THE CONTRIBUTION OF GEOMATIC TECHNOLOGIES TO BIM

Abstract. There are many definitions of the commonly used abbreviation BIM, but one can say that each user or data supplier has different idea about it. There can be an economic view, or other aspects like surveying, material, engineering, maintenance, etc. The common definition says that Building Information Modelling or Building Information Management (BIM) is a digital model representing a physical and functional object with its characteristics. The model serves as a database of object information for its design, construction and operation over its life cycle, i.e. from the initial concept to the removal of the building. BIM is a collection of interconnected digital information in both protected and open formats, recording graphical and non-graphical data on model elements. There are two facets: a) BIM created simultaneously with the project, or project designed directly in BIM (it is typical of new objects designed in CAD systems - for example in the Revit software) or b) BIM for old or historical objects. The former is a modern technology, which is nowadays used worldwide. From the engineer’s perspective, the issue is the creation of BIM for older objects. In this case, it is crucial to obtain a precise 3D data set - complex 3D documentation of an object is needed and it is created using various surveying techniques. The most popular technique is laser scanning or digital automatic photogrammetry, from which a point cloud is derived. But this is not the main result. While classical geodesy gives selective localized information, the above-mentioned technologies give unselected information and provide huge datasets. Fully automatic technologies that would select important information from the point cloud are still under development. This seems to be a task for the coming years. Large amounts of data can be acquired automatically and quickly, but getting the expected information is another matter. These problems will be analysed in this paper. Data conversion to BIM, especially for older objects, will be shown on several case studies. The first is an older technical building complex transferred to BIM, the second one is a historical building, and the third one will be a historic medieval bridge (Charles Bridge in Prague). The last part of this paper will refer to aspects and benefits of using Virtual Reality in BIM.

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Extracting features from laser scanning point cloud

SHS Web of Conferences ◽

10.1051/shsconf/20184400013 ◽

2018 ◽

Vol 44 ◽

pp. 00013 ◽

Cited By ~ 2

Author(s):

Vladimir Badenko ◽

Alexander Fedotov ◽

Dmitry Zotov

Keyword(s):

Point Cloud ◽

Laser Scanning ◽

Historical Buildings ◽

Historical Building ◽

Building Information Modelling ◽

Historic Building ◽

Technology Application ◽

Information Modelling ◽

Hybrid Technology ◽

Building Information

Analyses of gaps in processing of raw laser scanning data and results of bridging the gaps discovered on the basis of usage of laser scanning data for historic building information modelling are presented. Some results of the development of a unified hybrid technology for the processing, storage, access and visualization of combined laser scanning and photography data about historical buildings are analyzed. The first result of the technology application to historical building of St. Petersburg Polytechnic University shows the robustness of the approaches proposed.

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System analysis of the quality of meshes in HBIM

MATEC Web of Conferences ◽

10.1051/matecconf/201817003033 ◽

2018 ◽

Vol 170 ◽

pp. 03033 ◽

Cited By ~ 4

Author(s):

Elizaveta Fateeva ◽

Vladimir Badenko ◽

Alexandr Fedotov ◽

Ivan Kochetkov

Keyword(s):

Point Cloud ◽

Laser Scanning ◽

System Analysis ◽

Point Clouds ◽

Rational Solutions ◽

Historical Building ◽

Architectural Styles ◽

Architectural Features ◽

Building Information

Historical Building Information Modelling (HBIM) is nowadays used as a means to collect, store and preserve information about historical buildings and structures. The information is often collected via laser scanning. The resulting point cloud is manipulated and transformed into a polygon mesh, which is a type of model very easy to work with. This paper looks at the problems associated with creating mesh out of point clouds depending on various characteristics in context of façade reconstruction. The study is based on a point cloud recorded via terrestrial laser scanning in downtown Bremen, Germany that contains buildings completed in a number of different architectural styles, allowing to extract multiple architectural features. Analysis of meshes' quality depending on point cloud density was carried out. Conclusions were drawn as to what the rational solutions for effective surface extraction can be for each individual building in question. Recommendations on preprocessing of point clouds were given.

