CONTENT-BASED IMAGE RETRIEVAL AND SAR IMAGERY ADDRESSING URBANIZATION CHALLENGES

Abstract

Radar satellite imagery is frequently subject to noise interference. This study introduces the NEST Tool, which is designed to mitigate such noise using despeckling techniques. The tool employs statistical operations to reduce the noise on a bandwise basis. The results indicate that the NEST Tool surpasses the existing state-of-the-art methods. This study explores the impact of urbanization on land use and land cover (LULC) changes in the Warangal urban region from 2015 to 2022 using remote sensing and Geographic Information System (GIS) methodologies. Landsat imagery was processed using ArcGIS, and supervised classification was used to generate the LULC maps. The study revealed significant urban expansion, with bare soil and areas integrating agricultural and forestland being the most affected. Despite a slight increase in water bodies, the region faces challenges in meeting growing population demands. The mine and dump areas contracted by 192.5 hectares due to reduced production, while the forest area decreased by 184 ha. Agricultural and forest areas declined by 18.85% in urban zones and 16.3% in existing areas. This study emphasizes the need for effective planning to mitigate the adverse effects of urbanization on LULC in urban and rural contexts. These findings highlight the role of remote sensing and GIS technologies in understanding LULC dynamics, with implications for mine reclamation, closure planning, and sustainable urban development in Warangal