Preprint Article Version 1 This version is not peer-reviewed

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

Version 1 : Received: 14 October 2020 / Approved: 15 October 2020 / Online: 22 October 2020 (00:00:00 CEST)

How to cite: Onilude, O.O.; Vaz, E. Urban Sprawl and Growth Prediction for Lagos Using GlobeLand30 Data and Cellular Automata Model. Preprints 2020, 2020110112 (doi: 10.3390/sci2040080). Onilude, O.O.; Vaz, E. Urban Sprawl and Growth Prediction for Lagos Using GlobeLand30 Data and Cellular Automata Model. Preprints 2020, 2020110112 (doi: 10.3390/sci2040080).

Abstract

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.

Subject Areas

urban sprawl; GlobeLand30; LULC change; remote sensing; cellular automata; Markov chain; growth prediction; Lagos

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.

Leave a public comment
Send a private comment to the author(s)
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.