scholarly journals HBIM, 3D drawing and virtual reality for archaeological sites and ancient ruins

2020 ◽  
Vol 11 (23) ◽  
pp. 16 ◽  
Author(s):  
Fabrizio Banfi
Keyword(s):  
Virtual Reality ◽  
Laser Scanning ◽  
New Technologies ◽  
Three Dimensional ◽  
Point Clouds ◽  
Archaeological Sites ◽  
Digital Information ◽  
Holistic Model ◽  
Digital Modelling ◽  
The Creation

<p class="VARAbstract">Data collection, documentation and analysis of the traces of ancient ruins and archaeological sites represent an inestimable value to be handed down to future generations. Thanks to the development of new technologies in the field of computer graphics, Building Information Modelling (BIM), Virtual Reality (VR) and three-dimensional (3D) digital survey, this research proposes new levels of interactivity between users and virtual environments capable of communicating the tangible and intangible values of remains of ancient ruins. In this particular field of development, 3D drawing and digital modelling are based on the application of new Scan-to-HBIM-to-VR specifications capable of transforming simple points (point clouds) into mathematical models and digital information. Thanks to the direct application of novel grades of generation (GOG) and accuracy (GOA) it has been possible to go beyond the creation of complex models for heritage BIM (HBIM) and explore the creation of informative 3D representation composed by sub-elements (granular HBIM objects) characterized by a further level of knowledge. The value of measurement, 3D drawing and digital modelling have been investigated from the scientific point of view and oriented to the generation of a holistic model able to relate both with architects, engineers, and surveyors but also with archaeologists, restorers and virtual tourists.</p><p>Highlights:</p><ul><li><p>The concept of ‘granular HBIM objects’ is introduced to show the unexpressed potential of the scan-to-BIM process for different types of data analyses and uses.</p></li><li><p>Sustainable development of VR projects for archaeological sites is proposed, allowing users to discover the hidden historical values with new levels of interactivity and information.</p></li><li><p>HBIM and VR projects have been improved through the integration of laser scanning, digital photogrammetry (terrestrial and UAV) and advanced modelling techniques.</p></li></ul>

scholarly journals Three-dimensional model of the Rzeczka object (the Riese Complex, Sowie Range) as an enhancement of the comprehensive geotourism potential of an underground tourist route

2018 ◽  
Vol 55 ◽  
pp. 00015
Author(s):  
Katarzyna Kądziołka ◽  
Damian Kasza ◽  
Wojciech J. Milczarek
Keyword(s):  
Laser Scanning ◽  
Numerical Models ◽  
Three Dimensional ◽  
Point Clouds ◽  
Digital Data ◽  
Measurement Technology ◽  
Three Dimensional Model ◽  
Historic Areas ◽  
The Creation ◽  
Three Dimensional Models

The dynamic development of measurement technology based on the use of laser scanners allows for fast transfer of information, related to terrestrial data, to a virtual environment and enables the creation of three-dimensional models. Because of the growing demand for underground areas inventory, especially historic areas, the creation of 3D numerical models increases in popularity. It allows to increase the geotouristic potential of a particular area and to use solutions in support of the safety of tourists as well as the safety of area itself. The development of the terrestrial laser scanning technique is accompanied simultaneously by the development of means of digital data processing that was obtained in the form of point clouds. Those means use the commercial software as well as software available in the open source system. Both computing environments use algorithms enabling the processing of huge collections of points in automatized mode by using a number of open-access algorithms either freeware or dedicated. The methodology of numerical models development, described in this article, has been presented on the example of underground object “Rzeczka” (“Riese” Complex) located at the Sowie Range (SW Poland).

scholarly journals USING MOBILE LASER SCANNING DATA FOR FEATURES EXTRACTION OF HIGH ACCURACY DRIVING MAPS

2016 ◽  
Vol XLI-B3 ◽  
pp. 433-439 ◽  
Author(s):  
Bisheng Yang ◽  
Yuan Liu ◽  
Fuxun Liang ◽  
Zhen Dong
Keyword(s):  
Laser Scanning ◽  
Human Error ◽  
Traffic Accidents ◽  
Three Dimensional ◽  
Point Clouds ◽  
High Accuracy ◽  
3D Point Clouds ◽  
Assistant Systems ◽  
Novel Method ◽  
High Flexibility

