Urban Sprawl Analysis and Transportation Using Cellular Automata and Markov Chain

J. O. Olusina *

Department of Surveying and Geoinformatics, Faculty of Engineering, University of Lagos, Lagos, Nigeria

E. O. Abiodun

Department of Surveying and Geoinformatics, Faculty of Engineering, University of Lagos, Lagos, Nigeria

J. I. Oseke

Department of Surveying and Geoinformatics, Faculty of Engineering, University of Lagos, Lagos, Nigeria

*Author to whom correspondence should be addressed.


Abstract

The uncontrolled urban spread (urban sprawl) has both positive and negative implications. The adverse effects are more pronounced than its gains. Among others adverse effects is infrastructure provision (such as roads, etc.) which usually becomes a problem. This work examines the effects of urban sprawl in three (3) Local Government Areas (LGAs) of Lagos State so as to determine changes that have taken place between 1984 and 2006. Land Consumption Rate and Land Absorption Coefficient were introduced to aid in the quantitative assessment of the change, urban sprawl models were developed and the spread of urban sprawl in the next 14 years (2006 to 2020) were projected.

Lands at Imageries of three epochs (1984, 2000 and 2006) were processed, classified and analysed. CA-Markov modelling was carried out to predict for 2020. From the research, it was discovered that the Built-up Areas will increase from 8.76% to 17.60% of the Land use/land cover i.e. continuous urban sprawl in future. Finally, the adverse effects of urban sprawl on transportation in this area have resulted in high congestion cost and high level of air pollution just to mention but a few. The sprawl pattern has opened up the rural areas (such as Oniru, Ajah, Eti-Osa) and till today the sprawl is still unabated.

 

Keywords: Urban Sprawl, land-use/land-cover, change detection, remote sensing, Geographic Information Systems (GIS)


How to Cite

O. Olusina, J., E. O. Abiodun, and J. I. Oseke. 2014. “Urban Sprawl Analysis and Transportation Using Cellular Automata and Markov Chain”. Physical Science International Journal 4 (8):1191-1210. https://doi.org/10.9734/PSIJ/2014/9211.

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