Remote sensing-based changes in the Ukhia Forest, Bangladesh

Forest cover and its dynamic nature study are mandatory for the environmental, socio-economic as well as political actions. In the context of Bangladesh, the significance of forest-related research has been created new attention for the recent large amount of woodland degradation in the protected forest zone of Ukhia, Cox’s Bazar. This study illustrates a document to interpret multi-temporal Landsat 8 OLI, Sentinel 2A, and 2B imageries for detecting the dynamic changes of forest cover of Ukhia using spectral signatures by image analysis and GIS approaches. These data have been collected from the USGS earth explorer site for the years 2014, 2015, 2016, 2017, and 2018 respectively, and quantified the changes over 5 years. Image fusion technique i.e., NNDiffuse was applied based on the 15 m panchromatic bands of the same sensor to enhance the spatial resolution of Landsat 8. After that, the processed images were subject to supervised classification in ERDAS IMAGINE 2016 using the maximum likelihood technique to detect the forest cover change. By image interpretation, the land use and land covers of the study area were classified into four major classes i.e., Forest, Non-Forest, degraded land, and water bodies. The post-classification forest cover changes maps from 2014 to 2018 have been illustrated a distinguished decline of a large portion of about 82% of the forest in Ukhia. The total net loss of forest land has been calculated as 6.6 sq. miles over 5 years. The accuracy assessment also reported high classification accuracies of 84.00%, 83.81%, 88.99%, 93.20% and 91.00% with overall kappa statistics of 0.69, 0.67, 0.80, 0.85, and 0.85 respectively. Through the assessment of classified image and field data, it has been observed that these forest lands are destroyed for making shelters, roads, creating water sources, camp offices, schools, and other infrastructures for Rohingya refugees in Ukhia that is mapped as deforested land almost 8.02 sq. miles. This research aimed to assess the forest cover dynamics as well as provide an insight into land-use patterns, thus screening the hotspots of forest degradation in Ukhia, Bangladesh.