High Accuracy Driving Maps (HADMs) are the core component of Intelligent Drive Assistant Systems (IDAS), which can effectively reduce the traffic accidents due to human error and provide more comfortable driving experiences. Vehicle-based mobile laser scanning (MLS) systems provide an efficient solution to rapidly capture three-dimensional (3D) point clouds of road environments with high flexibility and precision. This paper proposes a novel method to extract road features (e.g., road surfaces, road boundaries, road markings, buildings, guardrails, street lamps, traffic signs, roadside-trees, power lines, vehicles and so on) for HADMs in highway environment. Quantitative evaluations show that the proposed algorithm attains an average precision and recall in terms of 90.6% and 91.2% in extracting road features. Results demonstrate the efficiencies and feasibilities of the proposed method for extraction of road features for HADMs.

scholarly journals Creation of virtual 3D models of the existing architectonic structures using the web resources

Spatium ◽  
2016 ◽  
pp. 30-36 ◽  
Author(s):  
Petar Pejic ◽  
Sonja Krasic
Keyword(s):  
Laser Scanning ◽  
Three Dimensional ◽  
3D Models ◽  
Three Dimensional Model ◽  
Web Resources ◽  
Existing Structures ◽  
Software Packages ◽  
Physical Presence ◽  
The Creation ◽  
Three Dimensional Models

Digital three-dimensional models of the existing architectonic structures are created for the purpose of digitalization of the archive documents, presentation of buildings or an urban entity or for conducting various analyses and tests. Traditional methods for the creation of 3D models of the existing buildings assume manual measuring of their dimensions, using the photogrammetry method or laser scanning. Such approaches require considerable time spent in data acquisition or application of specific instruments and equipment. The goal of this paper is presentation of the procedure for the creation of 3D models of the existing structures using the globally available web resources and free software packages on standard PCs. This shortens the time of the production of a digital three-dimensional model of the structure considerably and excludes the physical presence at the location. In addition, precision of this method was tested and compared with the results acquired in a previous research.

scholarly journals VISUALIZATION OF THE CONSTRUCTION OF ANCIENT ROMAN BUILDINGS IN OSTIA USING POINT CLOUD DATA

2017 ◽  
Vol XLII-2/W3 ◽  
pp. 345-352
Author(s):  
Y. Hori ◽  
T. Ogawa
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Feature Matching ◽  
Three Dimensional ◽  
Point Clouds ◽  
Final Report ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Coverage Accuracy ◽  
New Research

The implementation of laser scanning in the field of archaeology provides us with an entirely new dimension in research and surveying. It allows us to digitally recreate individual objects, or entire cities, using millions of three-dimensional points grouped together in what is referred to as "point clouds". In addition, the visualization of the point cloud data, which can be used in the final report by archaeologists and architects, should usually be produced as a JPG or TIFF file. Not only the visualization of point cloud data, but also re-examination of older data and new survey of the construction of Roman building applying remote-sensing technology for precise and detailed measurements afford new information that may lead to revising drawings of ancient buildings which had been adduced as evidence without any consideration of a degree of accuracy, and finally can provide new research of ancient buildings. We used laser scanners at fields because of its speed, comprehensive coverage, accuracy and flexibility of data manipulation. Therefore, we “skipped” many of post-processing and focused on the images created from the meta-data simply aligned using a tool which extended automatic feature-matching algorithm and a popular renderer that can provide graphic results.

scholarly journals Weighing trees with lasers: advances, challenges and opportunities

2018 ◽  
Vol 8 (2) ◽  
pp. 20170048 ◽  
Author(s):  
M. I. Disney ◽  
M. Boni Vicari ◽  
A. Burt ◽  
K. Calders ◽  
S. L. Lewis ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Large Scale ◽  
Three Dimensional ◽  
Point Clouds ◽  
3D Models ◽  
Tree Form ◽  
Form And Function ◽  
Challenges And Opportunities ◽  
And Function ◽  
Non Destructive

