scholarly journals Building Extraction from Terrestrial Laser Scanning Data with Density of Projected Points on Polar Grid and Adaptive Threshold

2021 ◽  
Vol 13 (21) ◽  
pp. 4392
Author(s):  
Maolin Chen ◽  
Xiangjiang Liu ◽  
Xinyi Zhang ◽  
Mingwei Wang ◽  
Lidu Zhao
Keyword(s):  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Region Growing ◽  
Density Variation ◽  
Building Extraction ◽  
Seed Point ◽  
Running Time ◽  
Point Number ◽  
Building Information ◽  
Polar Grid

The extraction of building information with terrestrial laser scanning (TLS) has a number of important applications. As the density of projected points (DoPP) of facades is commonly greater than for other types of objects, building points can be extracted based on projection features. However, such methods usually suffer from density variation and parameter setting, as illustrated in previous studies. In this paper, we present a building extraction method for single-scan TLS data, mainly focusing on those problems. To adapt to the large density variation in TLS data, a filter using DoPP is applied on a polar grid, instead of a commonly used rectangular grid, to detect facade points. In DoPP filtering, the threshold to distinguish facades from other objects is generated adaptively for each cell by calculating the point number when placing the lowest building in it. Then, the DoPP filtering result is further refined by an object-oriented decision tree mainly based on grid features, such as compactness and horizontal hollow ratio. Finally, roof points are extracted by region growing on the non-facade points, using the highest point in each facade cell as a seed point. The experiments are conducted on two datasets with more than 1.7 billion points and with point density varying from millimeter to decimeter levels. The completeness and correctness of the first dataset containing more than 50 million points are 91.8% and 99.8%, with a running time of approximately 970 s. The second dataset is Semantic3D, of which the point number, completeness and correctness are about 1.65 billion, 90.2% and 94.5%, with a running time of about 14,464 s. The test shows that the proposed method achieves a better performance than previous grid-based methods and a similar level of accuracy to the point-based classification method and with much higher efficiency.

scholarly journals Monitoring of the Production Process of Graded Concrete Component Using Terrestrial Laser Scanning

2021 ◽  
Vol 13 (9) ◽  
pp. 1622
Author(s):  
Yihui Yang ◽  
Laura Balangé ◽  
Oliver Gericke ◽  
Daniel Schmeer ◽  
Li Zhang ◽  
...  
Keyword(s):  
Production Process ◽  
Laser Scanning ◽  
Hollow Spheres ◽  
Terrestrial Laser Scanning ◽  
Region Growing ◽  
Casting Process ◽  
Concrete Surface ◽  
Cloud Data ◽  
Sphere Detection ◽  
Concrete Component

Accepting the ecological necessity of a drastic reduction of resource consumption and greenhouse gas emissions in the building industry, the Institute for Lightweight Structures and Conceptual Design (ILEK) at the University of Stuttgart is developing graded concrete components with integrated concrete hollow spheres. These components weigh a fraction of usual conventional components while exhibiting the same performance. Throughout the production process of a component, the positions of the hollow spheres and the level of the fresh concrete have to be monitored with high accuracy and in close to real-time, so that the quality and structural performance of the component can be guaranteed. In this contribution, effective solutions of multiple sphere detection and concrete surface modeling based on the technology of terrestrial laser scanning (TLS) during the casting process are proposed and realized by the Institute of Engineering Geodesy (IIGS). A complete monitoring concept is presented to acquire the point cloud data fast and with high-quality. The data processing method for multiple sphere segmentation based on the efficient combination of region growing and random sample consensus (RANSAC) exhibits great performance on computational efficiency and robustness. The feasibility and reliability of the proposed methods are verified and evaluated by an experiment monitoring the production of an exemplary graded concrete component. Some suggestions to improve the monitoring performance and relevant future work are given as well.

scholarly journals Separating Leaf and Wood Points in Terrestrial Laser Scanning Data Using Multiple Optimal Scales

Sensors ◽  
2019 ◽  
Vol 19 (8) ◽  
pp. 1852 ◽  
Author(s):  
Junjie Zhou ◽  
Hongqiang Wei ◽  
Guiyun Zhou ◽  
Lihui Song
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Geometric Features ◽  
Optimization Strategy ◽  
Running Time ◽  
Multi Scale ◽  
Scale Method ◽  
Optimal Scale

The separation of leaf and wood points is an essential preprocessing step for extracting many of the parameters of a tree from terrestrial laser scanning data. The multi-scale method and the optimal scale method are two of the most widely used separation methods. In this study, we extend the optimal scale method to the multi-optimal-scale method, adaptively selecting multiple optimal scales for each point in the tree point cloud to increase the distinctiveness of extracted geometric features. Compared with the optimal scale method, our method achieves higher separation accuracy. Compared with the multi-scale method, our method achieves more stable separation accuracy with a limited number of optimal scales. The running time of our method is greatly reduced when the optimization strategy is applied.

