Spatiotemporal variability of urban growth factors: A global and local perspective on the megacity of Mumbai

The rapid growth of megacities requires special attention among urban planners worldwide, and partic-ularly in Mumbai, India, where growth is very pronounced. To cope with the planning challenges this willbring, developing a retrospective understanding of urban land-use dynamics and the underlying driving-forces behind urban growth is a key prerequisite. This research uses regression-based land-use changemodels – and in particular non-spatial logistic regression models (LR) and auto-logistic regression mod-els (ALR) – for the Mumbai region over the period 1973–2010, in order to determine the drivers behindspatiotemporal urban expansion. Both global models are complemented by a local, spatial model, the so-called geographically weighted logistic regression (GWLR) model, one that explicitly permits variationsin driving-forces across space. The study comes to two main conclusions. First, both global models suggestsimilar driving-forces behind urban growth over time, revealing that LRs and ALRs result in estimatedcoefficients with comparable magnitudes. Second, all the local coefficients show distinctive temporaland spatial variations. It is therefore concluded that GWLR aids our understanding of urban growth pro-cesses, and so can assist context-related planning and policymaking activities when seeking to secure asustainable urban future.