Land Use and Land Cover Change Detection Using Remote Sensing and Machine Learning: A Temporal Analysis
摘要
With cities growing at unprecedented rates, urbanization and land use changes are also critical factors that affect environmental sustainability and resource management. In this study, analysis of land use and land cover (LULC) changes on Bhubaneswar and Cuttack areas in Odisha, during the year March 2019 to March 2024, is interpreted using Google Earth Engine capabilities for satellite image processing. Dedicated land cover and LULC supervised classifications were performed by the use of Sentinel-2 and Dynamic World datasets focusing on filtered classes as built-up and vegetation areas. Its findings show that built-up areas grew by 6.21%, or around 11.57 million square meters of new urban expansion. Meanwhile, the Annapa Gold Lush field increased by 23.24% to have another vegetation area of adding 21.63 million square meters as green cover and energy park amenities. But along with this up beat news values of tree removals in Bhubaneswar crossing over 7800 trees during period between 2019 and 2023, counterplotting over all greenery picture. There have been government schemes for the sake of such wastes of antiquated timbered land and tree-plantation proceedings, but solely with reference to 40% objectives ever attained. Growth patterns that have been detected indicate a relatively balanced yet multiplex typological trajectory of urban development requiring careful planning and resource management. The combining of GEE with remote sensing datasets that is presented an effective and scalable method for tracking LULC changes; therefore an imperative tool to decision makers in sustainable urban management.