Sensitivity of voxel-based estimations of leaf area density with terrestrial LiDAR to vegetation structure and sampling limitations: A simulation experiment

Soma, Maxime; Pimont, François; Dupuy, Jean‐Luc

doi:10.1016/j.rse.2021.112354

Cited by 18 publications

(4 citation statements)

References 31 publications

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“…While there are drawbacks to single-point scans, they are similar to ocular estimates of cover made by an observer at a single point. To fully utilize a voxelization method, multiple scans stitched together must be used for a near complete scan of all vegetation structures [61,62]. Having a near-complete scan of all the vegetation from multiple scans is relatively easy in open stands; however, many of our stands had dense understory vegetation with high amounts of occlusion.…”

Section: Tls Metricsmentioning

confidence: 99%

Terrestrial and Airborne Lidar to Quantify Shrub Cover for Canada Lynx (Lynx canadensis) Habitat Using Machine Learning

Batchelor,

Hudak,

Gould

et al. 2023

Remote Sensing

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The Canada lynx is listed as a threatened species, and as such, the identification and conservation of lynx habitats is of significant concern. Lynxes require areas with high amounts of horizontal cover made up of ground vegetation. Lidar offers a robust method of quantifying vegetation structure, and airborne lidar has been acquired across large areas of potential lynx habitat. Unfortunately, airborne lidar is often not able to directly measure understory horizontal cover due to occlusion from the upper branches. Terrestrial lidar does directly measure understory horizontal cover and can be used as training data for larger area models using airborne lidar. In this study, we acquired 168 individual terrestrial lidar scans (TLS) across 42 sites in north-central Washington state. We generated metrics from the single-scan TLS plots using depth maps, a digital cover board, and voxels. Using our TLS metrics as the training data for the airborne lidar acquired for the entire Loomis State Forest, we were able to produce a model using xgboost with 85% accuracy. We believe our study shows that single-scan TLS plots can be used effectively to quantify fine-scale forest structure elements relevant to species habitat, to then inform larger area models using airborne lidar.

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Section: Tls Metricsmentioning

confidence: 99%

Terrestrial and Airborne Lidar to Quantify Shrub Cover for Canada Lynx (Lynx canadensis) Habitat Using Machine Learning

Batchelor,

Hudak,

Gould

et al. 2023

Remote Sensing

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“…The physiological characteristic of foliage distribution occurs most often (in total, 34 times in the 48 papers included in the in-depth analysis). With horizontal and vertical foliage distribution, it can be used to determine the "energy and mass fluxes in heterogeneous ecosystems" [74], estimate the canopy-scale regulated light use efficiency [75,76], assess photosynthetic capacity and simulate the exchanges of CO 2 , water vapor and other trace gases. The leaf area index (LAI) and leaf area density (LAD) are the mathematical indices describing 3D foliage distribution in a simple and quantitative way.…”

Section: Crown-level Physiological Characteristicsmentioning

confidence: 99%

3D Tree Reconstruction in Support of Urban Microclimate Simulation: A Comprehensive Literature Review

et al. 2021

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The negative climate change induced by rapid urbanization has become a global environmental issue. Numerous studies have been devoted to microclimate regulation functions performed by urban vegetation. Digital city information modeling provides a powerful tool for various simulations and data analytics for the sustainable development of urban areas. However, the method reconstructing urban trees is still in its early stage compared to the relatively mature building modeling. Most prior studies on tree reconstruction focused on retrieving geometric features, while other factors related to urban microclimate simulation were rarely addressed. This paper presents a comprehensive literature review and in-depth analysis covering two distinct research directions in relation to urban microclimate simulation. The first one is set on the identification of key factors related to trees’ impact on urban microclimate. The second one is dedicated to approaches for three-dimensional (3D) tree reconstruction. Based on the findings, the paper identifies information including trees’ geometric, physiological characteristics and relation to the surroundings required for 3D tree reconstruction in the context of urban microclimate simulation, and further assesses the potential of the 3D tree reconstruction approaches to accommodate these pieces of information. An appropriate 3D tree reconstruction approach, which allows for the supply of the required information for urban microclimate simulation, is recommended.

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“…The specification of voxel size in the process of voxelization has proven to have a significant impact on the estimation accuracy in previous studies, and optimal voxel size needs to be determined [37,38]. Among vegetation complexity, subcanopy structure, and clumping effect, several factors are proposed to be influencing the value of optimal voxel size [39,40], and measures have been taken to tackle this problem, including limiting occlusion by conducting multiple scans and introducing correction factors in different voxel sizes [41], yet the specification of optimal voxel size still remains contradictory in different studies [42][43][44]. Here, we applied a non-voxel-based approach as an alternative and conducted comparisons to evaluate its performance for understory biomass estimation.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Three Approaches for Estimating Understory Biomass in Yanshan Mountains

Li,

Hu,

Xing

et al. 2024

Remote Sensing

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Aboveground biomass (AGB) of shrubs and low-statured trees constitutes a substantial portion of the total carbon pool in temperate forest ecosystems, contributing much to local biodiversity, altering tree-regeneration growth rates, and determining above- and belowground food webs. Accurate quantification of AGB at the shrub layer is crucial for ecological modeling and still remains a challenge. Several methods for estimating understory biomass, including inventory and remote sensing-based methods, need to be evaluated against measured datasets. In this study, we acquired 158 individual terrestrial laser scans (TLS) across 45 sites in the Yanshan Mountains and generated metrics including leaf area and stem volume from TLS data using voxel- and non-voxel-based approaches in both leaf-on and leaf-off scenarios. Allometric equations were applied using field-measured parameters as an inventory approach. The results indicated that allometric equations using crown area and height yielded results with higher accuracy than other inventory approach parameters (R2 and RMSE ranging from 0.47 to 0.91 and 12.38 to 38.11 g, respectively). The voxel-based approach using TLS data provided results with R2 and RMSE ranging from 0.86 to 0.96 and 6.43 to 21.03 g. Additionally, the non-voxel-based approach provided similar or slightly better results compared to the voxel-based approach (R2 and RMSE ranging from 0.93 to 0.96 and 4.23 to 11.27 g, respectively) while avoiding the complexity of selecting the optimal voxel size that arises during voxelization.

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Sensitivity of voxel-based estimations of leaf area density with terrestrial LiDAR to vegetation structure and sampling limitations: A simulation experiment

Cited by 18 publications

References 31 publications

Terrestrial and Airborne Lidar to Quantify Shrub Cover for Canada Lynx (Lynx canadensis) Habitat Using Machine Learning

Terrestrial and Airborne Lidar to Quantify Shrub Cover for Canada Lynx (Lynx canadensis) Habitat Using Machine Learning

3D Tree Reconstruction in Support of Urban Microclimate Simulation: A Comprehensive Literature Review

Comparison of Three Approaches for Estimating Understory Biomass in Yanshan Mountains

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