Analysis of Normalized Difference Vegetation Index (NDVI) of the Chittagong Hill Tracts from 1991 to 2021 Using Remote Sensing Tools

The Chittagong Hill Tracts (CHT) is the only widespread hilly regions of Bangladesh with distinctive landscape and profuse biodiversity. This study illustrates the variation of vegetative coverage of the CHT by examining Landsat images in the period 1991–2021. Land cover maps were created using the Normalized Difference Vegetation Index (NDVI) model with six classes—water, built-up area, barren land, agriculture and grassland, sparse vegetation, and dense vegetation. The NDVI was calculated in Google Earth Engine (GEE) using Landsat 8 and Landsat 5 images and then classified in ArcGIS 10.4. The results revealed that the proportion of built-up area in Rangamati, Khagrachari, and Bandarban climbed from 1.42% to 5.5%, 0.1% to 3.76%, and 0.9% to 1.7% from 1991 to 2021, respectively. At the same time, the percentage of dense vegetation declined from 84.1% to 54.33%, 91.72% to 49.69%, and 96% to 63.4% in those areas, respectively. On the other hand, a significant amount of sparse vegetation rose from 5.43% to 26.23%, 5.63% to 40.49%, and 2.4% to 29.2% between 1991 and 2021 in the same places, correspondingly. Other significant changes were observed in agriculture and grassland, which changed from 2.39% to 7.7% in Rangamati, 1.83% to 9.93% in Khagrachari, and 1% to 6.2% in Bandarban, whereas barren land increased in Rangamati from 0.59% to 1.96%, in Khagrachari from 0.29% to 0.62%, and in Bandarban from 0.2% to 0.7%. In Bandarban and Rangamati, the proportion of water remained largely unchanged, but in Khagrachari, it dropped largely from 3.21% in 2001 to 0.26% in 2021. The Chittagong Hill Tracts (CHT) in Bangladesh has experienced considerable changes in vegetation cover and quality over the past three decades, as revealed by an analysis of the Normalized Difference Vegetation Index (NDVI) in this study. Overall, this study in the CHT region from 1991 to 2021 has the potential to have important academic and social implications by providing vital information for environmental monitoring, agricultural planning, disaster management, and further academic research.