Skip to main content

Advertisement

SpringerLink
Log in

Cellular Automata Based Model of Urban Spatial Growth

  • Research Article
  • Published:
Journal of the Indian Society of Remote Sensing Aims and scope Submit manuscript

Abstract

In the study reported in this paper an attempt has been made to develop a Cellular Automata (CA) model for simulating future urban growth of an Indian city. In the model remote sensing data and GIS were used to provide the empirical data about urban growth while Markov chain process was used to predict the amount of land required for future urban use based on the empirical data. Multi-criteria evaluation (MCE) technique was used to reveal the relationships between future urban growth potential and site attributes of a site. Finally using the CA model, land for future urban development was spatially allocated based on the urban suitability image provided by MCE, neighbourhood information of a site and the amount of land predicted by Markov chain process. The model results were evaluated using Kappa Coefficient and future urban growth was simulated using the calibrated model

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

Similar content being viewed by others

References

  • Batty, M. (1996). Urban change. Environment & Planning B, 23, 513–514.

    Google Scholar 

  • Batty, M. (2001). Urban evolution on the desktop: simulation with the use of extended cellular automata. Environment & Planning A, 30, 1943–1967.

    Article  Google Scholar 

  • Batty, M., & Xie, Y. (1994a). Modelling inside GIS Part 1: model structures, exploratory spatial data analysis and aggregation. International Journal of Geographical Information Science, 8(3), 291–307.

    Article  Google Scholar 

  • Batty, M., & Xie, Y. (1994b). Modelling inside GIS Part 2: selecting and calibrating urban models using ARC/INFO. International Journal of Geographical Information Science, 8(1), 451–470.

    Article  Google Scholar 

  • Batty, M., & Xie, Y. (1994c). From cells to cities. Environment & Planning B, 21, 31–48.

    Article  Google Scholar 

  • Batty, M., & Xie, Y. (1997). Possible urban automata. Environment & Planning B, 24, 175–192.

    Article  Google Scholar 

  • Clarke, K. C., & Gaydos, L. (2001). Loose-coupling a CA model and GIS: long-term urban growth prediction for San Franciso and Washington/Baltimore. International Journal of Geographical Information Science, 12(7), 699–714.

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Congalton, R. G. (1991). A review of assessing the accuracy of classifications of remotely sensed data. Remote Sensing of Environment, 37, 35–46.

    Article  Google Scholar 

  • Congalton, R. G., & Green, K. (1999). Assessing the accuracy of remotely sensed data: Principles and practices (1st ed.). Florida: CRC Press.

    Google Scholar 

  • Jacob, N., Krishnan, R., Harmsen, K., & Murali Krishna, I. V. (2006). Spatial dynamic modeling through cellular automata for simulating land use change dynamics. International Journal of Geoinformatics, 2(2), 31–38.

    Google Scholar 

  • Kiefer, R. W., & Lillesand, T. M. (2000). Remote sensing and image interpretation (1st ed.). New York: Wiley.

    Google Scholar 

  • Li, X., & Yeh, A. G. O. (2000). Modeling sustainable urban development by the integration of constrained cellular automata and GIS. International Journal of Geographical Information Science, 14(2), 131–152.

    Article  Google Scholar 

  • Malczewski, J. (1999). GIS and multicriteria decision analysis (1st ed.). New York: Wiley.

    Google Scholar 

  • Malczewski, J. (2006). GIS-based multicriteria decision analysis: a survey of the literature. International Journal of Geographical Information Science, 20(7), 703–726.

    Article  Google Scholar 

  • White, R. (2001). Cities and cellular automata. Discrete Dynamics in Nature and Society, 2, 111–125.

    Article  Google Scholar 

  • White, R., & Engelen, G. (1993). Cellular automata and fractal urban form: a cellular modeling approach to the evolution of urban land use patterns. Environment & Planning A, 25, 1175–1199.

    Article  Google Scholar 

  • White, R., & Engelen, G. (1994). Cellular dynamics and GIS: modelling spatial complexity. Geographical Systems, 1, 237–253.

    Google Scholar 

  • White, R., & Engelen, G. (1997). Cellular automata as the basis of integrated dynamic regional modelling. Environment & Planning B, 24, 235–246.

    Article  Google Scholar 

  • Wu, F. (2001a). An empirical model of intrametropolitan land use changes in a Chinese city. Environment & Planning B, 25, 245–263.

    Article  Google Scholar 

  • Wu, F. (2001b). Simland: a prototype to simulate land conversion through the integrated GIS and CA with AHP-derived transition rules. International Journal of Geographical Information Science, 12, 63–82.

    Article  Google Scholar 

  • Wu, F. (2002). Calibration of stochastic cellular automata: the application to rural-urban land conversions. International Journal of Geographical Information Science, 16(8), 795–818.

    Article  Google Scholar 

  • Wu, F., & Webster, C. J. (2000). Simulation artificial cities in a GIS environment: urban growth under alternative regulation regime. International Journal of Geographical Information Science, 14(7), 625–648.

    Article  Google Scholar 

  • Wu, F., & Webster, C. J. (2001). Simulation of land development through the integration of cellular automata and multicriteria evaluation. Environment & Planning B, 25, 103–126.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Human Settlement Analysis Division, Indian Institute of Remote Sensing, 4, Kalidas Road, Dehradun, 248001, Uttrakhand, India

    Sandeep Maithani

Authors
  1. Sandeep Maithani
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sandeep Maithani.

About this article

Cite this article

Maithani, S. Cellular Automata Based Model of Urban Spatial Growth. J Indian Soc Remote Sens 38, 604–610 (2010). https://doi.org/10.1007/s12524-010-0053-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12524-010-0053-3

Keywords

Search

Navigation