scholarly journals COMBINED 3D BUILDING SURVEYING TECHNIQUES – TERRESTRIAL LASER SCANNING (TLS) AND TOTAL STATION SURVEYING FOR BIM DATA MANAGEMENT PURPOSES

2013 ◽  
Vol 19 (Supplement_1) ◽  
pp. S23-S32 ◽  
Author(s):  
Tarvo Mill ◽  
Aivars Alt ◽  
Roode Liias
Keyword(s):  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Geodetic Survey ◽  
Economic Benefits ◽  
Accurate Information ◽  
Total Station ◽  
Existing Building ◽  
Building Information ◽  
Design And Construction

Building information modelling (BIM) represents the process of development and use of a computer generated model to simulate the planning, design, construction and operation of a building. The utilisation of building information models has increased in recent years due to their economic benefits in design and construction phases and in building management. BIM has been widely applied in the design and construction of new buildings but rarely in the management of existing ones. The point of creating a BIM model for an existing building is to produce accurate information related to the building, including its physical and functional characteristics, geometry and inner spatial relationships. The case study provides a critical appraisal of the process of both collecting accurate survey data using a terrestrial laser scanner combined with a total station and creating a BIM model as the basis of a digital management model. The case study shows that it is possible to detect and define facade damage by integration of the laser scanning point cloud and the creation of the BIM model. The paper will also give an overview of terrestrial laser scanning (TLS), total station surveying, geodetic survey networks and data processing to create a BIM model.

scholarly journals THE EXPERIENCE IN USING LASER SCANNING AND BUILDING INFORMATION MODELING FOR ENGINEERING DATA MANAGEMENT DURING THE LIFE CYCLE OF AN INDUSTRIAL OBJECT

2021 ◽  
Vol 26 (1) ◽  
pp. 57-67
Author(s):  
Anzhelika A. Sharafutdinova ◽  
◽  
Michael Ja. Bryn ◽  
Keyword(s):  
Life Cycle ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Information Modeling ◽  
Technical Documentation ◽  
Existing Structures ◽  
Operation Process ◽  
Industrial Object ◽  
Building Information ◽  
Project Construction

An industrial object accumulates a great deal of information about its assets throughout its whole development period. This information is provided in the different drawings, passports, regulations, and other technical documentation. One of the common problems of most industrial objects is the disor-ganized storage of technical documentation on assets and its limited access to different industrial ser-vices. This greatly complicates the retrieval of information about the assets to ensure the steady opera-tion of the industrial object. As a consequence, one of the ongoing important tasks becomes the crea-tion of a unified source of up-to-date information about the object’s assets and the facilitation of the access to that data for all the participants of the project, construction, and operation process. Exactly these issues are tackled in the article alongside with the solutions based on using BIM and terrestrial laser scanning. This article also describes the types of BIM and detailed differences between them, the methods to form a BIM, as well as how the methods change at different stages of the life cycle. As well, the typology of tasks for which BIM solutions are applicable. TLS technology is described as a source of initial data for the formation of BIM. This article describes the results of the combined use of BIM and TLS at the stages of design, construction, and operation of an industrial object based on the implemented project. The article provides the result of clash detection in design documentation. The result of clash detection between designed and existing structures is also given. The article also provides the deviations at the construction stage of industrial objects, which were discovered. The ac-quired results demonstrated the effectiveness of using terrestrial laser scanning and BIM in engineering solutions.

scholarly journals Consequences of vertical basic wood density variation on the estimation of aboveground biomass with terrestrial laser scanning

Trees ◽  
2021 ◽  
Author(s):  
Miro Demol ◽  
Kim Calders ◽  
Sruthi M. Krishna Moorthy ◽  
Jan Van den Bulcke ◽  
Hans Verbeeck ◽  
...  
Keyword(s):  
Wood Density ◽  
Aboveground Biomass ◽  
Laser Scanning ◽  
Basic Density ◽  
Terrestrial Laser Scanning ◽  
Density Variation ◽  
Tree Level ◽  
Timber Species ◽  
Adult Trees ◽  
Tree Models

