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Article

Urban Sprawl and Growth Prediction for Lagos Using GlobeLand30 Data and Cellular Automata Model

1
Environmental Applied Science and Management, Yeates School of Graduate Studies, Ryerson University, Toronto, ON M5B 2K3, Canada
2
Department of Geography and Environmental Studies, Ryerson University, Toronto, ON M5B 2K3, Canada
*
Author to whom correspondence should be addressed.
Academic Editor: Claus Jacob
Received: 14 October 2020 / Revised: 14 October 2020 / Accepted: 15 October 2020 / Published: 5 May 2021
(This article belongs to the Special Issue Feature Papers 2020 Editors' Collection)
Urban growth in various cities across the world, especially in developing countries, leads to land use change. Thus, predicting future urban growth in the most rapidly growing region of Nigeria becomes a significant endeavor. This study analyzes land use and land cover (LULC) change and predicts the future urban growth of the Lagos metropolitan region, using Cellular Automata (CA) model. To achieve this, the GlobeLand30 datasets from years 2000 and 2010 were used to obtain LULC maps, which were utilized for modeling and prediction. Change analysis and prediction for LULC scenario for 2030 were performed using LCM and CA Markov chain modeling. The results show a substantial growth of artificial surfaces, which will cause further reductions in cultivated land, grassland, shrubland, wetland, and waterbodies. There was no appreciable impact of change for bare land, as its initial extent of cover later disappeared completely. Additionally, artificial surfaces/urban growth in Lagos expanded to the neighboring towns and localities in Ogun State during the study period, and it is expected that such growth will be higher in 2030. Lastly, the study findings will be beneficial to urban planners and land use managers in making key decisions regarding urban growth and improved land use management in Nigeria. View Full-Text
Keywords: urban sprawl; GlobeLand30; LULC change; remote sensing; cellular automata; Markov chain; growth prediction; Lagos urban sprawl; GlobeLand30; LULC change; remote sensing; cellular automata; Markov chain; growth prediction; Lagos
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MDPI and ACS Style

Onilude, O.O.; Vaz, E. Urban Sprawl and Growth Prediction for Lagos Using GlobeLand30 Data and Cellular Automata Model. Sci 2021, 3, 23. https://0-doi-org.brum.beds.ac.uk/10.3390/sci3020023

AMA Style

Onilude OO, Vaz E. Urban Sprawl and Growth Prediction for Lagos Using GlobeLand30 Data and Cellular Automata Model. Sci. 2021; 3(2):23. https://0-doi-org.brum.beds.ac.uk/10.3390/sci3020023

Chicago/Turabian Style

Onilude, Olalekan O., and Eric Vaz. 2021. "Urban Sprawl and Growth Prediction for Lagos Using GlobeLand30 Data and Cellular Automata Model" Sci 3, no. 2: 23. https://0-doi-org.brum.beds.ac.uk/10.3390/sci3020023

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