Revealing 3D Variations in Forest Fuel Structures in Subtropical Forests through Backpack Laser Scanning

Wildfire hazard is a prominent issue in subtropical forests as climate change and extreme drought events increase in frequency. Stand-level fuel load and forest structure are determinants of forest fire occurrence and spread. However, the current fuel management often lacks the detailed vertical fuel distribution, limiting accurate fire risk assessment and effective fuel policy implementation. In this study, backpack laser scanning (BLS) is used to estimate several 3D structural parameters, including canopy height, crown base height, canopy volume, stand density, vegetation area index (VAI) and vegetation coverage, to characterize the fuel structure characteristics and the vertical density distribution variation in different stands of subtropical forests in China. Through standard measurement by BLS point cloud data, we found that canopy height, crown base height, stand density, and VAI in the lower and middle height strata differed significantly among stand types. Comapre to vegetation coverage, LiDAR derived VAI can better show significant stratified changes in fuel density in the vertical direction among stand types. Among the stand types, conifer-broadleaf mixed forest and C. lanceolata had higher VAI in surface strata than other stand types, while P. massoniana and conifer-broadleaf mixed forests were particularly unique in having higher VAI in the lower and middle height strata, corresponding to the higher surface fuel and ladder fuel in the stand respectively. To provide more informative support for forest fuel management, BLS LiDAR data combined with other remote sensing data was advocated to facilitates the visualization of fuel density distribution and the development of fire risk assessment.