land cover pattern on land surface temperature in urban landscapes. Landscape and Urban Planning, 102(1), 54–63.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Environmental Science, Faculty of Natural Resources, University of Tehran, Karaj, Iran

    Yousef Sakieh, Bahman Jabbarian Amiri, Afshin Danekar & Sadeq Dezhkam

  2. Department of Forestry, Faculty of Natural Resource, University of Tehran, Karaj, Iran

    Jahangir Feghhi

Authors
  1. Yousef Sakieh
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Bahman Jabbarian Amiri
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Afshin Danekar
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jahangir Feghhi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Sadeq Dezhkam
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Bahman Jabbarian Amiri.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sakieh, Y., Amiri, B.J., Danekar, A. et al. Scenario-based evaluation of urban development sustainability: an integrative modeling approach to compromise between urbanization suitability index and landscape pattern. Environ Dev Sustain 17, 1343–1365 (2015). https://doi.org/10.1007/s10668-014-9609-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10668-014-9609-7

Keywords

Search

Navigation