Land cover detection and classification has been an important component of Geographic Information Systems.They are used in policy planning, socio-economic analysis, cartography and Government scheme planning andevaluation. Our study uses high-resolution time-series satellite images of Indian cities between years 2000-2017 and measures the changes in area occupied by infrastructure such as buildings and hutments during thatperiod. To detect buildings and hutments we train a U-Net model for image segmentation task and highlightthe boundaries for man-made constructions i.e. buildings and hutments for each block in our New Delhi datacollection. We have also provided sample contrast against the development information available on BHUVANportal, made publicly available by Indian Space Research Organization (ISRO) study. Using the time-seriesdata of building and hutment growth, we can enable urban planners and policy makers to identify necessity ofsupplementary resources like government hospitals, roads, gardens, etc.
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