Paper Info
Title
Integration of logistic regression, Markov chain and cellular automata models to simulate urban expansion.
Abstract
This research analyses the suburban expansion in the metropolitan area of Tehran, Iran. A hybrid model consisting of logistic regression model, Markov chain (MC), and cellular automata (CA) was designed to improve the performance of the standard logistic regression model. Environmental and socio-economic variables dealing with urban sprawl were operationalised to create a probability surface of spatiotemporal states of built-up land use for the years 2006, 2016, and 2026. For validation, the model was evaluated by means of relative operating characteristic values for different sets of variables. The approach was calibrated for 2006 by cross comparing of actual and simulated land use maps. The achieved outcomes represent a match of 89% between simulated and actual maps of 2006, which was satisfactory to approve the calibration process. Thereafter, the calibrated hybrid approach was implemented for forthcoming years. Finally, future land use maps for 2016 and 2026 were predicted by means of this hybrid approach. The simulated maps illustrate a new wave of suburban development in the vicinity of Tehran at the western border of the metropolis during the next decades.
Year
DOI
Venue
2013
10.1016/j.jag.2011.12.014
International Journal of Applied Earth Observation and Geoinformation
Keywords
Field
DocType
Land use change,Logistic regression,Markov chain,Cellular automata,Tehran
Econometrics,Cellular automaton,Land use, land-use change and forestry,Remote sensing,Markov chain,Urban sprawl,Statistics,Metropolitan area,Urban expansion,Geography,Logistic regression,Land use
Journal
Volume
ISSN
Citations 
21
0303-2434
52
PageRank 
References 
Authors
2.49
6
4
Name
Order
Citations
PageRank
Jamal Jokar Arsanjani119113.19
Marco Helbich217313.47
Wolfgang Kainz315018.79
Ali Darvishi Boloorani4554.69