Rapid urbanization and land use and land cover changes (LULCCs) pose significant challenges to sustainable urban development and climate-resilient cities in coastal regions around the world. This study employs stochastic and numerical approaches to investigate the spatiotemporal patterns of LULCC and their socioeconomic impacts in three rapidly urbanizing coastal districts (Khulna, Satkhira, and Bagerhat) of Bangladesh from 1992 to 2022. Exploiting the cloud computing, remote sensing, and stochastic data analysis techniques, we analyze Landsat satellite imageries to classify land cover into five categories: built-up, waterbody, barren land, vegetation, and agriculture. The overall accuracy of the classified images ranges from 89.52% to 95.49%, with kappa coefficients between 0.847 and 0.929. Our findings reveal significant LULCC, with built-up areas increasing by 15.68%, 9.72%, and 4.27% in Satkhira, Khulna, and Bagerhat districts, respectively. Additionally, agricultural land has decreased by 11.92%, 38.42%, and 30.89% in rural areas, while waterbodies have expanded by 49.32%, 41.95%, and 27.95% in the same districts. To assess the socioeconomic impacts of LULCC, we integrate census data from the Bangladesh Bureau of Statistics and perform spatial clustering and outlier analysis to delineate population concentration in the study area. Furthermore, we summarize the workforce analysis data in the geographical information system’s platform. Pearson’s correlation analysis reveals that significant relationships exist between LULCC and socioeconomic factors, such as built-up areas negatively correlating with vegetation (−0.470) and agriculture (−0.344) in urban areas. Upon completing the analysis, we underscore that adaptive urban development strategies and climate-resilient planning may be required immediately to ensure a balance of economic growth, environmental conservation, and social well-being in the rapidly urbanizing coastal regions.
Miah et al. (2026) studied this question.