Understanding forest fragmentation dynamics and identifying drivers for forest cover loss using random forest models to develop effective forest management strategies in North-East India
Deforestation poses a significant conservation challenge on a global scale, endangering both plant life and the interconnected animal communities reliant upon it. This loss is primarily propelled by anthropogenic activities, emphasizing the need for meticulous monitoring tools tailored to the intric...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-06-01
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| Series: | Results in Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123025007170 |
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| Summary: | Deforestation poses a significant conservation challenge on a global scale, endangering both plant life and the interconnected animal communities reliant upon it. This loss is primarily propelled by anthropogenic activities, emphasizing the need for meticulous monitoring tools tailored to the intricacies of regional socio-political and cultural dynamics influencing forest loss within specific regions. This study utilized advanced remote sensing technologies, employing Landsat imagery on the Google Earth Engine platform, to generate detailed Land Use and Land Cover (LULC) classifications spanning three decades (1991–2021), revealing significant landscape changes over time. Forest fragmentation patterns and loss were analyzed using spatial metrics derived from FRAGSTATS to assess ecological impacts. Furthermore, spatial and non-spatial Random Forest regression techniques were employed to identify key drivers of forest loss within the landscape. The assessment of deforestation identifies a significant ∼9% reduction, particularly in the plains of Assam, Manipur, and Meghalaya, with substantial changes in AREA, PERIM, and SHAPE (p < 0.05). Landscape fragmentation analysis revealed the susceptibility of peripheral forest zones and forest perforation to rapid deforestration. Human population density, forest-to-population ratio, and mean temperature emerged as key drivers of forest loss, with elevated temperatures augmenting forest fire risks. Conversely, rugged terrain and high rainfall negatively impacted forest loss in less inaccessible areas of the region. Our study underscores the urgent need for evidence-based conservation strategies and sustainable land use practices in the North East Indian Region. By integrating remote sensing and modeling techniques, our approach offers a template for regional analysis worldwide, informing policy-making and ground-based management efforts to safeguard terrestrial forest ecosystems. |
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| ISSN: | 2590-1230 |