2026 Volume 46 Issue 3 Pages 227-231
This study examined the relationships between burn severity levels classified from dNBR derived from Sentinel-2 MSI imagery and post-fire canopy height model (CHM) and canopy cover (CC) obtained from airborne LiDAR (LP) data, using the March 2025 wildfire in Minamiku, Okayama City, Japan (total burned area: 486 ha) as a case study. Post-fire airborne LiDAR data were acquired on March 29, 2025. CHM was calculated as the difference between the digital surface model (DSM) and digital elevation model (DEM) at 1 m resolution, and CC was derived by binarizing CHM at a 2 m threshold. Both CHM and CC were resampled to a 10 m grid to match the dNBR pixel size. dNBR was classified into five burn severity levels based on thresholds from Key and Benson (2006). Buildings and roads were excluded using mask polygons derived from base map data. Zonal statistics of CHM and CC were computed for each burn severity level. The results showed a clear decreasing trend in both CHM and CC with increasing burn severity: the Unburned level had a median CHM of 8.3 m and median CC of 1.00, while the Moderate-High level showed values of 3.6 m and 0.77, respectively. Spatial distributions of dNBR and CHM also showed visual correspondence across the study area. These findings indicate that dNBR broadly reflects post-fire changes in canopy height and cover derived from airborne LiDAR data, even in Japanese wildfire conditions.
