A Review on Remote Sensing Based Forest Vegetation Health Assessment: Bangladesh Perspective

Abstract

This paper aims to present a critical review of the published scientific papers that have addressed the issue of forest health in Bangladesh using remote sensing techniques. A systematic review approach has been followed in this study where all the available papers on the application of remote sensing to assess the forest health vegetation condition of Bangladesh were considered for review. That search resulted in the selection of 48 papers. The findings indicate that remote-sensing-based studies have focused mostly on forest cover mapping and change, and landcover change detection rather than assessing the overall health condition of those forests. Also, among the major forests of the country, most studies have been conducted on Mangrove (Sundarban) forests whereas the least number of studies were found for the forests in the Chittagong Hill Tracts Forests areas and those studies were mostly conducted after the Rohingya crisis. Landsat satellite products have been most extensively used for their broader temporal resolution and availability while a few studies have worked with other products like MODIS, Sentinel, SPOT, etc. The application of advanced classification approaches incorporating machine learning algorithms and ground validation has shown effectiveness for investigating the forest or overall ecosystem health in a more detailed way. Although the RS techniques are increasingly used to study the forests of Bangladesh, forest health-specific and indicator-based research is yet to be done which can ensure sustainable forest management. The Dhaka University Journal of Earth and Environmental Sciences, Vol. 12(1), 2023, P 107-121