Forest Fire Disaster Risk Analysis using Sentinel 2 and Landsat Images Case Study: Al-Qoubaiyat and Tyre regions, Lebanon

Authors : Mohamed Issa, Mohammad Abboud

Pages : 84-94

Doi:10.48053/turkgeo.1177843

View : 16 | Download : 12

Publication Date : 2022-12-30

Article Type : Research

Abstract :Fires are considered a threat to the world with all its components and sectors. Recently, it is noticeable an increase in these fires that hit many countries, especially in Lebanon which is considered a country, rich in forests. A forest fire can be naturally caused by either global warming or high temperature. On the other hand, it may be caused by man-made via factories and glass waste. Fires cause great damage to the environment and may lead to human death. Unfortunately, the fire that broke out in AL-Qoubaiyat and Tyre in Lebanon, have been witnessed and caused great damage to the environment, human losses, etc. In this study, a study of fire risk management for those two study areas, will be analyzed using two types of data (Landsat-8 and Sentinel-2) for AL-Qoubaiyat case study, whereas it will be between (Landsat-7 and Sentinel-2) for the Tyre case study. The Analysis will be done by using the Normalized Burn Ration (NBR), Differenced Normalized Burn Ration (NBR) along with all type of required atmospheric corrections. According to our study, it was found advisable to monitor fire risk management using Sentinel-2 L2A data since the atmospheric correction is already performed on it but for L1C data the Sen2Cor python must be used to apply atmospheric correction. Furthermore, the Sentinel-2 L2A data analysis gave more precise results than Landsat-8 by about 2% in Sour case study and 5.7 % in AL-Qoubaiyat case study. Hoping that this method will help in tracking fires, disaster risk reduction, and help in classifying burn severity accompanied with calculating the area corresponding to each class.
Keywords : GIS, DEM, DRR, Forest Fire, Satellite Remote Sensing, Lebanon, NBR, Burn Index