WILDFIRE DAMAGE ASSESSMENT USING MULTI-TEMPORAL SENTINEL-2 DATA
Keywords: Wildfire damage assessment, Multi-temporal image analysis, OBIA, Change detection, Sentinel-2
Abstract. Recently, the drastic climate changes have increased the importance of wildfire monitoring and damage assessment as well as the possibility of wildfire occurrence. Estimation of wildfire damage provides the information on wildfire-induced ecological changes and supports the decision-making process for post-fire treatment activities. For accurate wildfire damage assessment, the discrimination between disaster-induced and natural changes is crucial because they usually coupled together.
In this study, Sentinel-2 images were employed to assess the damage from a wildfire, which occurred in the coniferous forest of Gangneung, Gangwon Province, South Korea on April 2019. The images were captured from both Sentinel-2A and -2B, shortening the temporal interval of available pre- and post-fire images. Multi-temporal image analysis was performed in both object and pixel-based with two commonly used spectral indices, NDVI and NBR. Additional image pair from the same period of 2018 was used to distinguish the fire-affected regions from the naturally changed area and compared with the results from using only one pair of images from 2019. The experimental results showed that the change detection performance could be affected by the number of image pairs and spectral indices used to discriminate burned region from unburned region. Thus it verified the significance of adequately employing annual multi-pair satellite images for wildfire damage assessment.