Assessing Spatio-Temporal Patterns of Deforestation in Nagaland for 2014–2024 Using Geospatial Techniques

Registration ID: IJNRD_313390

Published ID: IJNRD2603293

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Ankita Tewatia

Spatio-Temporal Pattern, Deforestation, Geospatial Techniques

This study investigates the spatio-temporal dynamics of deforestation in Nagaland, India, over a decade (2014–2024) using geospatial techniques such as satellite-based remote sensing, Normalized Difference Vegetation Index (NDVI) computation, and change detection analysis. Situated in the ecologically sensitive belt of Northeast India, Nagaland has experienced accelerating landscape modification due to anthropogenic and environmental pressures. The study aims to quantify forest-cover transitions, evaluate vegetation health, identify deforestation hotspots, and explore correlations with topography and population density. Multi-temporal Landsat 8 (2014) and Landsat 9 (2024) imagery were classified through supervised classification (Maximum Likelihood Algorithm) into six land-use/land-cover (LULC) categories—dense forest, open forest, scrub, agriculture, built-up area, and water bodies. NDVI was computed to assess vegetation vigor and spatial health, while post-classification comparison and NDVI differencing were employed for change detection. The analysis reveals a 10.6% decline in dense forest cover (−806 km²) alongside substantial increases in open forest (+8.6%), scrubland (+24.2%), and built-up area (+42.9%). NDVI values decreased from 0.58 to 0.47, indicating a deterioration in canopy density and photosynthetic activity. Deforestation hotspots were predominantly located in Dimapur, Mon, and Tuensang, regions of high population density and infrastructural expansion. Statistical correlation confirmed a strong positive relationship (r = +0.81) between population density and forest loss, while elevation exhibited an inverse association. The study interprets deforestation as a spatial–ecological process characterized by feedback loops between socio-economic development and environmental degradation. The transition from dense forest to open and degraded vegetation signifies a loss of ecosystem resilience, carbon storage capacity, and biodiversity connectivity. Ecological implications include increased soil erosion, hydrological imbalance, and reduced carbon sequestration potential (estimated at 40–45 Mt CO₂e). Socio-economically, forest depletion has intensified livelihood insecurity, particularly among indigenous and agrarian communities reliant on shifting cultivation (jhum). Policy recommendations emphasize geospatial monitoring, community-based forest governance, and slope-based land-use zoning to restore ecological balance. Integration of remote sensing technologies with participatory management frameworks is proposed to enhance adaptive governance and align with national forest and climate commitments (REDD+ and NDCs). The study contributes both methodologically and conceptually to the regional discourse on sustainable mountain forest management by demonstrating how deforestation in Nagaland embodies an ongoing forest transition without equilibrium. It underscores the urgency of reimagining forest conservation through a spatially intelligent and socially inclusive approach.

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Ankita Tewatia (March-2026). Assessing Spatio-Temporal Patterns of Deforestation in Nagaland for 2014–2024 Using Geospatial Techniques. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 11(3), c860-c874. https://ijnrd.org/papers/IJNRD2603293.pdf

Volume 11 Issue 3, March-2026

Pages : c860-c874

Paper Reg. ID: IJNRD_313390

Published Paper Id: IJNRD2603293

Research Area: Humanities All

Author Type: Indian Author

Country: Faridabad, Haryana, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2603293.pdf

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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

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