Evaluating Unmanned Aerial Vehicle Images for Estimating Forest Canopy Fuels in a Ponderosa Pine Stand

Margaret Moore,Patrick Shin,Andrea Thode,Temuulen Sankey

doi:10.3390/rs10081266

Abstract

Forests in the Southwestern United States are becoming increasingly susceptible to large wildfires. As a result, forest managers are conducting forest fuel reduction treatments for which spatial fuels and structure information are necessary. However, this information currently has coarse spatial resolution and variable accuracy. This study tested the feasibility of using unmanned aerial vehicle (UAV) imagery to estimate forest canopy fuels and structure in a southwestern ponderosa pine stand. UAV-based multispectral images and Structure-from-Motion point clouds were used to estimate canopy cover, canopy height, tree density, canopy base height, and canopy bulk density. Estimates were validated with field data from 57 plots and aerial photography from the U.S. Department of Agriculture National Agriculture Imaging Program. Results indicate that UAV imagery can be used to accurately estimate forest canopy cover (correlation coefficient (R2) = 0.82, root mean square error (RMSE) = 8.9%). Tree density estimates correctly detected 74% of field-mapped trees with a 16% commission error rate. Individual tree height estimates were strongly correlated with field measurements (R2 = 0.71, RMSE = 1.83 m), whereas canopy base height estimates had a weaker correlation (R2 = 0.34, RMSE = 2.52 m). Estimates of canopy bulk density were not correlated to field measurements. UAV-derived inputs resulted in drastically different estimates of potential crown fire behavior when compared with coarse resolution LANDFIRE data. Methods from this study provide additional data to supplement, or potentially substitute, traditional estimates of canopy fuel.

Highlights

The Southwestern United States is home to the largest contiguous ponderosa pine (Pinus ponderosa) forest in the world [1,2]
We focused on a 12.14 ha area that has been identified by the city of Flagstaff as high priority for fuels treatment and mechanical thinning, due to its close proximity to residential structures, and is located in Phase 1 of a forest fuels reduction project known as the Flagstaff Watershed Protection Project (FWPP)
The unmanned aerial vehicle (UAV) SfM point cloud-derived tree density estimates were first compared with field-based measurements in each density class

Summary

Introduction

The Southwestern United States is home to the largest contiguous ponderosa pine (Pinus ponderosa) forest in the world [1,2]. The southwestern ponderosa pine forests serve an ecologically important role by providing biodiversity, wildlife habitat, carbon storage, and sequestration functions, as well as ecosystem services for the surrounding communities. In these forests, fire suppression, heavy grazing, logging, and climate change have created increased susceptibility to high-intensity crown fires, putting the forest ecosystems and neighboring communities at risk [1,3,4,5]. The forests that were naturally maintained by frequent low-intensity fires are characterized by an overabundance of forest fuel [8,9,10,11]

Objectives

Methods

Results

Discussion

Conclusion