Using airborne and ground-based ranging lidar to measure canopy structure in Australian forests

Lovell, Jenny; Jupp, David L.B.; Culvenor, Darius; Coops, Nicholas C.

doi:10.5589/m03-026

Cited by 433 publications

(322 citation statements)

References 25 publications

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“…The most commonly applied distribution is a Weibull function, due to its flexibility in characterizing foliage distributions of various species (Vose 1988, Gillespie et al 1994, Kershaw and Maguire 1995, Xu and Harrington 1998, Lovell et al 2003. This distribution has also been used (Magnussen et al 1999) to examine the distribution of canopy heights from airborne LiDAR systems by comparing the probability of LiDAR height quantiles above a desired height with the distribution of leaf area.…”

Section: Fitting the Weibull Distribution To Foliage Profilesmentioning

confidence: 99%

“…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 study the approach of Lovell et al (2003) was followed resulting in the computation of forest stand attributes over a 20 x 20 m window centred over the plot location. Maximum height was calculated as the highest return within the window size.…”

Section: Height Derivation From Small-footprint Lidarmentioning

confidence: 99%

“…These N heights are then averaged to obtain a stratified dominant height estimate. In this case, the plot was divided into four sub-plots and the highest return in each sub-plot was averaged to obtain a dominant height estimate for the plot (Naesset 1997, Lovell et al 2003). …”

Section: Height Derivation From Small-footprint Lidarmentioning

confidence: 99%

See 3 more Smart Citations

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

Coops

Hilker

Wulder

et al. 2007

Trees

304

223

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Section: Fitting the Weibull Distribution To Foliage Profilesmentioning

confidence: 99%

Section: Lidar Based Measures Of Canopy Structurementioning

confidence: 99%

Section: Height Derivation From Small-footprint Lidarmentioning

confidence: 99%

Section: Height Derivation From Small-footprint Lidarmentioning

confidence: 99%

See 2 more Smart Citations

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

Coops

Hilker

Wulder

et al. 2007

Trees

304

223

View full text Add to dashboard Cite

“…Airborne radiometric, magnetic and electromagnetic measurements of the sub-surface, for instance, could be integrated. Further datasets derived from laser scanning can give information about supra-surface features such as vegetation canopy structure (e.g ECHIDNA) to, for example, estimate biomass (Lovell et al, 2003). Integrating such geophysical data with DEMs in order to understand geomorphic processes has been the focus of much recent work (e.g.…”

Section: In Spacementioning

confidence: 99%

3.11 Geovisualization

Smith

Hillier²,

Otto³

et al. 2013

Treatise on Geomorphology

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Synopsis (50-100 words)Geovisualisation, the depiction of spatial data, is key to facilitating the generation of observational datasets through which Earth surface and solid Earth processes may be understood. This chapter focuses upon the visualisation of terrain morphology using satellite imagery and DEMs, where manual interpretation remains prevalent in the study of geomorphic processes. Techniques to enhance satellite images and DEMs in order to improve landform identification as part of the manual mapping process are presented. Visual interaction with spatial data is an important part of exploring and understanding geomorphological datasets and a variety of methods ranging from simple overlay, panning and zooming are discussed, along with 2.5D, 3D and temporal analyses. Visualisation outputs are outlined in the final section, which focuses on static and interactive methods of dissemination. Geomorphological mapping legends and the cartographic principles for map design are introduced, followed by details of dynamic webmap systems that allow a greater immersive use by end users, as well as the dissemination of data.

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Improved snow interception modeling using canopy parameters derived from airborne LiDAR data

Moeser

Stähli

Jonas³

2015

Water Resources Research

118

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Forest snow interception can account for large snow storage differences between open and forested areas. The effect of interception can also lead to significant variations in sublimation, with estimates varying from 5 to 60% of total snowfall. Most current interception models utilize canopy closure and LAI to partition interception from snowfall and calculate interception efficiency as an exponential decrease of interception efficiency with increasing precipitation. However, as demonstrated, these models can show specific deficiencies within heterogeneous canopy. Seven field areas were equipped with 1932 surveyed points within various canopy density regimes in three elevation bands surrounding Davos, Switzerland. Snow interception measurements were taken from 2012 to 2014 ($9000 samples) and compared with measurements at two open sites. The measured data indicated the presence of snow bridging from a demonstrated increase in interception efficiency as precipitation increased until a maximum was reached. As precipitation increased beyond this maximum, the data then exhibited a decrease in interception efficiency. Standard and novel canopy parameters were developed using aerial LiDAR data. These included estimates of LAI, canopy closure, distance to canopy, gap fraction, and various tree size parameters. These canopy metrics and the underlying efficiency distribution were then integrated to formulate a conceptual model based upon the snow interception measurements. This model gave a $27% increase in the r 2 (from 0.39 to 0.66) and a $40% reduction in RMSE (from 5.19 to 3.39) for both calibration and validation data sets when compared to previous models at the point scale. When upscaled to larger grid sizes, the model demonstrated further increases in performance.

show abstract

Using airborne and ground-based ranging lidar to measure canopy structure in Australian forests

Cited by 433 publications

References 25 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

3.11 Geovisualization

Improved snow interception modeling using canopy parameters derived from airborne LiDAR data

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