Terrestrial laser scanning (TLS) is providing exciting new ways to quantify tree and forest structure, particularly above-ground biomass (AGB). We show how TLS can address some of the key uncertainties and limitations of current approaches to estimating AGB based on empirical allometric scaling equations (ASEs) that underpin all large-scale estimates of AGB. TLS provides extremely detailed non-destructive measurements of tree form independent of tree size and shape. We show examples of three-dimensional (3D) TLS measurements from various tropical and temperate forests and describe how the resulting TLS point clouds can be used to produce quantitative 3D models of branch and trunk size, shape and distribution. These models can drastically improve estimates of AGB, provide new, improved large-scale ASEs, and deliver insights into a range of fundamental tree properties related to structure. Large quantities of detailed measurements of individual 3D tree structure also have the potential to open new and exciting avenues of research in areas where difficulties of measurement have until now prevented statistical approaches to detecting and understanding underlying patterns of scaling, form and function. We discuss these opportunities and some of the challenges that remain to be overcome to enable wider adoption of TLS methods.

A new drone laser scanning benchmark dataset for characterization of single-tree and forest biophysical properties

2021 ◽  
Author(s):  
Puliti Stefano ◽  
Grant D. Pears ◽  
Michael S. Watt ◽  
Edward Mitchard ◽  
Iain McNicol ◽  
...  
Keyword(s):  
Boreal Forests ◽  
Laser Scanning ◽  
Method Development ◽  
Three Dimensional ◽  
Point Clouds ◽  
Benchmark Dataset ◽  
Validation Dataset ◽  
Tree Structures ◽  
Single Tree ◽  
Individual Trees

&lt;p&gt;Survey-grade drone laser scanners suitable for unmanned aerial vehicles (UAV-LS) allow the efficient collection of finely detailed three-dimensional information of tree structures. This data type allows forests to be resolved into discrete individual trees and has shown promising results in providing accurate in-situ observations of key forestry variables. New and improved approaches for analyzing UAV-LS point clouds have to be developed to transform the vast amounts of data from UAV-LS into actionable insights and decision support. Many different studies have explored various methods for automating single tree detection, segmentation, parsing into different tree components, and measurement of biophysical variables (e.g., diameter at breast height). Despite the considerable efforts dedicated to developing automated ways to process UAV-LS data into useful data, current methods tend to be tailored to small datasets, and it remains challenging to evaluate the performance of different algorithms based on a consistent validation dataset. To fill this knowledge gap and to further advance our ability to measure forests from UAV-LS data, we present a new benchmarking dataset. This data is composed of manually labelled UAV-LS data acquired a number of continents and biomes which span tropical to boreal forests. The UAV-LS data was collected exclusively used survey-grade sensors such as the Riegl VUX and mini-VUX series which are characterized by a point density in the range&amp;#160;1 &amp;#8211; 10 k points m&lt;sup&gt;2&lt;/sup&gt;. Currently, such data represent the state-of-the-art in aerial laser scanning data. The benchmark data consists of a library of single-tree point clouds, aggregated to sample plots, with each point classified as either stem, branch, or leaves. With the objective of releasing such a benchmark dataset as a public asset, in the future, researchers will be able to leverage such pre-existing labelled trees for developing new methods to measure forests from UAV-LS data. The availability of benchmarking datasets represents an important driver for enabling the development of robust and accurate methods. Such a benchmarking dataset will also be important for a consistent comparison of existing or future algorithms which will guide future method development.&lt;/p&gt;

The Data Imperative

2020 ◽  
pp. 19-43
Author(s):  
Henri Schildt
Keyword(s):  
Real Time ◽  
Business Processes ◽  
New Technologies ◽  
Digital Data ◽  
Digital Information ◽  
Information Flows ◽  
End Point ◽  
The World ◽  
The Creation ◽  
And Control

This chapter examines digitalization as a set of new normative ideals for managing and organizing businesses, enabled by new technologies. The data imperative consists of two mutually reinforcing goals: the pursuit of omniscience—the aspiration of management to capture the world relevant to the company through digital data; and the pursuit of omnipotence—an aspiration of managers to control and optimize activities in real-time and around the world through software. The data imperative model captures a self-reinforcing cycle of four sequential steps: (1) the creation and capture of data, (2) the combination and analysis of data, (3) the redesign of business processes around smart algorithms, and (4) the ability to control the world through digital information flows. The logical end-point of the data imperative is a ‘programmable world’, a conception of society saturated with Internet-connected hardware that is able to capture processes in real time and control them in order to optimize desired outcomes.

scholarly journals Toward a Novel Laser-Based Approach for Estimating Snow Interception

