Forest Change Detection Using Google Earth Engine: A Temporal Analysis of Shirani District

Abstract

Forest fires are a common and devastating natural disaster that causes widespread damage to forest vegetation and poses significant threats to ecosystems. Detecting and monitoring forest fires are crucial for mitigating their impact on the environment and human communities. This research paper focuses on remotely monitoring the change detection in the Sherani Balochistan Pine Nut Forest, which experienced extensive fires, resulting in substantial damage to the Pine Nut crop. Being the world’s largest Pine Nut crop, this event has significant implications for global nut crop production. The proposed solution utilizes remote sensing techniques to detect major changes in the Pine Nut Forest, with images depicting the Sherani forest fire collected from Landsat 9 satellite imagery. It involves actual fire detection, monitoring of damaged areas, and risk hazard analysis. The research employs temporal analysis, which examines the burned area at different time series to observe changes in the geographic area and potential loss of forest cover. Satellite imagery is obtained through the GEE for geospatial analysis, using Landsat data with a spatial resolution of 30 meters for improved comparison and collation of semi-centennial forest data. The approach involves the calculation of indices for the Pine Nut Forest using the NBR and dNBR. These indices help identify the extent of affected land and the severity of the burn. By utilizing this novel approach, the forest department can effectively detect changes in land and climate, enabling better decision-making based on the collected data. Overall, this research contributes to improved forest fire management and conservation efforts.