Remote sensing-based monitoring of peri-urban landscape dynamics: A case study of Rupganj, Bangladesh

Abstract

This research evaluates changes in land use and land cover, as well as vegetation dynamics in Rupganj, using Google Earth Engine and ArcGIS. For that purpose, land cover categories were classified utilizing supervised algorithms applied to multi-temporal Landsat TM and OLI imagery from the years 1994 and 2024. The classification accuracy attained was 86.75% for the 1994 imagery and 87.20% for the 2024 imagery. The analysis of land use and land cover change between 1994 and 2024 revealed significant increases in agricultural, vegetation, and urban areas (262.51%, 60.08%, and 12.96%, respectively). On the other hand, a notable decrease in barren lands and water bodies was observed (-46.12% and -42.11%, respectively). A substantial increase in NDVI values was recorded in 2024 relative to 1994, underscoring the enhanced vegetation health. The results highlight the patterns of urban growth, increased agricultural practices, reforestation initiatives, and changes in hydrological dynamics within the region. It is imperative to implement stringent measures aimed at safeguarding water resources, directing sustainable urban development, encouraging agro-ecological practices, and establishing green infrastructure as a standard practice. In this context, the integration of cloud-enabled monitoring facilitates adaptive and sustainable land management in the face of rapid peri-urban transformation.