Modeling spatial variation of explanatory factors of urban expansion of Kolkata: a geographically weighted regression approach

Abstract

Modern cities face a large number of issues related to boundary, land alteration and environmental degradation. Extensive urban expansion is an especially serious problem faced by most of the cities in developing countries. Urban management has extensive engagement with rapid urban expansion and their factors to achieve a sustainable form of development. A more inclusive understanding of the urban driver variables and their cross comparison greatly helps to investigate this rapid urban expansion. The major theme of this study will be to inquire into this factors of urban expansion. Both global and local regressions are performed to determine the spatial variability of the driving forces of urban expansion. The results indicate that geographically weighted regression model outperformed global regression. Urban expansion in the city of Kolkata can be observed mainly in two directions; northeast and south-east. The possible reasons include that of economic appraising, lack of environmental distress and good spatial settings along with investor interest, which together determine the biased bidirectional axial expansion. This study comes to the conclusion that local variables are significant in driving the bi-directional urban expansion in the context of a biased urban management.