Modeling Airborne Laser Scanning Data for the Spatial Generation of Critical Forest Parameters in Fire Behavior Modeling. Riaño, D., Meierc, E., Allgöwerc, B., Chuvieco, E., & Ustin, S. L. Remote Sensing of Environment, 86(2):177–186, July, 2003. doi abstract bibtex Methods for using airborne laser scanning (also called airborne LIDAR) to retrieve forest parameters that are critical for fire behavior modeling are presented. A model for the automatic extraction of forest information is demonstrated to provide spatial coverage of the study area, making it possible to produce 3-D inputs to improve fire behavior models. [] The Toposys I airborne laser system recorded the last return of each footprint (0.30-0.38 m) over a 2000 m by 190 m flight line. Raw data were transformed into height above the surface, eliminating the effect of terrain on vegetation height and allowing separation of ground surface and crown heights. Data were defined as ground elevation if heights were less than 0.6 m. A cluster analysis was used to discriminate crown base height, allowing identification of both tree and understory canopy heights. Tree height was defined as the 99 percentile of the tree crown height group, while crown base height was the 1 percentile of the tree crown height group. Tree cover (TC) was estimated from the fraction of total tree laser hits relative to the total number of laser hits. Surface canopy (SC) height was computed as the 99 percentile of the surface canopy group. Surface canopy cover is equal to the fraction of total surface canopy hits relative to the total number of hits, once the canopy height profile (CHP) was corrected. Crown bulk density (CBD) was obtained from foliage biomass (FB) estimate and crown volume (CV), using an empirical equation for foliage biomass. Crown volume was estimated as the crown area times the crown height after a correction for mean canopy cover.
@article{rianoModelingAirborneLaser2003,
title = {Modeling Airborne Laser Scanning Data for the Spatial Generation of Critical Forest Parameters in Fire Behavior Modeling},
author = {Ria{\~n}o, D. and Meierc, Erich and Allg{\"o}werc, Britta and Chuvieco, Emilio and Ustin, Susan L.},
year = {2003},
month = jul,
volume = {86},
pages = {177--186},
issn = {0034-4257},
doi = {10.1016/s0034-4257(03)00098-1},
abstract = {Methods for using airborne laser scanning (also called airborne LIDAR) to retrieve forest parameters that are critical for fire behavior modeling are presented. A model for the automatic extraction of forest information is demonstrated to provide spatial coverage of the study area, making it possible to produce 3-D inputs to improve fire behavior models.
[] The Toposys I airborne laser system recorded the last return of each footprint (0.30-0.38 m) over a 2000 m by 190 m flight line. Raw data were transformed into height above the surface, eliminating the effect of terrain on vegetation height and allowing separation of ground surface and crown heights. Data were defined as ground elevation if heights were less than 0.6 m. A cluster analysis was used to discriminate crown base height, allowing identification of both tree and understory canopy heights. Tree height was defined as the 99 percentile of the tree crown height group, while crown base height was the 1 percentile of the tree crown height group. Tree cover (TC) was estimated from the fraction of total tree laser hits relative to the total number of laser hits. Surface canopy (SC) height was computed as the 99 percentile of the surface canopy group. Surface canopy cover is equal to the fraction of total surface canopy hits relative to the total number of hits, once the canopy height profile (CHP) was corrected. Crown bulk density (CBD) was obtained from foliage biomass (FB) estimate and crown volume (CV), using an empirical equation for foliage biomass. Crown volume was estimated as the crown area times the crown height after a correction for mean canopy cover.},
journal = {Remote Sensing of Environment},
keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-4412594,environmental-modelling,forest-fires,forest-resources,modelling,remote-sensing,wildfires},
lccn = {INRMM-MiD:c-4412594},
number = {2}
}
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