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Forests 2019, 10(2), 148; https://doi.org/10.3390/f10020148

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

Forestry Engineering School, A Xunqueira Campus University, 36005 Pontevedra, Spain
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Received: 17 December 2018 / Revised: 6 February 2019 / Accepted: 9 February 2019 / Published: 11 February 2019
(This article belongs to the Section Forest Inventory, Quantitative Methods and Remote Sensing)
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Abstract

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. View Full-Text
Keywords: forest fire; LiDAR; automatic measuring; tree characterization; shrub evaluation forest fire; LiDAR; automatic measuring; tree characterization; shrub evaluation
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Fernández-Álvarez, M.; Armesto, J.; Picos, J. LiDAR-Based Wildfire Prevention in WUI: The Automatic Detection, Measurement and Evaluation of Forest Fuels. Forests 2019, 10, 148.

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