Quantifying a decadal driver of ecological environment in Jamuna River basin using geospatial techniques

Abstract This study investigates the ecological environment quality within Bangladesh's Jamuna River Basin from 2003 to 2023, using Landsat imagery analysed through Google Earth Engine (GEE) to create the Remote Sensing Ecological Index (RSEI) for the districts of Kurigram, Sirajganj and Tangail. The analysis reveals significant spatial and temporal variations in ecological health, driven by both anthropogenic and natural factors. The findings show that whilst Kurigram's ecological quality fluctuates between good and moderate states, Sirajganj has experienced a continuous decline, and Tangail shows marked ecological degradation, especially in urban areas. The study demonstrates that the integration of RSEI with spatial autocorrelation techniques, such as Moran's I and Local Indicator of Spatial Autocorrelation (LISA), effectively captures spatial clustering of ecological quality. The clustering patterns indicate that ecological degradation is unevenly distributed, influenced by both human activities and natural processes. These results emphasise the importance of sustainable land management practices to mitigate further ecological decline and provide a foundation for targeted conservation efforts. The study's use of geospatial tools offers a scalable approach for assessing ecological health in other river basins and regions facing environmental pressures. This research underscores the critical role of monitoring long‐term ecological changes to inform policy interventions and promote sustainable development in vulnerable ecosystems.