Modeling airborne laser scanning data for the spatial generation of critical forest parameters in fire behavior modeling

Riaño, David; Meier, Erich; Allgöwer, Britta; Chuvieco, Emilio; Ustin, Susan L.

doi:10.1016/s0034-4257(03)00098-1

Cited by 235 publications

(177 citation statements)

References 37 publications

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“…Derivation of the apparent foliage profile from LiDAR observations has been well described (Lovell et al 2003, Riano et al 2003. The probability of a gap from the top of the canopy to a given height, z, can be estimated by summing the total number of hits down to z and comparing them to the total number of independent LiDAR shot (N):…”

Section: Lidar Based Measures Of Canopy Structurementioning

confidence: 99%

“…In this research, we modify the Lefsky et al (1999) computations of canopy volume profile to allow their prediction from discrete (first and last return) LiDAR data. To enable this, each of the 20m x 20m plots were subset into sixteen 5m x 5m windows and all LiDAR non-ground returns binned within of these 25 m² (5 x 5) plot subsets The number of returns within each of the sub-plots at 1 m height intervals were then counted and corrected according to Lefsky et al (1998) and Riano et al (2003). A sub plot size of 25m² is a compromise between obtaining a sufficient number of ground returns required for the correction of small footprint LiDAR returns, and having enough subplots within the area to characterize the stand.…”

Section: Lidar Canopy Volume Profilesmentioning

confidence: 99%

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Estimating canopy structure of Douglas-fir forest stands from discrete-return LiDAR

Coops

Hilker

Wulder

et al. 2007

Trees

311

223

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Section: Lidar Based Measures Of Canopy Structurementioning

confidence: 99%

Section: Lidar Canopy Volume Profilesmentioning

confidence: 99%

Estimating canopy structure of Douglas-fir forest stands from discrete-return LiDAR

Coops

Hilker

Wulder

et al. 2007

Trees

311

223

View full text Add to dashboard Cite

“…Traditionally, interpretation of aerial photography coupled with field data has been the primary method used to map fire-related tree crown variables (Riano et al, 2003) such as crown bulk density, crown closure, and canopy height. More recently empirical methods, which are less labor intensive, have been used to estimate these variables from Landsat thematic mapper (TM) and systeme probatoire d'observation de la terre (SPOT) high resolution visible (HRV) data (Riano et al, 2003).…”

Section: Remote Sensing Of Crown Fuelsmentioning

confidence: 99%

“…More recently empirical methods, which are less labor intensive, have been used to estimate these variables from Landsat thematic mapper (TM) and systeme probatoire d'observation de la terre (SPOT) high resolution visible (HRV) data (Riano et al, 2003). For example, Franklin et al (2003) mapped various stand attributes, including canopy height and crown closure, through implementation of empirical relationships between single band Landsat reflectance and canopy characteristics.…”

Section: Remote Sensing Of Crown Fuelsmentioning

confidence: 99%

“…Remote sensing-based fuels mapping has typically employed one of the Landsat sensors (MSS, TM, or ETM+) to map fuels characteristics (Riano et al, 2003). Although these sensors are effective, and widely applicable to many environmental mapping and monitoring situations, the development and launch of new sensors with improved spatial and spectral resolutions may improve the accuracy (Chuvieco and Congalton, 1989) and reduce the cost (Zhu and Blumberg, 2001) of forest fuels mapping.…”

Section: Fuels Mapping Objectivementioning

confidence: 99%

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Characterizing and mapping forest fire fuels using ASTER imagery and gradient modeling

Falkowski

Gessler

Morgan

et al. 2005

Forest Ecology and Management

145

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Land managers need cost-effective methods for mapping and characterizing forest fuels quickly and accurately. The launch of satellite sensors with increased spatial resolution may improve the accuracy and reduce the cost of fuels mapping. The objective of this research is to evaluate the accuracy and utility of imagery from the advanced spaceborne thermal emission and reflection radiometer (ASTER) satellite sensor, and gradient modeling, for mapping fuel layers for fire behavior modeling with FARSITE and FLAMMAP. Empirical models, based upon field data and spectral information from an ASTER image, were employed to test the efficacy of ASTER for mapping and characterizing crown closure and crown bulk density. Surface fuel models (National Forest Fire Laboratory (NFFL) 1-13) were mapped using a classification tree based upon three gradient layers; potential vegetation type, cover type, and structural stage. The final surface fuel model layer had an overall accuracy of 0.632 (K HAT = 0.536). Results for the canopy fuel empirical models developed here suggest that vegetation indices incorporating visible wavelengths (i.e. the green red vegetation index (GRVI)) are suitable for predicting crown closure and crown bulk density (r 2 = 0.76. and 0.46, respectively). #

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Canopy influence on snow depth distribution in a pine stand determined from terrestrial laser data

Revuelto

López‐Moreno

Azorín-Molina

et al. 2015

Water Resources Research

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In this study, we analyzed the effects of the forest canopy and trunks of a pine stand in the central Spanish Pyrenees on the snow depth (SD) distribution. Using LiDAR technology with a terrestrial laser scanner (TLS), high-resolution data on the SD distribution were acquired during the 2011-2012 and 2012-2013 snow seasons, which were 2 years having very contrasting climatic and snow accumulation conditions. Average SD evolution in open and canopy areas was characterized. Principal component analysis was applied to identify days having similar spatial patterns of SD distribution. There was a clear contrast in the temporal variability of the snowpack in different areas of the forest stand, corresponding generally to beneath the canopy, and in open sites. The canopy and openings showed markedly different accumulation and melting, with higher snow accumulation found in openings. Differences ranged from 14 to 80% reduction (average 49%) in the SD beneath the canopy relative to open sites. The difference in SD between open and canopy areas increased throughout the snow season. The surveyed days were classified in terms of SD distribution, and included days associated with: high SD, low SD, intense melting conditions and periods when the SD distribution was driven by wind conditions. The SD increased with distance from the trunks to a distance of 3.5-4.5 m, coinciding with the average size of the crown of individual trees.

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Modeling airborne laser scanning data for the spatial generation of critical forest parameters in fire behavior modeling

Cited by 235 publications

References 37 publications

Estimating canopy structure of Douglas-fir forest stands from discrete-return LiDAR

Estimating canopy structure of Douglas-fir forest stands from discrete-return LiDAR

Characterizing and mapping forest fire fuels using ASTER imagery and gradient modeling

Canopy influence on snow depth distribution in a pine stand determined from terrestrial laser data

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