AI-Assisted Spatio-Temporal Analysis of Forest Cover and Carbon Dynamics in Northeast India: A Remote Sensing and GIS Approach

Arman Khan

Keywords: Remote sensing, Geographic Information Systems, Artificial intelligence, Machine learning, Forest cover change, Carbon dynamics, Aboveground biomass, Vegetation indices, Land use land cover, Northeast India

TL;DR: AI‑assisted remote sensing and GIS are used to track forest‑cover change and estimate carbon stocks across Northeast India, pinpointing hotspots for nature‑based climate resilience interventions.

Abstract: Northeast India, located within the Eastern Himalaya and Indo‑Burma biodiversity hotspots, is undergoing rapid land‑use and land‑cover transformation driven by agricultural expansion, infrastructure growth, urbanisation, and shifting cultivation. These changes threaten regional ecological stability and complicate traditional, ground‑based monitoring approaches, which are labour‑intensive and poorly suited to large, inaccessible terrains. This study integrates Geographic Information Systems, multi‑temporal satellite imagery, and machine learning to automate the spatio‑temporal analysis of forest cover and carbon dynamics in selected landscapes across Assam, Arunachal Pradesh, Manipur, and Mizoram. Using imagery from Landsat and Sentinel missions, Support Vector Machine classification is combined with vegetation indices such as NDVI, SAVI, and MSAVI to map land‑cover transitions, quantify forest degradation, and estimate aboveground biomass. The results reveal substantial localised declines in forest area and corresponding increases in built‑up and bare‑soil surfaces, alongside pockets of regreening associated with plantations and community‑managed forests. Synthesised biomass data indicate high carbon storage potential in intact and traditionally protected forests, underscoring the importance of indigenous conservation practices. The findings demonstrate that AI‑enabled geospatial workflows provide a scalable decision‑support framework for identifying ecological hotspots, prioritising restoration zones, and designing nature‑based solutions that strengthen climate resilience in Northeast India.

Submission Number: 10