Introduced by the development organizations, in the early nineties of the twentieth century, the concept of good governance emerged as a powerful tool of government management. The term Disaster Management has also been introduced in Bangladesh in the contemporary period. However, Bangladesh is observing the lack of good governance being an obstacle to disaster management. Without ensuring good governance the rise of the death toll due to natural as well as human-induced disasters such as floods, cyclones, river erosion, drought, fire incidents, launch accidents, or building collapse could not be prevented. This study has particularly focused on revealing the relation of landslides to the eight significant characteristics of good governance. The researchers have collected both the primary and the secondary data and have adopted a qualitative method for analysing the data retrieved from Chattogram metropolitan area (previously known as Chittagong) during the research. This study has tried to establish the argument that, lack of the characteristics of good governance including transparency, accountability, rules of law, participation, responsiveness, consensus, inclusiveness, efficiency, and effectiveness is responsible for occurring disasters like landslides. Thus, this study is expected to open a new edge in academic and development research. This will also help the policymakers cope with the guidelines to create necessary policies. Social Science Review, Vol. 39(1), June 2022 Page 35-55

The study of land use/land cover dynamics has been increasingly important in the research of earth surface natural resources. The normalized difference vegetation index (NDVI) is a widely used method for observing land use/land cover change detection. The surface land resources are easily interpreted by computing their NDVI. This study aimed at analyzing Land Use/Land Cover (LULC) changes between 1977 and 2019 in the Rangamati district, Bangladesh using reclassify the NDVI values of the Landsat satellite image and identifying the main drivers to change LULC by household survey. Five different years of Landsat images were used to extract the NDVI values January of 1977, 1989, 2000, 2011 and 2019. The NDVI values are initially computed using the user define method to reclassify the NDVI map to create land use land cover map and change detection. The highest NDVI value was found in 1977 (0.88) which indicates healthy vegetation at that time and thereafter it followed a decreasing trend (0.79 in 1989, 0.74 in 2000, 0.71 in 2011 and 0.53 in 2019) which shows a rapid vegetation cover change in the study area. Analysis of the household survey revealed that population growth, migration from plain land, rapidly urbanization, Kaptai Dam, migration policy of government, high land price, unplanned development, development of tourism industry, firewood collection and poverty have been identified as the major drivers of LULC changes in the study area. Furthermore, analysis of NDVI confirms that the forest vegetation area is being decreased and settlement area and sparseness of vegetation are being increased. The accuracy of the NDVI-based classified images is assessed, using a confusion matrix where overall classification accuracy and Kappa coefficient are computed. The overall classification accuracy was 84% - 90% with corresponding Kappa statistics of 80% - 88% for TM and OLI-TIRS images, respectively. The study serves as a basis of understanding of the LULC changes in the southeastern part of Bangladesh. Bangladesh J. Agri. 2019-2021, 44-46: 127-140