Assessing Land Cover Shifts and Fire Impact in Uttarakhand (2018-2024): A Cloud-based Geospatial Solution Using GEE and Dynamic World Data

Abstract

In Uttarakhand, the 2024 forest fire season has seen a dramatic rise in outbreaks, marking one of the most severe incidents in recent years. Effective environmental management in ecologically fragile areas like Uttarakhand depends on analysing land cover changes and fire intensity. This article introduces a web-based tool that leverages cloud geospatial analytics to evaluate forest fire severity and land cover shifts in Uttarakhand, India. The application, built on Google Earth Engine (GEE), combines multi-temporal Sentinel-2 satellite imagery, Dynamic World land cover probability data, and FIRMS active fire alerts to provide near-real-time monitoring. The platform utilizes probabilistic land cover change detection and an enhanced Difference Normalized Burn Ratio (dNBR) method, specifically adapted for Himalayan Forest conditions. Four distinct goals are addressed by this study's automated cloud-based platform for environmental monitoring in Uttarakhand, India:  (1) To examine changes in land cover in Uttarakhand between 2018 and 2024, (2) Map and evaluate yearly fire incidents in Uttarakhand between 2018 and 2024, (3) Use spectral indices to assess burn severity within 10 km of a user-selected point, and (4) Create a time series analysis of changes in land cover for a user-selected pixel between 2018 and 2024. The study uses Google Earth Engine to combine FIRMS active fire records, Dynamic World land cover data, and multi-temporal Sentinel-2 imagery.  The increase of built-up areas by 28%, the stability of forest cover (27,000–29,500 km2) with fire-induced oscillations, and the notable variability in climate-sensitive classes are some of the main results.  Using enhanced dNBR algorithms, users can visualize burn severity within a 10 km radius of a selected point. It also offers interactive visualization features via a dedicated dashboard. At user-specified sites, this framework provides tool for land cover change detection, fire impact assessment, and temporal analysis, providing a solution for near-real-time environmental monitoring.  The findings offer important new information for the sustainable management of Himalayan ecosystems in the face of mounting environmental stress.