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FINE REGISTRATION OF KILO-STATION NETWORKS - A MODERN PROCEDURE FOR TERRESTRIAL LASER SCANNING DATA SETS

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xli-b5-485-2016 ◽

2016 ◽

Vol XLI-B5 ◽

pp. 485-492

Author(s):

J.-F. Hullo

Keyword(s):

Laser Scanning ◽

Laser Scanner ◽

Data Sets ◽

Data Set ◽

Information Models ◽

3D Network ◽

Laser Scanners ◽

Building Information ◽

Set Up ◽

Fine Registration

We propose a complete methodology for the fine registration and referencing of kilo-station networks of terrestrial laser scanner data currently used for many valuable purposes such as 3D as-built reconstruction of Building Information Models (BIM) or industrial asbuilt mock-ups. This comprehensive target-based process aims to achieve the global tolerance below a few centimetres across a 3D network including more than 1,000 laser stations spread over 10 floors. This procedure is particularly valuable for 3D networks of indoor congested environments. In situ, the use of terrestrial laser scanners, the layout of the targets and the set-up of a topographic control network should comply with the expert methods specific to surveyors. Using parametric and reduced Gauss-Helmert models, the network is expressed as a set of functional constraints with a related stochastic model. During the post-processing phase inspired by geodesy methods, a robust cost function is minimised. At the scale of such a data set, the complexity of the 3D network is beyond comprehension. The surveyor, even an expert, must be supported, in his analysis, by digital and visual indicators. In addition to the standard indicators used for the adjustment methods, including Baarda’s reliability, we introduce spectral analysis tools of graph theory for identifying different types of errors or a lack of robustness of the system as well as in fine documenting the quality of the registration.

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ON A KNOWLEDGE-BASED APPROACH TO THE CLASSIFICATION OF MOBILE LASER SCANNING POINT CLOUDS

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-4-343-2018 ◽

2018 ◽

Vol XLII-4 ◽

pp. 343-349 ◽

Cited By ~ 1

Author(s):

M. Lemmens

Keyword(s):

Point Cloud ◽

Laser Scanning ◽

Decision Rules ◽

Point Clouds ◽

Bench Mark ◽

Automated Classification ◽

Initial Experiment ◽

Data Set ◽

Knowledge Based

Abstract. A knowledge-based system exploits the knowledge, which a human expert uses for completing a complex task, through a database containing decision rules, and an inference engine. Already in the early nineties knowledge-based systems have been proposed for automated image classification. Lack of success faded out initial interest and enthusiasm, the same fate neural networks struck at that time. Today the latter enjoy a steady revival. This paper aims at demonstrating that a knowledge-based approach to automated classification of mobile laser scanning point clouds has promising prospects. An initial experiment exploiting only two features, height and reflectance value, resulted in an overall accuracy of 79% for the Paris-rue-Madame point cloud bench mark data set.

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From Point Cloud Data to Building Information Modelling: An Automatic Parametric Workflow for Heritage

Remote Sensing ◽

10.3390/rs12071094 ◽

2020 ◽

Vol 12 (7) ◽

pp. 1094 ◽

Cited By ~ 4

Author(s):

Mesrop Andriasyan ◽

Juan Moyano ◽

Juan Enrique Nieto-Julián ◽

Daniel Antón

Keyword(s):

Point Cloud ◽

Laser Scanning ◽

Accuracy Assessment ◽

Parametric Modelling ◽

Point Cloud Data ◽

Building Information Modelling ◽

Historical Interpretation ◽

Information Modelling ◽

Cloud Data ◽

Building Information

Building Information Modelling (BIM) is a globally adapted methodology by government organisations and builders who conceive the integration of the organisation, planning, development and the digital construction model into a single project. In the case of a heritage building, the Historic Building Information Modelling (HBIM) approach is able to cover the comprehensive restoration of the building. In contrast to BIM applied to new buildings, HBIM can address different models which represent either periods of historical interpretation, restoration phases or records of heritage assets over time. Great efforts are currently being made to automatically reconstitute the geometry of cultural heritage elements from data acquisition techniques such as Terrestrial Laser Scanning (TLS) or Structure From Motion (SfM) into BIM (Scan-to-BIM). Hence, this work advances on the parametric modelling from remote sensing point cloud data, which is carried out under the Rhino+Grasshopper-ArchiCAD combination. This workflow enables the automatic conversion of TLS and SFM point cloud data into textured 3D meshes and thus BIM objects to be included in the HBIM project. The accuracy assessment of this workflow yields a standard deviation value of 68.28 pixels, which is lower than other author’s precision but suffices for the automatic HBIM of the case study in this research.

