NBR Index-Based Fire Detection Using Sentinel-2 Images and GIS: A Case Study in Mosul Park, Iraq

Abstract

Forest fires lead to severe damage to the environment and human health. Monitoring can be applied using remotely sensed data and in combination with Geographical Information Systems (GIS) based spatial analysis. Lately, Iraq subjected to many forest fires. In this study, the aim was to monitor and detect the burned areas in Mosul Park during the latest period which happened in June 2022. The hypothesis of the study was based on using Sentinel-2 images and the Normalized Burn Ratio (NBR) index. Two images have been used to compare burned areas; one during the fire events and another postfire. as well as, Normalized Difference Vegetation Index (NDVI) map has been used to identify the Park's characteristics. Moreover, Pearson's correlation (r) with Air Quality Index (AQI) was determined during the burning period. GIS-based processes resulted in detecting the area of burning where the burned area was 16.76 hectares and lay in the eastern part of the study area. Pearson correlation with AQI has resulted in 0.92, while the collinearity between the burned areas and AQI was 0.84. Accurate and prompt planning for fire-affected regions is essential for supporting fire affect assessment, calculating environmental losses, determining planning strategies, and monitoring vegetation recovery.