The structural and radiative consistency of three-dimensional tree reconstructions from terrestrial lidar

Côté, Jean-François; Widlowski, Jean-Luc; Fournier, Richard; Verstraete, M. M.

doi:10.1016/j.rse.2009.01.017

Cited by 250 publications

(152 citation statements)

References 25 publications

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“…The biggest problems arising with these approaches are the rotational dependency of the height function and the sensitivity of the level set extraction to the sampling density, [8]. The approach of [24] was applied by Côtè et al [9] on trees. A virtual tree model based on the allometries of the known tree species was used to estimate the finer branches.…”

Section: D Descriptorsmentioning

confidence: 99%

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SkelTre

2010

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Terrestrial laser scanners capture 3D geometry of real world objects as a point cloud. This paper reports on a new algorithm developed for the skeletonization of a laser scanner point cloud. The skeletonization algorithm proposed in this paper consists of three steps: (i) extraction of a graph from an octree organization, (ii) reduction of the graph to a skeleton, and (iii) embedding of the skeleton into the point cloud. For these three steps, only one input parameter is required. The results are validated on laser scanner point clouds representing 2 classes of objects; first on botanic trees as a special application and secondly on popular arbitrary objects. The presented skeleton found its first application in obtaining botanic tree parameters like length and diameter of branches and is presented here in a new, generalized version. Its definition as Reeb Graph, proofs the usefulness of the skeleton for applications like shape analysis. In this paper we show that the resulting skeleton contains the Reeb Graph and investigate the practically relevant parameters: centeredness and topological correctness. The robustness of this skeletonization method against undersampling, varying point density and systematic errors of the point cloud is demonstrated on real data examples.

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Section: D Descriptorsmentioning

confidence: 99%

“…[25,26] and Remote Sensing, e.g. [13] and [9]. Both fields have in common that a skeleton is used to represent the tree with the goal to extract surface information.…”

Section: Introductionmentioning

confidence: 99%

SkelTre

2010

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“…Although the use of TLS intensity data as reflectance information has been proved to be effective to separate foliage from wood in trees and other applications [8,30], it is not useful to define a fixed set of filter parameters under the conditions of the present study. Intensities should be calibrated with an external reference if the aim is to develop an effective intensity-based filter.…”

Section: Discussionmentioning

confidence: 99%

“…Time-of-flight discrete-return instruments provide high accuracy at large range. This category of scanners has been the most used for vegetation structure assessments [8]. In addition to the point cloud data, most TLS instruments also record the instrumental (i.e., raw) point intensity value.…”

Section: Introductionmentioning

confidence: 99%

Correction of Erroneous LiDAR Measurements in Artificial Forest Canopy Experimental Setups

Cifuentes

Zande

Salas

et al. 2014

Forests

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Terrestrial laser scanning (TLS) data makes possible to directly characterize the three-dimensional (3D) distribution of canopy foliage elements. The scanned edges of these elements may result in incorrectly point measurements (i.e., "ghost points") impacting the quality of point cloud data. Therefore, estimation of the ghost points' spatial visibilities, measurement of their characteristics and their removal are essential. In order to quantify the improvements on data quality, a method is developed in this study to efficiently correct for ghost points. Since the occurrence of ghost points is governed by a number of factors, (e.g., scanning resolution and distance, object properties, incident angle); the developed method is based on the analysis of the effects of these factors under controlled conditions where canopy-like objects (i.e., leaves, branches and layers of leaves) were scanned using a continuous-wave TLS system that employs phase-shift technology. Manual extraction of ghost points was done in order to calculate the relative amount of ghost points per scan, or ghost points ratio (gpr). The gpr values were computed in order to: (i) analyze their relationships with variables representing the above factors; and (ii) be used as a reference to evaluate the performance of filters used for extraction of ghost points. The ghost points' occurrence was modeled by fitting regression models using different predictor variables OPEN ACCESSForests 2014, 5 1566 that represent the variables under study. The obtained results indicated that reduced models with three predictors were suitable for gpr estimation in artificial leaves and in artificial branches, with a relative root mean squared error (RMSE) of 4.7% and 3.7%, respectively; while the full model with four predictors was appropriate for artificial layers of leaves, with relative RMSE of 4.5%. According to the statistical analysis, scanning distance was identified as the most important variable for modeling ghost points occurrence. Results indicated that optimized distance-based filters relative to the scanning distance have improved the outcomes in ghost points detection, in comparison to standard filtering criteria. These results suggest that more accurate characterization of forest canopy 3D structures can be achieved by removing ghost points using the new developed method.

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“…Some methods carry out firstly a contraction, before extracting a skeleton from the reduced point cloud (Cao et al, 2010;Preuksakarn, 2012). Others transform the point cloud into a graph in order to organize it for obtaining the skeleton (Côté et al, 2009;Livny et al, 2010;Xu et al, 2007). We can also find a method which segments the point cloud in octree before computing the centroid of each cell to form the skeleton (Bucksch et al, 2010).…”

Section: Accurate 3d Reconstruction Methods Of Treesmentioning

confidence: 99%

From TLS Point Clouds to 3d Models of Trees: A Comparison of Existing Algorithms for 3d Tree Reconstruction

Bournez

Landes

Saudreau

et al. 2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:3D models of tree geometry are important for numerous studies, such as for urban planning or agricultural studies. In climatology, tree models can be necessary for simulating the cooling effect of trees by estimating their evapotranspiration. The literature shows that the more accurate the 3D structure of a tree is, the more accurate microclimate models are. This is the reason why, since 2013, we have been developing an algorithm for the reconstruction of trees from terrestrial laser scanner (TLS) data, which we call TreeArchitecture. Meanwhile, new promising algorithms dedicated to tree reconstruction have emerged in the literature. In this paper, we assess the capacity of our algorithm and of two others -PlantScan3D and SimpleTree-to reconstruct the 3D structure of trees. The aim of this reconstruction is to be able to characterize the geometric complexity of trees, with different heights, sizes and shapes of branches. Based on a specific surveying workflow with a TLS, we have acquired dense point clouds of six different urban trees, with specific architectures, before reconstructing them with each algorithm. Finally, qualitative and quantitative assessments of the models are performed using reference tree reconstructions and field measurements. Based on this assessment, the advantages and the limits of every reconstruction algorithm are highlighted. Anyway, very satisfying results can be reached for 3D reconstructions of tree topology as well as of tree volume.

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The structural and radiative consistency of three-dimensional tree reconstructions from terrestrial lidar

Cited by 250 publications

References 25 publications

SkelTre

SkelTre

Correction of Erroneous LiDAR Measurements in Artificial Forest Canopy Experimental Setups

From TLS Point Clouds to 3d Models of Trees: A Comparison of Existing Algorithms for 3d Tree Reconstruction

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