Abstract

Because of the lack of time-series spatial data on urban components, urban expansion in developing countries has usually been studied using a pixel-based approach, despite the coarse spatial resolution associated with this technique. To understand the residential-scale processes involved in urban expansion, we developed feature-oriented GIS data extracted from very high spatial resolution satellite images (IKONOS for 2000 and Quickbird for 2006 and 2008). We selected a fringe area of Ulaanbaatar, the capital municipality of Mongolia, as a case study. Residential plots in this area have developed in an unplanned manner owing to the poor execution of land reform policy. This study facilitated the residential-scale delineation of the significantly expanding area occupied by private land plots in time series. It also permitted the identification of geographical factors driving the expansion. Using a logistic regression model, we found that such expansion is related to social infrastructure rather than to natural landforms. In particular, new plots of private land tended to be built near pre-existing plots and in proximity to roads and water kiosks (which provide essential drinking water for residents). These findings and the probability map predicted by the model have implications for urban planners and decision makers.

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