DYNAMICS OF FOREST LOSS IN NAGALAND, INDIA, 2000 - 2024: A GOOGLE EARTH ENGINE-BASED ANALYSIS
DOI:
https://doi.org/10.53555/e308dj52Keywords:
Forest Cover Loss, Hansen Global Forest Change, Drivers of forest loss, GEE, DeepMind Global DriversAbstract
Forest Cover loss is a crucial driver of environmental degradation. Forest loss has a significant impact on biodiversity and ecosystem services. Despite being the most forested and biologically diverse regions in India, the forests of Northeast India have experienced significant alteration due to growing human pressures. This study evaluates the spatio-temporal patterns of forest cover loss in Nagaland from 2000 to 2024 using the Google Earth Engine (GEE) platform. Annual forest cover loss was assessed using the Hansen Global Forest Change (GFC) v1.12. Proximate drivers of forest loss were examined using the WRI/Google DeepMind Global Drivers of Forest Loss v1.2 dataset, and results were validated against biennial state-level forest cover estimates from the Indian State of Forest Report. The results reveal a cumulative forest loss of approximately 3,646.97 sq. km over the study period. A distinct shift was observed from relatively steady forest loss during 2001-2010 to accelerated deforestation after 2011. The highest forest loss occurred in 2017 and remained consistently high through 2024. Spatial analysis shows that forest loss is unevenly distributed within the eastern and southeastern Nagaland, experiencing the most extensive and concentrated loss. Driver analysis indicates that shifting cultivation is the dominant driver, which accounts for nearly 77% of driver-attributed forest loss, followed by logging. Strong agreement between Hansen-derived forest loss estimates and Forest cover trends from the India State of Forest Report confirms that the observed decline reflects a persistent transformation in Nagaland’s Forest cover. The findings highlight the need for targeted land-use interventions and sustainable forest management strategies to address anthropogenic forest loss in the region.
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