2020
DOI: 10.3390/rs12101565
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LiDAR-Based Estimates of Canopy Base Height for a Dense Uneven-Aged Structured Forest

Abstract: Accurate canopy base height (CBH) information is essential for forest and fire managers since it constitutes a key indicator of seedling growth, wood quality and forest health as well as a necessary input in fire behavior prediction systems such as FARSITE, FlamMap and BEHAVE. The present study focused on the potential of airborne LiDAR data analysis to estimate plot-level CBH in a dense uneven-aged structured forest on complex terrain. A comparative study of two widely employed methods was performed, namely t… Show more

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Cited by 21 publications
(20 citation statements)
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“…The following metrics were calculated based on the vertical distribution of the normalised point heights within each reference area (i.e. either plot or area to be harvested): average, maximum, percentiles (every 5%, plus 99%), the number of points in different height ranges (between 0 and 10 cm, 10 and 20 cm, 20 and 30 cm, 40 and 50 cm, 50 and 60 cm, 60 and 70 cm), and bincentiles (every 5 from 5 to 95) (Stefanidou et al 2020). A bincentile is the percentage of points above a reference height, with the reference height being the percentage of the maximum height, which is added to the end of the bincentile.…”
Section: Generating and Processing Of The 3d Uav Lidar Point Cloudmentioning
confidence: 99%
See 1 more Smart Citation
“…The following metrics were calculated based on the vertical distribution of the normalised point heights within each reference area (i.e. either plot or area to be harvested): average, maximum, percentiles (every 5%, plus 99%), the number of points in different height ranges (between 0 and 10 cm, 10 and 20 cm, 20 and 30 cm, 40 and 50 cm, 50 and 60 cm, 60 and 70 cm), and bincentiles (every 5 from 5 to 95) (Stefanidou et al 2020). A bincentile is the percentage of points above a reference height, with the reference height being the percentage of the maximum height, which is added to the end of the bincentile.…”
Section: Generating and Processing Of The 3d Uav Lidar Point Cloudmentioning
confidence: 99%
“…A bincentile is the percentage of points above a reference height, with the reference height being the percentage of the maximum height, which is added to the end of the bincentile. Bicentiles can be considered as a canopy density measure (Stefanidou et al 2020). The measure of the return energy of the emitted laser beam is the basis for generating the LiDAR intensity, which RiProcess then uses to calculate the reflectance of each LiDAR point.…”
Section: Generating and Processing Of The 3d Uav Lidar Point Cloudmentioning
confidence: 99%
“…This finding agrees with those of Fernández-Guisuraga et al (2021) who found that severe ecosystem damage was mainly driven by vegetation structure rather than topography or patch size, with different roles of pre-fire fuel structure parameters. Many studies have accurately estimated CBH from ALS data (Andersen et al, 2005;Kelly et al, 2017;Luo et al, 2018;Moran et al, 2020;Stefanidou et al, 2020;Chamberlain et al, 2021), and a few studies have estimated CBH with TLS data (García et al, 2011;Novotny et al, 2021), so ideally these forest structure variables could be estimated via remote sensing instead of a field-based approach, to maintain a continuity in data collection.…”
Section: Modeling the Relationship Between Ladder Fuels And Burn Seve...mentioning
confidence: 99%
“…And, their measurement accuracy and data stability are difficult to guarantee compared with point cloud data. Measuring tree parameters through lidar data can realize forest monitoring (including tree species classification [23], forest structure [24], canopy height [25], parameter extraction, etc.) and mapping [26].…”
Section: A Backgroundmentioning
confidence: 99%