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Reconstruction of Axial Tomographic High Resolution Data from Confocal Fluorescence Microscopy: A Method for Improving 3D FISH Images

Analytical Cellular Pathology ◽

10.1155/2000/459351 ◽

2000 ◽

Vol 20 (1) ◽

pp. 7-15 ◽

Cited By ~ 18

Author(s):

R. Heintzmann ◽

G. Kreth ◽

C. Cremer

Keyword(s):

High Resolution ◽

Laser Scanning ◽

Axial Direction ◽

Laser Scanning Microscopy ◽

Three Dimensions ◽

Confocal Laser ◽

Data Sets ◽

Data Set ◽

High Resolution Data ◽

3D Data

Fluorescent confocal laser scanning microscopy allows an improved imaging of microscopic objects in three dimensions. However, the resolution along the axial direction is three times worse than the resolution in lateral directions. A method to overcome this axial limitation is tilting the object under the microscope, in a way that the direction of the optical axis points into different directions relative to the sample. A new technique for a simultaneous reconstruction from a number of such axial tomographic confocal data sets was developed and used for high resolution reconstruction of 3D‐data both from experimental and virtual microscopic data sets. The reconstructed images have a highly improved 3D resolution, which is comparable to the lateral resolution of a single deconvolved data set. Axial tomographic imaging in combination with simultaneous data reconstruction also opens the possibility for a more precise quantification of 3D data. The color images of this publication can be accessed from http://www.esacp.org/acp/2000/20‐1/heintzmann.htm. At this web address an interactive 3D viewer is additionally provided for browsing the 3D data. This java applet displays three orthogonal slices of the data set which are dynamically updated by user mouse clicks or keystrokes.

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Hybrid processing of laser scanning data

E3S Web of Conferences ◽

10.1051/e3sconf/20183301047 ◽

2018 ◽

Vol 33 ◽

pp. 01047 ◽

Cited By ~ 9

Author(s):

Vladimir Badenko ◽

Dmitry Zotov ◽

Alexander Fedotov

Keyword(s):

Laser Scanning ◽

Building Information Modeling ◽

Information Modeling ◽

Historical Buildings ◽

Historical Building ◽

Historic Building ◽

Technology Application ◽

Hybrid Technology ◽

Building Information

In this article the analysis of gaps in processing of raw laser scanning data and results of bridging the gaps discovered on the base of usage of laser scanning data for historic building information modeling is presented. The results of the development of a unified hybrid technology for the processing, storage, access and visualization of combined laser scanning and photography data about historical buildings are analyzed. The first result of the technology application for the historical building of St. Petersburg Polytechnic University shows reliability of the proposed approaches.

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AN AUTOMATIC PROCEDURE FOR MOBILE LASER SCANNING PLATFORM 6DOF TRAJECTORY ADJUSTMENT

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-1-203-2018 ◽

2018 ◽

Vol XLII-1 ◽

pp. 203-209 ◽

Cited By ~ 2

Author(s):

Z. Hussnain ◽

S. Oude Elberink ◽

G. Vosselman

Keyword(s):

Image Matching ◽

Point Cloud ◽

Laser Scanning ◽

Aerial Image ◽

Second Step ◽

Data Set ◽

B Splines ◽

Image Patches ◽

Trajectory Representation ◽

Previous Step

Abstract. In this paper, a method is presented to improve the MLS platform’s trajectory for GNSS denied areas. The method comprises two major steps. The first step is based on a 2D image registration technique described in our previous publication. Internally, this registration technique first performs aerial to aerial image matching, this issues correspondences which enable to compute the 3D tie points by multiview triangulation. Similarly, it registers the rasterized Mobile Laser Scanning Point Cloud (MLSPC) patches with the multiple related aerial image patches. The later registration provides the correspondence between the aerial to aerial tie points and the MLSPC’s 3D points. In the second step, which is described in this paper, a procedure utilizes three kinds of observations to improve the MLS platform’s trajectory. The first type of observation is the set of 3D tie points computed automatically in the previous step (and are already available), the second type of observation is based on IMU readings and the third type of observation is soft-constraint over related pose parameters. In this situation, the 3D tie points are considered accurate and precise observations, since they provide both locally and globally strict constraints, whereas the IMU observations and soft-constraints only provide locally precise constraints. For 6DOF trajectory representation, first, the pose [R, t] parameters are converted to 6 B-spline functions over time. Then for the trajectory adjustment, the coefficients of B-splines are updated from the established observations. We tested our method on an MLS data set acquired at a test area in Rotterdam, and verified the trajectory improvement by evaluation with independently and manually measured GCPs. After the adjustment, the trajectory has achieved the accuracy of RMSE X=9cm, Y=14cm and Z=14cm. Analysing the error in the updated trajectory suggests that our procedure is effective at adjusting the 6DOF trajectory and to regenerate a reliable MLSPC product.

