LiDAR-Based Estimation of Canopy Fuel Parameters of Tree Plantation in Bukidnon, Philippines

Abstract

Forest wildfires in the Philippines are all human-caused. Resource managers are dependent on accurate estimates and spatially accurate forest structure information to govern this kind of phenomena.This study presents methods of using airborne laser scanning data to acquire forest and tree parameters that are critical in modelling forest fire behavior. The study aimed on assessing fuel models of a tree plantation through LiDAR (Light Detection and Ranging) point cloud data. The tree plantation under this study is located in the Municipality of Malitbog, Bukidnon that is managed by Bukidnon Forest Incorporated (BFI). Canopy fuel of Caribbean pine (Pinus caribaea) was determined through calculation of canopy bulk density (CBD), canopy base height (CBH), canopy fuel weight (CFW) and canopy height (CH), which are essential in mapping the spatial distribution and modelling fire behavior. The Canopy Fuel Estimator (CFE) software, developed by researchers from USDA Forest Service, was used in this study. The plantation’s mean value of canopy fuel was extracted from available LiDAR data, which was also compared to the field data. Findings show that Caribbean pine plantation has high CBH (11.8 m), CH (31.5 m), and CBD (1.5 kg/m2). This indicates higher risk of forest fire in the area. Furthermore, field data for canopy fuel (CBH = 17.9 m, CH = 27.9 m, CFW = 2.9 kg/ha, CBD = 0.6 kg/m2) was observed to be close to LiDAR data (CBH = 11.8 m, CH = 31.5, CFW = 1.5 kg/ha, CBD = 1.5 kg/m2). Therefore, this study indicates the reliability of LiDAR data in modeling canopy fuel in a homogenous tree plantation through CFE. The maps produced can be used in fire behavior prediction, fuel reduction treatment prioritization and during active fire elimination.