Abstract:
Pakistan has a unique landscape geographically due to its strategic geo-political im portance. It has played a vital role in global climate and politics. There are various
semantic segmentation studies performed on remote sensing high-resolution imagery of
various urban and rural areas into major classes of buildings, vegetation, water, and
roads. These analyses have supported the land coverage study, which can facilitate ur ban infrastructure management, forestry, disaster management, and climate challenges.
Recent climate reports have confirmed the importance of these studies, especially for
Pakistan. It’s a critical location for the global south to observe the climate catastrophe.
This research will focus on three major cities of Islamabad, Karachi, and Quetta and
semantically segment the satellite imagery to study the land coverage. My research will
contribute to developing the dataset from major cities of Pakistan and compare the
performance of state-of-the-art semantic segmentation networks to evaluate the dataset.
It will help in selecting a highly effective deep learning network and generalizing those
networks on my prepared dataset.
