Multicriteria Regression Approach to Modeling Urban Expansion in Greater Lagos, Nigeria

Detecting changes that have occurred in an area, identifying drivers of expansion, and the ability to predict future changes in expansion are important for long-term planning. Lagos (Nigeria) has experienced rapid expansion and many factors can be offered to contribute to its sprawling. The aim of this study is to develop a multivariate model for urban expansion in Greater Lagos for which a set of 14 drivers of expansion is considered in a multinucleic structure. The study area was partitioned into 25 regular cells of 20 x 25 km each. A sequence of images of the study area for 1984, 2001, 2006, and 2013 was acquired and processed into six land-use classes. Empirical data for the evaluation of each driver were acquired from relevant government agencies and through a field survey. Coefficients of the multicriteria model were derived using a stepwise linear regression analysis. The effectiveness of each driver was tested at a significant level of alpha = 0.05. Predicted results suggest that urban expansion will increase by 56% in 2030. The observed rate of expansion may form the basis for a new policy on land reform in Lagos. (C) 2017 American Society of Civil Engineers.