2020 ◽  
Vol 12 (7) ◽  
pp. 1146 ◽  
Author(s):  
Micah Russell ◽  
Jan U. H. Eitel ◽  
Andrew J. Maguire ◽  
Timothy E. Link
Keyword(s):  
Laser Scanning ◽  
Three Dimensional ◽  
Point Clouds ◽  
Primary Objective ◽  
Snow Accumulation ◽  
Future Research ◽  
Snow Density ◽  
Canopy Interception ◽  
Terrestrial Lidar ◽  
Large Trees

Forests reduce snow accumulation on the ground through canopy interception and subsequent evaporative losses. To understand snow interception and associated hydrological processes, studies have typically relied on resource-intensive point scale measurements derived from weighed trees or indirect measurements that compared snow accumulation between forested sites and nearby clearings. Weighed trees are limited to small or medium-sized trees, and indirect comparisons can be confounded by wind redistribution of snow, branch unloading, and clearing size. A potential alternative method could use terrestrial lidar (light detection and ranging) because three-dimensional lidar point clouds can be generated for any size tree and can be utilized to calculate volume of the intercepted snow. The primary objective of this study was to provide a feasibility assessment for estimating snow interception volume with terrestrial laser scanning (TLS), providing information on challenges and opportunities for future research. During the winters of 2017 and 2018, intercepted snow masses were continuously measured for two model trees suspended from load-cells. Simultaneously, autonomous terrestrial lidar scanning (ATLS) was used to develop volumetric estimates of intercepted snow. Multiplying ATLS volume estimates by snow density estimates (derived from empirical models based on air temperature) enabled the comparison of predicted vs. measured snow mass. Results indicate agreement between predicted and measured values (R2 ≥ 0.69, RMSE ≥ 0.91 kg, slope ≥ 0.97, intercept ≥ −1.39) when multiplying TLS snow interception volume with a constant snow density estimate. These results suggest that TLS might be a viable alternative to traditional approaches for mapping snow interception, potentially useful for estimating snow loads on large trees, collecting data in difficult to access terrain, and calibrating snow interception models to new forest types around the globe.

scholarly journals Mobile Laser Scanning Data for the Evaluation of Pavement Surface Distress

2020 ◽  
Vol 12 (6) ◽  
pp. 942 ◽  
Author(s):  
Maria Rosaria De Blasiis ◽  
Alessandro Di Benedetto ◽  
Margherita Fiani
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Road Traffic ◽  
Single Point ◽  
Three Dimensional ◽  
Point Clouds ◽  
Road Surface ◽  
Important Indicator ◽  
The Road ◽  
Laser Systems

The surface conditions of road pavements, including the occurrence and severity of distresses present on the surface, are an important indicator of pavement performance. Periodic monitoring and condition assessment is an essential requirement for the safety of vehicles moving on that road and the wellbeing of people. The traditional characterization of the different types of distress often involves complex activities, sometimes inefficient and risky, as they interfere with road traffic. The mobile laser systems (MLS) are now widely used to acquire detailed information about the road surface in terms of a three-dimensional point cloud. Despite its increasing use, there are still no standards for the acquisition and processing of the data collected. The aim of our work was to develop a procedure for processing the data acquired by MLS, in order to identify the localized degradations that mostly affect safety. We have studied the data flow and implemented several processing algorithms to identify and quantify a few types of distresses, namely potholes and swells/shoves, starting from very dense point clouds. We have implemented data processing in four steps: (i) editing of the point cloud to extract only the points belonging to the road surface, (ii) determination of the road roughness as deviation in height of every single point of the cloud with respect to the modeled road surface, (iii) segmentation of the distress (iv) computation of the main geometric parameters of the distress in order to classify it by severity levels. The results obtained by the proposed methodology are promising. The procedures implemented have made it possible to correctly segmented and identify the types of distress to be analyzed, in accordance with the on-site inspections. The tests carried out have shown that the choice of the values of some parameters to give as input to the software is not trivial: the choice of some of them is based on considerations related to the nature of the data, for others, it derives from the distress to be segmented. Due to the different possible configurations of the various distresses it is better to choose these parameters according to the boundary conditions and not to impose default values. The test involved a 100-m long urban road segment, the surface of which was measured with an MLS installed on a vehicle that traveled the road at 10 km/h.

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