Abstract Key message Stump-to-tip trends in basic wood density complicate the conversion of tree volume into aboveground biomass. We use 3D tree models from terrestrial laser scanning to obtain tree-level volume-weighted wood density. Abstract Terrestrial laser scanning (TLS) is used to generate realistic 3D tree models that enable a non-destructive way of quantifying tree volume. An accurate value for basic wood density is required to convert tree volume into aboveground biomass (AGB) for forest carbon assessments. However, basic density is characterised by high inter-, intra-species and within-tree variability and a likely source of error in TLS-derived biomass estimates. Here, 31 adult trees of 4 important European timber species (Fagus sylvatica, Larix decidua, Pinus sylvestris, Fraxinus excelsior) were scanned using TLS and then felled for several basic wood density measurements. We derived a reference volume-weighted basic density (ρw) by combining volume from 3D tree models with destructively assessed vertical density profiles. We compared this to basic density retrieved from a single basal disc over bark (ρbd), two perpendicular pith-to-bark increment cores at breast height (ρic), and sourcing the best available local basic wood density from publications. Stump-to-tip trends in basic wood density caused site-average woody AGB estimation biases ranging from −3.3 to + 7.8% when using ρbd and from −4.1 to + 11.8% when using ρic. Basic wood density from publications was in general a bad predictor for ρw as the bias ranged from −3.2 to + 17.2%, with little consistency across different density repositories. Overall, our density-attributed biases were similar to several recently reported biases in TLS-derived tree volume, leading to potentially large compound errors in biomass assessments with TLS if patterns of vertical basic wood density variation are not properly accounted for.

scholarly journals DEVELOPING VERIFICATION SYSTEMS FOR BUILDING INFORMATION MODELS OF HERITAGE BUILDINGS WITH HETEROGENEOUS DATASETS

2017 ◽  
Vol XLII-2/W5 ◽  
pp. 125-128 ◽  
Author(s):  
L. Chow ◽  
S. Fai
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Interior Spaces ◽  
Information Models ◽  
Heterogeneous Datasets ◽  
Building Information ◽  
Building Information Models

The digitization and abstraction of existing buildings into building information models requires the translation of heterogeneous datasets that may include CAD, technical reports, historic texts, archival drawings, terrestrial laser scanning, and photogrammetry into model elements. In this paper, we discuss a project undertaken by the Carleton Immersive Media Studio (CIMS) that explored the synthesis of heterogeneous datasets for the development of a building information model (BIM) for one of Canada’s most significant heritage assets – the Centre Block of the Parliament Hill National Historic Site. The scope of the project included the development of an as-found model of the century-old, six-story building in anticipation of specific model uses for an extensive rehabilitation program. The as-found Centre Block model was developed in Revit using primarily point cloud data from terrestrial laser scanning. The data was captured by CIMS in partnership with Heritage Conservation Services (HCS), Public Services and Procurement Canada (PSPC), using a Leica C10 and P40 (exterior and large interior spaces) and a Faro Focus (small to mid-sized interior spaces). Secondary sources such as archival drawings, photographs, and technical reports were referenced in cases where point cloud data was not available. As a result of working with heterogeneous data sets, a verification system was introduced in order to communicate to model users/viewers the source of information for each building element within the model.

scholarly journals Automatic Building Extraction from Terrestrial Laser Scanning Data

2013 ◽  
Vol 13 (3) ◽  
pp. 11-16 ◽  
Author(s):  
W. HAO ◽  
Y. WANG ◽  
X. NING ◽  
M. ZHAO ◽  
J. ZHANG ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Building Extraction

scholarly journals LiDAR Segmentation using Suitable Seed Points for 3D Building Extraction

2014 ◽  
Vol XL-3 ◽  
pp. 1-8 ◽  
Author(s):  
S. M. Abdullah ◽  
M. Awrangjeb ◽  
G. Lu
Keyword(s):  
Point Cloud ◽  
Region Growing ◽  
Data Sets ◽  
Building Detection ◽  
Building Extraction ◽  
Seed Point ◽  
Point Cloud Segmentation ◽  
Ground Point ◽  
Plane Extraction ◽  
Seed Points

Effective building detection and roof reconstruction has an influential demand over the remote sensing research community. In this paper, we present a new automatic LiDAR point cloud segmentation method using suitable seed points for building detection and roof plane extraction. Firstly, the LiDAR point cloud is separated into "ground" and "non-ground" points based on the analysis of DEM with a height threshold. Each of the non-ground point is marked as coplanar or non-coplanar based on a coplanarity analysis. Commencing from the maximum LiDAR point height towards the minimum, all the LiDAR points on each height level are extracted and separated into several groups based on 2D distance. From each group, lines are extracted and a coplanar point which is the nearest to the midpoint of each line is considered as a seed point. This seed point and its neighbouring points are utilised to generate the plane equation. The plane is grown in a region growing fashion until no new points can be added. A robust rule-based tree removal method is applied subsequently to remove planar segments on trees. Four different rules are applied in this method. Finally, the boundary of each object is extracted from the segmented LiDAR point cloud. The method is evaluated with six different data sets consisting hilly and densely vegetated areas. The experimental results indicate that the proposed method offers a high building detection and roof plane extraction rates while compared to a recently proposed method.

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