Abstract
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Urbanisation refers to the growth of the towns and cities due to large proportion of the population living in urban areas and its suburbs at the expense of its rural areas. Unplanned urbanisation leads to the large scale land use changes affecting the sustenance of local natural resources. This necessitates an understanding of spatial patterns of urbanisation to implement appropriate mitigation measures. The focus of the current study is to analyse the spatial patterns of urbanisation and sprawl in Pune city with 10 km buffer using temporal remote sensing data through geoinformatics and spatial metrics. Land use analyses of the city with a buffer of 10km reveals that there has been a significant increase of built-up land from 2.96% (1977) to 20.4% (2013) with the reduction of vegetation from 22.49 to 17.96%. Shannon entropy reveal the tendency of sprawl in NW direction. Zone and Gradient-wise spatial metrics analysis is done to understand the spatial patterns of urbanisation at local levels. The analysis suggests that urbanisation has caused fragmentation with adjacencies in buffer zones. Spatial metrics substantiate rampant sprawl at the peri-urban regions and infilling at city centre. However, this value has reduced in 2013 indicating of reaching the threshold of urbanization. These analyses highlight of the significant changes in land cover with the decline in vegetation, water bodies, etc. This necessitates an integrated approaches in urban planning to ensure the sustenance of water, moderation of micro climate, etc. Conservative urban planning would take into account the sustenance of natural resources and people’s livelihood aspects. Visualization of urban growth at local levels helps the urban planners and decision-makers in understanding the role of policy decisions (industrialization, etc.) on land use dynamics, which helps in evolving region specific development strategies to mitigate the potential impacts on the urban environment. This research provides the details of land use and its development for guidi ng scientific-based decision support and policy making.
