Strata-based forest fuel classification for wild fire hazard assessment using terrestrial LiDAR

Yang Chen, Xuan Zhu, Marta Yebra, Sarah Harris, Nigel Tapper

Research output: Contribution to journalArticleResearchpeer-review

12 Citations (Scopus)


Fuel structural characteristics affect fire behavior including fire intensity, spread rate, flame structure, and duration, therefore, quantifying forest fuel structure has significance in understanding fire behavior as well as providing information for fire management activities (e.g., planned burns, suppression, fuel hazard assessment, and fuel treatment). This paper presents a method of forest fuel strata classification with an integration between terrestrial light detection and ranging (LiDAR) data and geographic information system for automatically assessing forest fuel structural characteristics (e.g., fuel horizontal continuity and vertical arrangement). The accuracy of fuel description derived from terrestrial LiDAR scanning (TLS) data was assessed by field measured surface fuel depth and fuel percentage covers at distinct vertical layers. The comparison of TLS-derived depth and percentage cover at surface fuel layer with the field measurements produced root mean square error values of 1.1 cm and 5.4%, respectively. TLS-derived percentage cover explained 92% of the variation in percentage cover at all fuel layers of the entire dataset. The outcome indicated TLS-derived fuel characteristics are strongly consistent with field measured values. TLS can be used to efficiently and consistently classify forest vertical layers to provide more precise information for forest fuel hazard assessment and surface fuel load estimation in order to assist forest fuels management and fire-related operational activities. It can also be beneficial for mapping forest habitat, wildlife conservation, and ecosystem management.

Original languageEnglish
Article number046025
Number of pages16
JournalJournal of Applied Remote Sensing
Issue number4
Publication statusPublished - 1 Oct 2016


  • Canopy height
  • Eucalyptus spp
  • Geographic information system
  • Terrestrial LiDAR scanning

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