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Influence of Control Points Configuration on the Mobile Laser Scanning Accuracy

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/906/1/012091 ◽

2021 ◽

Vol 906 (1) ◽

pp. 012091

Author(s):

Petr Kalvoda ◽

Jakub Nosek ◽

Petra Kalvodova

Keyword(s):

Reference Point ◽

Point Cloud ◽

Laser Scanning ◽

Reference Data ◽

Data Sets ◽

Control Points ◽

Mobile Mapping ◽

Data Set ◽

Accuracy Test ◽

Data Subset

Abstract Mobile mapping systems (MMS) are becoming widely used in standard geodetic tasks more commonly in the last years. The paper is focused on the influence of control points (CPs) number and configuration on mobile laser scanning accuracy. The mobile laser scanning (MLS) data was acquired by MMS RIEGL VMX-450. The resulting point cloud was compared with two different reference data sets. The first reference data set consisted of a high-accuracy test point field (TPF) measured by a Trimble R8s GNSS system and a Trimble S8 HP total station. The second reference data set was a point cloud from terrestrial laser scanning (TLS) using two Faro Focus3D X 130 laser scanners. The coordinates of both reference data sets were determined with significantly higher accuracy than the coordinates of the tested MLS point cloud. The accuracy testing is based on coordinate differences between the reference data set and the tested MLS point cloud. There is a minimum number of 6–7 CPs in our scanned area (based on MLS trajectory length) to achieve the declared relative accuracy of trajectory positioning according to the RIEGL datasheet. We tested two types of ground control point (GCP) configurations for 7 GCPs, using TPF reference data. The first type is a trajectory-based CPs configuration, and the second is a geometry-based CPs configuration. The accuracy differences of the MLS point clouds with trajectory-based CPs configuration and geometry-based CPs configuration are not statistically significant. From a practical perspective, a geometry-based CPs configuration is more advantageous in the nonlinear type of urban area such as our one. The following analyzes are performed on geometry-based CPs configuration variants. We tested the influence of changing the location of two CPs from ground to roof. The effect of the vertical configuration of the CPs on the accuracy of the tested MLS point cloud has not been demonstrated. The effect of the number of control points on the accuracy of the MLS point cloud was also tested. In the overall statistics using TPF, the accuracy increases significantly with increasing the number of GCPs up to 6. This number corresponds to a requirement of the manufacturer. Although further increasing the number of CPs does not significantly increase the global accuracy, local accuracy improves with increasing the number of CPs up to 10 (average spacing 50 m) according to the comparison with the TLS reference point cloud. The accuracy test of the MLS point cloud was divided into the horizontal accuracy test on the façade data subset and the vertical accuracy test on the road data subset using the TLS reference point cloud. The results of this paper can help improve the efficiency and accuracy of the mobile mapping process in geodetic praxis.

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The metrological research of the Machu Picchu site. Application of a cosine quantogram method for 3D laser data.

ACTA IMEKO ◽

10.21014/acta_imeko.v6i3.460 ◽

2017 ◽

Vol 6 (3) ◽

pp. 52

Author(s):

Anna Maria Kubicka

Keyword(s):

Point Cloud ◽

Laser Scanning ◽

Statistical Approach ◽

3D Laser Scanning ◽

Metrological Analysis ◽

Data Set ◽

Machu Picchu ◽

Mediterranean Culture ◽

New Information ◽

Metrological Research

The aim of a metrological analysis of the Machu Picchu site is to verify the hypothesis on the functioning of the imperial system of length measurement which was used by the Incas during measurement and construction processes. Data for metrological analyses were obtained from 3D laser scanning as 3D point cloud from where desired length measurements were collected. As far as the research method is concerned, a statistical model of a cosine quantogram was used to find a unit of design from a data set. The method has successfully been introduced during the analysis of architectural sites of the Mediterranean culture but never has been applied in regard to pre-Columbian archaeology. Statistical approach in this study will reveal new information about Inca urban planning based on the elements of architecture design.

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