Spatiotemporal Changes of the Forest Cover in Northeastern Ghat Zone of Odisha, India Using Multi-Year Landsat Data

Forests are essential to the terrestrial ecosystem, which supports a sustainable way of life and economy for people. As a result of their ability to capture atmospheric carbon dioxide and mitigate its worldwide consequences, forests are crucial for halting climate change. In light of this context, the current study’s objective is to assess the changes in Land Use & Land Cover (LULC) and forest cover across the North Eastern Ghat Zone (NEGZ) of Odisha, India, from 1990 to 2020. Firstly, multi-year preprocessed Landsat data at ten-year intervals (1990, 2000, 2010 and 2020) were collected using cloud computing Google Earth Engine (GEE) platform, and the entire region was divided into five separate classes based on the Normalized Difference Vegetation Index (NDVI) thresholds viz., Very Dense Forest (VDF), Moderately Dense Forest (MDF), Open Forest (OF), and Non- Forest Land (NFL). Through the use of Supervised & Unsupervised techniques of classification, five main LULC categories were also established, viz., Agriculture, Barren Lands, Forest, Settlements, and Water Bodies. The results infer that the forest cover was reduced by 20%, wherein a gradual decrease in the VDF area by 14.21% of the NEGZ was significant during the study period. Unlike the VDF dynamics, the OF coverage showed a slight increase of 4.56% of NEGZ. On the contrary, the settlement area increased by about 130%. However, this study could infer that the expansion of settlements due to population hike is the primary driver of deforestation and forest fragmentation (because the population growth and increased settlements accounted for 97% and 93% of the variability in forest cover). Additionally, it was found that the variation in the forest cover could explain 45% variability of the mean air temperature as indicated by the coefficient of determination. Therefore, by placing special focus on the aforementioned findings and conclusions, we may conclude that the current study may contribute to research on forest management, climate change mitigation, and sustainable development.