scholarly journals MODELLING IMMOVABLE ASSET IN 3D USING CITYGML 3.0 CONCEPT TO SUPPORT SMART CITY INITIATIVES

2021 ◽  
Vol XLVI-4/W5-2021 ◽  
pp. 391-396
Author(s):  
A. A. M. Nasir ◽  
S. Azri ◽  
U. Ujang
Keyword(s):  
Asset Management ◽  
Laser Scanning ◽  
Smart Cities ◽  
Management Practice ◽  
City Council ◽  
Data Set ◽  
Cloud Data ◽  
Aerial Vehicle ◽  
Effective Cost ◽  
Asset Management System

Abstract. Urbanization phenomenon is a key role that contributes to the smart cities development. The expansion of urban growth requires everything to be smart and controlled by advance technology for efficient urban management. One of the important aspects that often overlooked in realizing smart cities is asset management. Asset management is an approach for managing, monitoring and maintenance of assets. Previous studies showed that there are several efforts in managing asset by integrating the asset with Geographic Information System (GIS). However, several limitations can be seen from the studies such as unavailability of real visualization and limitation on asset descriptions although we believe that 3D offers rich information and real visualization for asset management practice. Therefore, to achieve an effective asset management, we proposed to conceptualize the asset with the latest version of CityGML 3.0. The aim of this paper is to model the immovable asset using CityGML 3.0 concept. We adopted the concept of occupied and unoccupied spaces to model the public hall, owned by Johor Bahru City Council (MBJB). The hall was modelled based on point cloud data set from Terrestrial Laser Scanning (TLS) and Unmanned Aerial Vehicle (UAV). The attribute data for the hall was stored in 3DCityDB for information retrieval and query. The result showed that the hall was successfully visualized and information regarding the asset can be retrieved. With this approach, it is believed that an effective 3D asset management system can be developed in the future, to ensure adequate system performance and effective cost operational.

scholarly journals Detailed point cloud data on stem size and shape of Scots pine trees

2020 ◽  
Author(s):  
Ninni Saarinen ◽  
Ville Kankare ◽  
Tuomas Yrttimaa ◽  
Niko Viljanen ◽  
Eija Honkavaara ◽  
...  
Keyword(s):  
Scots Pine ◽  
Boreal Forests ◽  
Laser Scanning ◽  
Point Clouds ◽  
Data Set ◽  
Cloud Data ◽  
Stem Size ◽  
Size And Shape ◽  
Pine Trees ◽  
Tree Stem

AbstractQuantitative assessment of the effects of forest management on tree size and shape has been challenging as there has been a lack of methodologies for characterizing differences and possible changes comprehensively in space and time. Terrestrial laser scanning (TLS) and photogrammetric point clouds provide three-dimensional (3D) information on tree stem reconstructions required for characterizing differences between stem shapes and growth allocation. This data set includes 3D reconstructions of stems of Scots pine (Pinus sylvestris L.) trees from sample plots with different thinning treatments. The thinning treatments include two intensities of thinning, three thinning types as well as control (i.e. no thinning treatment since the establishment). The data set can be used in developing point clouds processing algorithms for single tree stem reconstruction and for investigating variation in stem size and shape of Scots pine trees. Additionally, it offers possibilities in characterizing the effects of various thinning treatments on stem size and shape of Scots pine trees from boreal forests.Data setZenodo https://zenodo.org/record/3701271Data set licenseAttribution 4.0 International (CC BY 4.0)

scholarly journals Characterising Termite Mounds in a Tropical Savanna with UAV Laser Scanning

2021 ◽  
Vol 13 (3) ◽  
pp. 476
Author(s):  
Barbara D’hont ◽  
Kim Calders ◽  
Harm Bartholomeus ◽  
Tim Whiteside ◽  
Renee Bartolo ◽  
...  
Keyword(s):  
High Resolution ◽  
Laser Scanning ◽  
Point Clouds ◽  
Limited Area ◽  
Termite Mound ◽  
Termite Mounds ◽  
Data Set ◽  
High Resolution Data ◽  
Airborne Laser ◽  
Aerial Vehicle

Termite mounds are found over vast areas in northern Australia, delivering essential ecosystem services, such as enhancing nutrient cycling and promoting biodiversity. Currently, the detection of termite mounds over large areas requires airborne laser scanning (ALS) or high-resolution satellite data, which lack precise information on termite mound shape and size. For detailed structural measurements, we generally rely on time-consuming field assessments that can only cover a limited area. In this study, we explore if unmanned aerial vehicle (UAV)-based observations can serve as a precise and scalable tool for termite mound detection and morphological characterisation. We collected a unique data set of terrestrial laser scanning (TLS) and UAV laser scanning (UAV-LS) point clouds of a woodland savanna site in Litchfield National Park (Australia). We developed an algorithm that uses several empirical parameters for the semi-automated detection of termite mounds from UAV-LS and used the TLS data set (1 ha) for benchmarking. We detected 81% and 72% of the termite mounds in the high resolution (1800 points m−2) and low resolution (680 points m−2) UAV-LS data, respectively, resulting in an average detection of eight mounds per hectare. Additionally, we successfully extracted information about mound height and volume from the UAV-LS data. The high resolution data set resulted in more accurate estimates; however, there is a trade-off between area and detectability when choosing the required resolution for termite mound detection Our results indicate that UAV-LS data can be rapidly acquired and used to monitor and map termite mounds over relatively large areas with higher spatial detail compared to airborne and spaceborne remote sensing.

