Determining The Forest Fire Risk with Sentinel 2 Images

Forest fires are one of the most important disasters since past. The necessary preventions should be taken promptly to prevent these disasters. Remote sensing, which is a very effective and practical tool, is one of these tools that provide a timely receipt of measures with the development of technology. In this study, a forest fire that started at 07.23.2018 in Athens, in Greece and continued until July 26 was discussed. Mati region where the most loss of life was examined as the study area. Sentinel 2 images were used in order to detect forest fire risk class. Normalized Burn Ratio (NBR), Differenced Normalized Burn Ratio (dNBR), Relativized Burn Ratio (RBR) spectral indices and Normalized Difference Vegetation Index (NDVI) were used in order to determine the forest area damaged by fire and to establish fire risk classes. According to the results of the study, the size of the vegetation area that was destroyed due to fire determined, and the probability of forest fire exposure of these areas established.