Multi-Temporal Image Processing for LULC Classification and Change Detection

Changes in land use land cover (LULC) are critical in regional studies, local, and worldwide changes in the environment. The term “land use” relates to how humans are using the landscape, whether it is for expansion, conservation, or a combination of the two. Human activity on the Earth’s surface alters the land cover area. These adjustments greatly affect how well-functioning vital Earth system components (such as the balance of energy, soil, and water). Applications for remote sensing make it possible to analyses land changes quickly and affordably. Numerous researchers have created techniques for analyzing modifications in the LULC. This study used GIS and random forest machine learning technique to pinpoint the LULC changes in Muzaffarpur District’s urban and rural areas in the span of 15 years i.e., 2005 to 2020. The User land is scattered throughout the western region. The district’s soil becomes more salinized and alkaline as a result of the waterlogging that is also prevalent in some areas of the district. This study’s technique is simple and inexpensive. Between 2005 and 2020, there were major variations in the LULC in the research area. The rise in built-up activity is the main cause of the LULC alterations in the studied region. The current study may not be significantly impacted by the LULC changes. However, to maintain environmentally sustainable development in the future, LULC alteration needs to be continuously watched.