Investigating coastal ecosystem health in Bangladesh using machine learning and remote sensing.

Abstract

Ecosystem health is a measure that is used to describe the condition of the ecosystem. The stability of the ecosystem and sustainable growth are represented by ecosystem health which covers the overall condition of the environment. The loss of habitat and deterioration of ecosystem services are the outcomes of coastal urbanization and ecosystem health damage. Potential natural disasters and biodiversity loss are happening more frequently and intensely which makes an emerging issue of environmental resilience. That's why ecosystem health assessment is must. The 1,47,570 km2 of Bangladesh has 47,201 km2 of coastal zone consisting of 19 districts which is 32% of the country and about 43.8 million people live here. This study aims to assess the ecosystem health of 2013 and 2023 and to investigate the change in the coastal ecosystem health in evaluating with past and present conditions of the ecosystem. For assessment, a random forest machine learning model has been used in conjunction with remote sensing and GIS due to its high accuracy and efficiencies. The PSR (Pressure-State-Response) model has been used in this investigation. This study reveals that the ecosystem health of 2023 deteriorated mostly than in 2013. About 19.76% of the lower ecosystem health area of coastal zone has been increased over the decades. In addition, 6.92% and 12.84% of higher and medium ecosystem health areas have been degraded accordingly. The Satkhira district had higher ecosystem health and Chittagong had lower ecosystem health in 2013; whereas in 2023, it became Narail and Jhalokathi accordingly. The point is that the ecosystem is down falling from the time on. This concerning factor can assist the body in making decisions on how should interact with the environment with adequate controlling crucial measures to heal the environment's health.