Land use classification and change detection by using multi-temporal remotely sensed imagery: The case of Chunati wildlife sanctuary, Bangladesh

Abstract

The degraded Chunati wildlife sanctuary (CWS) has undergone various land use changes since 1980s. In this study, land use changes of CWS were assessed from 2005 to 2015 by using Landsat TM and Landsat 8 OLI/TIRS images. The ArcGIS v10.1 and ERDAS Imagine v14 were used to process satellite imageries and assessed quantitative data for land use change assessment of this study area. Maximum likelihood classification algorithm was used in order to derive supervised land use classification. It was found that about 256ha of degraded forest area had been increased within 10years (2005–2015) and the annual rate of change was 25.56%. Another 159ha of naturally forested land had been changed to other land uses having an (−) annual rate of change of 15.88%. The overall supervised classification accuracy was found 92.16% for 2015, 86.15% for 2010, and 83.96% for 2005 with Kappa values of 0.89, 0.82, and 0.81 for 2015, 2010, and 2005, respectively and these were fairly satisfactory. The results of this study would be helpful to plan and implement important management decisions in order to conserve the rich biodiversity of Chunati wildlife sanctuary.