Land Cover Analysis and Change Detection: Comprehensive Study with Linear Regression Prediction

Land cover analysis and change detection are critical components of environmental monitoring and management. This paper explores methodologies, technologies, and applications related to the assessment of land cover changes over time. Using Geographic map techniques and Geographic Information System (GIS) tools, we analyze satellite imagery using maps to provide insights into land cover dynamics. Additionally, we employ linear regression for predicting future land cover changes based on historical data. A core component of the analysis is the use of linear regression models to predict future land cover changes. These models are developed using historical land cover data to forecast trends and potential future scenarios. Our study provides a detailed examination of land cover transformations, highlighting significant shifts such as urban expansion, deforestation, and agricultural development. The predictive models offer valuable insights into future land cover trends, enabling better planning and decision-making. This study focuses on identifying significant changes in land use, mainly focusing on Urbanization, Vegetation and Agriculture, Barrens Land and Deforestation.