Monitoring Spatial-Temporal Transition Dynamics of Transport Infrastructure Space in Urban Growth Phenomena: A Case Study of Lagos—Nigeria

Abstract

Lagos is one of the fastest growing world mega-cities with a huge urban mobility crisis, the traditional aggregate city’s development model could not provide reliable scientific solutions to monitor the competing demands of various land-use components and the urbanization’s effects on transport infrastructure space. This study uses a disaggregated predictive spatial modeling approach to investigate the evolutionary dynamics of transportation infrastructure space to address the fragmented urban chain process. The methodology involves analysis and modeling of the land-use spatial transition changes that have occurred over the past three decades using three Landsat imagery epochs (1984, 2013, and 2019) in remote sensing ARC-GIS 10.7. Furthermore, the prediction of the two-temporal milestones (2030 and 2050) using hybrid cellular automata-Markov (CA-Markov) implemented in IDIRISI SELVA 17.0 software when the tides of social-demographic factors were expected to bring about significant urban spatial transformation. The forecast results are expected to increase the area for transport infrastructure spaces by 93 km2 (7.3%) in 2030 and 157 km2 (12.4%) in 2050. The model’s kappa reliability coefficient estimates for the three temporal scales (k1984 = 85%; k2013 = 88% and k2019 = 89%) are higher than the 80% minimum adjudged strong agreement between the ground truth and prediction classified images in literature. The model provides efficient tool in urban development planning and sustainable transport decisions.