Estimating Ladder Fuels In A Mixed-Oak Forest Using LiDAR

Abstract

Prescribed fire cannot be used as a method to reduce forest fuels in areas of wildland urban interface (WUI).  Instead, mechanical fuel reduction is performed by removing ladder fuels.  Fire managers must estimate ladder fuels to efficiently manage crews and budgets. This study proposes a method of estimating ladder fuels in a mixed oak forest in Northern California applying an adapted ladder fuel index (LFI) to LiDAR data.  The field study consisted of eight circular plots with 11.3 m radius, each plot containing 36 random points. Linear regression was applied to LiDAR height and intensity statistics and achieved good cross-validated model fit for field-measured canopy base height (r² = 0.98), understory height (r² = 0.86), and understory percentage cover (r² = 0.96).  The field-derived LFI was compared to the predicted LFI and achieved a strong coefficient of determination of 0.94.  The LFI was applied to the study area-wide LiDAR dataset using cell sizes of 22.6 m, 67.8 m, and 112.8 m to visualize the LFI distribution.