Assessment of Natural Mixed Forest Recovery in Northeastern Japan Three Years Post-Wildfire Using Dual UAV-Field Survey

Understanding how forest structure recovers after wildfire specifically the horizontal arrangement of canopies and the vertical layering of vegetation is essential for guiding long-term forest management. Yet in natural mixed forests, this assessment is inherently difficult: structural complexity is high, and the different tree species often respond to fire in markedly different ways. In this study, we tracked three-year post-fire regeneration trajectories in northeastern Japan by pairing UAV-based multispectral imaging with ground-based field surveys. Replying strictly on the post-fire data, vegetation indeces derived from UAV imagery were threshold based on the remaining green canopy cover and localized charring to classify the burend area into distinct burn severity classes. Vegetation indices derived from UAV imagery allowed us to classify the burned area into distinct recovery levels. In severely burned plots, these indices clearly captured the rapid expansion of pioneer shrubs and the regreening of open ground. However, in partially burnt stands where a dense overstory survived, the canopy foliage masked the spectral signal from the forest floor, making it impossible to separate understory regrowth from surviving tree crowns with remote sensing alone. To move beyond surface greenness and examine genuine tree regeneration, we conducted field surveys measuring understory seedling density, sapling height, and species-specific mortality for the two dominant trees. Our dual-scale remote sensing approach demonstrates that while heavily burned areas quickly turn green again, the critical regeneration of canopy trees is strongly shaped by the environmental conditions created under partially surviving overstories.