Tree modelling from mobile laser scanning data‐sets

Rutzinger, Martin; Pratihast, Arun Kumar; Elberink, Sander Oude; Vosselman, G.

doi:10.1111/j.1477-9730.2011.00635.x

Cited by 121 publications

(106 citation statements)

References 24 publications

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“…Based on MLS data, Jaakkola et al [35] separated trees by clustering the extracted vertical line segments and examining the spatial distribution of clusters. Rutzinger et al [43] developed a method for tree recognition, in which the MLS point cloud is first segmented into planar regions using a 3D Hough transform and surface growing algorithm, and then the segments forming an individual tree are identified. Pu et al [44] adopted a percentile based pole recognition algorithm for segmenting tree trunks and crowns from MLS data.…”

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confidence: 99%

A Voxel-Based Method for Automated Identification and Morphological Parameters Estimation of Individual Street Trees from Mobile Laser Scanning Data

et al. 2013

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Abstract:As an important component of urban vegetation, street trees play an important role in maintenance of environmental quality, aesthetic beauty of urban landscape, and social service for inhabitants. Acquiring accurate and up-to-date inventory information for street trees is required for urban horticultural planning, and municipal urban forest management. This paper presents a new Voxel-based Marked Neighborhood Searching (VMNS) method for efficiently identifying street trees and deriving their morphological parameters from Mobile Laser Scanning (MLS) point cloud data. The VMNS method consists of six technical components: voxelization, calculating values of voxels, searching and marking neighborhoods, extracting potential trees, deriving morphological parameters, and eliminating pole-like objects other than trees. The method is validated and evaluated through two case studies. The evaluation results show that the completeness and correctness of our method for street tree detection are over 98%. The derived morphological parameters, including tree height, crown diameter, diameter at breast height (DBH), and crown base height (CBH), are in a good agreement with the field OPEN ACCESS Remote Sens. 2013, 5 585 measurements. Our method provides an effective tool for extracting various morphological parameters for individual street trees from MLS point cloud data.

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confidence: 99%

A Voxel-Based Method for Automated Identification and Morphological Parameters Estimation of Individual Street Trees from Mobile Laser Scanning Data

et al. 2013

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“…α‐shapes are a generalization of the convex hull concept (Edelsbrunner, Kirkpatrick, & Seidel, 1983), and by adjusting the value of α, even small details and concave surface structures in crown morphology can be captured. The rationale for using α‐shapes is often to simplify the point cloud and the amount of data without losing information on occupied crown space (Rutzinger, Pratihast, Elberink, Sander, & Vosselman, 2011). However, oversimplification may lead to the loss of details within the crown, that is, branches that lie within the α‐shape hull.…”

Section: Introductionmentioning

confidence: 99%

A high‐resolution approach for the spatiotemporal analysis of forest canopy space using terrestrial laser scanning data

Hess

Härdtle

Kunz

et al. 2018

Ecology and Evolution

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Forest canopies and tree crown structures are of high ecological importance. Measuring canopies and crowns by direct inventory methods is time‐consuming and of limited accuracy. High‐resolution inventory tools, in particular terrestrial laser scanning (TLS), is able to overcome these limitations and obtain three‐dimensional (3D) structural information about the canopy with a very high level of detail. The main objective of this study was to introduce a novel method to analyze spatiotemporal dynamics in canopy occupancy at the individual tree and local neighborhood level using high‐resolution 3D TLS data. For the analyses, a voxel grid approach was applied. The tree crowns were modeled through the combination of two approaches: the encasement of all crown points with a 3D α‐shape, which was then converted into a voxel grid, and the direct voxelization of the crown points. We show that canopy occupancy at individual tree level can be quantified as the crown volume occupied only by the respective tree or shared with neighboring trees. At the local neighborhood level, our method enables the precise determination of the extent of canopy space filling, the identification of tree–tree interactions, and the analysis of complementary space use. Using multitemporal TLS data recordings, this method allows the precise detection and quantification of changes in canopy occupancy through time. The method is applicable to a wide range of investigations in forest ecology research, including the study of tree diversity effects on forest productivity or growing space analyses for optimal tree growth. Due to the high accuracy of this novel method, it facilitates the precise analyses even of highly plastic individual tree crowns and, thus, the realistic representation of forest canopies. Moreover, our voxel grid framework is flexible enough to allow for the inclusion of further biotic and abiotic variables relevant to complex analyses of forest canopy dynamics.

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“…The results of MLS's application for the detection of trees or pole-like objects have been presented (e.g. by Jaakkola et al, 2010;Lehtomäki et al, 2010;Rutzinger et al, 2010;Kaartinen et al, 2013;Liang et al, 2014). Holopainen et al (2013) compare the accuracy and efficiency of airborne laser scanning (ALS), TLS and MLS measurements in tree mapping in heterogeneous park forests.…”

Section: Introductionmentioning

confidence: 99%

The Effect of Wind on Tree Stem Parameter Estimation Using Terrestrial Laser Scanning

Vaaja¹,

Virtanen²,

Kurkela³

et al. 2016

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Commission VIII, WG VIII/7 KEY WORDS: Terrestrial Laser Scanning, Wind, Tree Reconstruction, Stem Diameter, Stem Location, Pine ABSTRACT:The 3D measurement technique of terrestrial laser scanning (TLS) in forest inventories has shown great potential for improving the accuracy and efficiency of both individual tree and plot level data collection. However, the effect of wind has been poorly estimated in the error analysis of TLS tree measurements although it causes varying deformations to the trees. In this paper, we evaluated the effect of wind on tree stem parameter estimation at different heights using TLS. The data consists of one measured Scots pine captured from three different scanning directions with two different scanning resolutions, 6.3 mm and 3.1 mm at 10 m. The measurements were conducted under two different wind speeds, approximately 3 m/s and 9 m/s, as recorded by a nearby weather station of the Finnish Meteorological Institute. Our results show that the wind may cause both the underestimation and overestimation of tree diameter when using TLS. The duration of the scanning is found to have an impact for the measured shape of the tree stem under 9 m/s wind conditions. The results also indicate that a 9 m/s wind does not have a significant effect on the stem parameters of the lower part of a tree (<28% of the tree height). However, as the results imply, the wind conditions should be taken into account more comprehensively in analysis of TLS tree measurements, especially if multiple scans from different positions are registered together. In addition, TLS could potentially be applied to indirectly measure wind speed by observing the tree stem movement.

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Tree modelling from mobile laser scanning data‐sets

Cited by 121 publications

References 24 publications

A Voxel-Based Method for Automated Identification and Morphological Parameters Estimation of Individual Street Trees from Mobile Laser Scanning Data

A Voxel-Based Method for Automated Identification and Morphological Parameters Estimation of Individual Street Trees from Mobile Laser Scanning Data

A high‐resolution approach for the spatiotemporal analysis of forest canopy space using terrestrial laser scanning data

The Effect of Wind on Tree Stem Parameter Estimation Using Terrestrial Laser Scanning

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