Home
A JFSP Fire Science Exchange Network
Bringing People Together & Sharing Knowledge in the Northern Rockies

LiDAR-Based Wildfire Prevention in WUI: The Automatic Detection, Measurement and Evaluation of Forest Fuels

Author(s): Marta Fernández-Álvarez, Julia Armesto, Juan Picos
Year Published: 2019
Description:

This paper describes a methodology using LiDAR point clouds with an ultra-high resolution in the characterization of forest fuels for further wildfire prevention and management. Biomass management strips were defined in three case studies using a particular Spanish framework. The data were acquired through a UAV platform. The proposed methodology allows for the detection, measurement and characterization of individual trees, as well as the analysis of shrubs. The individual tree segmentation process employed a canopy height model, and shrub cover LiDAR-derived models were used to characterize the vegetation in the strips. This way, the verification of the geometric legal restrictions was performed automatically and objectively using decision trees and GIS tools. As a result, priority areas, where wildfire prevention efforts should be concentrated in order to control wildfires, can be identified.

Citation: Fernández-Álvarez M, Armesto J, Picos J. 2019. LiDAR-Based Wildfire Prevention in WUI: The Automatic Detection, Measurement and Evaluation of Forest Fuels. Forests, 10(2), 148. https://doi.org/10.3390/f10020148
Topic(s): Mapping, Fuels, Fuels Inventory & Monitoring
Ecosystem(s): None
Document Type: Book or Chapter or Journal Article
NRFSN number: 19311
Record updated: Apr 10, 2019