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Applications of Airborne Laser Scanning in Forest Fuel Assessment and Fire Prevention

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Forestry Applications of Airborne Laser Scanning

Part of the book series: Managing Forest Ecosystems ((MAFE,volume 27))

Abstract

Forest fire management requires accurate, spatially explicit and up-to date information on forest fuels and their vertical structure. Airborne laser scanning (ALS) provides 3-D vegetation models to map accurate fuel properties critical for modelling fire behaviour. Laser point cloud data stratified into height intervals coupled with spectral information can provide accurate fuel type maps, especially if non-parametric classifiers are used. Canopy bulk density (CBD) depends on ALS metrics related to canopy volume and biomass to yield regression models ranging between 0.77 and 0.94 in R2. ALS estimates canopy base height (CBH) after the identification of the gap in the canopy that describes the beginning of the tree crown. Due to laser point density among other factors, CBH for individual trees is usually less accurate than for plots. Penetration through the upper canopy and the low height of the surface fuels combined with a low laser pulse density constrain the estimation of surface canopy height (SCH). ALS together with optical sensors map the above mentioned fuels properties more accurately than with any of these sensors alone due to the synergy of the structural and spectral information collected by each sensor. Despite the fact that most attempts at using ALS for fire management have been focused on characterization of fuels at the pre-fire stage or during the fire, multi-temporal ALS data also have high potential at the post-fire stage to estimate burn severity and vegetation regeneration after fire.

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Acknowledgements

John Gajardo was supported by CONICYT Doctoral Fellowship, Government of Chile. Felix Morsdorf and Rubén Valbuena provided insightful review to improve this chapter. We would also like to thank Joaquín Ramírez and his team from Tecnosylva SL. for generating Fig. 22.1. Linguistic assistance from Richard Hewitt is as well acknowledged.

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    1. Center for Spatial Technologies and Remote Sensing (CSTARS), University of California, Davis, One Shields Avenue, 139 Veihmeyer Hall, Davis, CA, 95616, USA

      John Gajardo, Mariano García & David Riaño

    2. Department of Geography and Geology, University of Alcalá, Alcalá de Henares, 28801, Madrid, Spain

      John Gajardo & Mariano García

    3. Associated Research Unit GEOLAB, University of Alcalá-Spanish National Research Council (CSIC), Alcalá de Henares, 28801, Madrid, Spain

      John Gajardo, Mariano García & David Riaño

    4. Associated Research Unit GEOLAB, University of Alcalá-Spanish National Research Council (CSIC), Albasanz 26-28, 28037, Madrid, Spain

      John Gajardo, Mariano García & David Riaño

    5. Faculty of Forest Sciences, University of Talca, 2 Norte # 685, Talca, Chile

      John Gajardo

    6. Remote Sensing Area, Complutig-University of Alcalá, Alcalá de Henares, 28801, Madrid, Spain

      Mariano García

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    1. School of Forest Sciences, University of Eastern Finland, Joensuu, Finland

      Matti Maltamo

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      Erik Næsset

    3. Department of Forest Sciences, University of Helsinki, Helsinki, Finland

      Jari Vauhkonen

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    Gajardo, J., García, M., Riaño, D. (2014). Applications of Airborne Laser Scanning in Forest Fuel Assessment and Fire Prevention. In: Maltamo, M., Næsset, E., Vauhkonen, J. (eds) Forestry Applications of Airborne Laser Scanning. Managing Forest Ecosystems, vol 27. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-8663-8_22

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