Assessing the Rapid Urbanization in Tertiary City of Bangladesh by Land Use and Land Cover Change Detection from 2000 to 2024 through NDVI Based Classification and future forecasting for 2032 by Cellular Automata (CA) model in Meherpur District

Understanding Land Use and Land Cover (LULC) changes is vital for environmental sustainability, particularly in areas undergoing rapid urban and agricultural transformations. In Meherpur District, Bangladesh, limited research has integrated LULC mapping with predictive models, resulting in a gap in knowledge regarding future land use patterns in this fast-changing region. This study addresses that gap by analyzing LULC changes from 2000 to 2024 using the Normalized Difference Vegetation Index (NDVI), Geographic Information Systems (GIS), and the Cellular Automata (CA) model for predictive analysis. The study reveals significant LULC changes over the 24-year period, including an 18% decrease in vegetation cover, a 6% reduction in agricultural land, and a 4% increase in built-up areas. These trends align with global patterns of urban expansion, often at the expense of agricultural and natural land. Additionally, increases in fallow land (7%) and water bodies (8%) indicate changing land use driven by population growth and infrastructure development. The loss of vegetation, in particular, poses risks to biodiversity, climate regulation, and food security. An innovative aspect of this research is the use of the CA model with the MOLUSCE plugin in QGIS, enabling simulations of future LULC changes up to 2032. This predictive approach offers insights into the impacts of ongoing urbanization, unlike previous studies in Bangladesh that mainly focused on historical LULC changes. The study suggests several future research directions, including investigating the socio-economic drivers of LULC changes, expanding the geographic scope to neighboring regions, and incorporating advanced remote sensing and machine learning techniques to enhance the accuracy of predictions. In conclusion, this research fills a critical gap in LULC studies in Meherpur by combining historical analysis with predictive modeling, offering valuable insights for policymakers to guide sustainable land use planning amidst ongoing urbanization and agricultural development.