scholarly journals THREE-DIMENSIONAL RECORDING OF BASTION MIDDLEBURG MONUMENT USING TERRESTRIAL LASER SCANNER

2016 ◽  
Vol XLI-B5 ◽  
pp. 323-326
Author(s):  
Z. Majid ◽  
C. L. Lau ◽  
A. R. Yusoff
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Cloud Model ◽  
Three Dimensional ◽  
Third Party ◽  
Scanning System ◽  
Point Cloud Data ◽  
Data Set ◽  
Cloud Data ◽  
Spherical Target

This paper describes the use of terrestrial laser scanning for the full three-dimensional (3D) recording of historical monument, known as the Bastion Middleburg. The monument is located in Melaka, Malaysia, and was built by the Dutch in 1660. This monument serves as a major hub for the community when conducting commercial activities in estuaries Malacca and the Dutch build this monument as a control tower or fortress. The monument is located on the banks of the Malacca River was built between Stadhuys or better known as the Red House and Mill Quayside. The breakthrough fort on 25 November 2006 was a result of the National Heritage Department through in-depth research on the old map. The recording process begins with the placement of measuring targets at strategic locations around the monument. Spherical target was used in the point cloud data registration. The scanning process is carried out using a laser scanning system known as a terrestrial scanner Leica C10. This monument was scanned at seven scanning stations located surrounding the monument with medium scanning resolution mode. Images of the monument have also been captured using a digital camera that is setup in the scanner. For the purposes of proper registration process, the entire spherical target was scanned separately using a high scanning resolution mode. The point cloud data was pre-processed using Leica Cyclone software. The pre-processing process starting with the registration of seven scan data set through overlapping spherical targets. The post-process involved in the generation of coloured point cloud model of the monument using third-party software. The orthophoto of the monument was also produced. This research shows that the method of laser scanning provides an excellent solution for recording historical monuments with true scale of and texture.

scholarly journals Point cloud data from terrestrial laser scanning for volume modelling of Scots pine trees

2020 ◽  
Author(s):  
Ninni Saarinen ◽  
Ville Kankare ◽  
Jiri Pyörälä ◽  
Tuomas Yrttimaa ◽  
Xinlian Liang ◽  
...  
Keyword(s):  
Scots Pine ◽  
Point Cloud ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Point Cloud Data ◽  
Data Set ◽  
Cloud Data ◽  
Pine Trees ◽  
Stem Shape ◽  
Shape And Size

Stem shape and size develop through time especially due to changing environmental characteristics but especially if and when forest management activities change. Terrestrial laser scanning (TLS) provides detailed information on stem shape and size and can enable large and comprehensive data sets for various modelling applications. We collected diameter at breast height and tree height information with traditional field measurements as well as preprocessed TLS point cloud data on 230 Scots pine trees (Pinus sylvestris L.) from southern Finland. The data set described here includes three-dimensional information on Scots pine tree stems derived from TLS point clouds. The usage of this data set can include, but is not limited to, development of point cloud processing algorithms for single tree stem reconstruction and investigations of stem volume modelling for Scots pine.

scholarly journals Application of Remote Sensing Data for Evaluation of Rockfall Potential within a Quarry Slope

2019 ◽  
Vol 8 (9) ◽  
pp. 367 ◽  
Author(s):  
Robiati ◽  
Eyre ◽  
Vanneschi ◽  
Francioni ◽  
Venn ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Numerical Simulations ◽  
Laser Scanning ◽  
Remote Sensing Data ◽  
Terrestrial Lidar ◽  
Cloud Data ◽  
Geometrical Properties ◽  
Use Of Data ◽  
Mechanical Characterisation ◽  
Aerial Vehicle

In recent years data acquisition from remote sensing has become readily available to the quarry sector. This study demonstrates how such data may be used to evaluate and back analyse rockfall potential of a legacy slope in a blocky rock mass. Use of data obtained from several aerial LiDAR (Light Detection and Ranging) and photogrammetric campaigns taken over a number of years (2011 to date) provides evidence for potential rockfall evolution from a slope within an active quarry operation in Cornwall, UK. Further investigation, through analysis of point cloud data obtained from terrestrial laser scanning, was undertaken to characterise the orientation of discontinuities present within the rock slope. Aerial and terrestrial LiDAR data were subsequently used for kinematic analysis, production of surface topography models and rockfall trajectory analyses using both 2D and 3D numerical simulations. The results of an Unmanned Aerial Vehicle (UAV)-based 3D photogrammetric analysis enabled the reconstruction of high resolution topography, allowing one to not only determine geometrical properties of the slope surface and geo-mechanical characterisation but provide data for validation of numerical simulations. The analysis undertaken shows the effectiveness of the existing rockfall barrier, while demonstrating how photogrammetric data can be used to inform back analyses of the underlying failure mechanism and investigate potential runout.

scholarly journals THREE-DIMENSIONAL RECORDING OF BASTION MIDDLEBURG MONUMENT USING TERRESTRIAL LASER SCANNER

2016 ◽  
Vol XLI-B5 ◽  
pp. 323-326
Author(s):  
Z. Majid ◽  
C. L. Lau ◽  
A. R. Yusoff
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Cloud Model ◽  
Three Dimensional ◽  
Third Party ◽  
Scanning System ◽  
Point Cloud Data ◽  
Data Set ◽  
Cloud Data ◽  
Spherical Target

This paper describes the use of terrestrial laser scanning for the full three-dimensional (3D) recording of historical monument, known as the Bastion Middleburg. The monument is located in Melaka, Malaysia, and was built by the Dutch in 1660. This monument serves as a major hub for the community when conducting commercial activities in estuaries Malacca and the Dutch build this monument as a control tower or fortress. The monument is located on the banks of the Malacca River was built between Stadhuys or better known as the Red House and Mill Quayside. The breakthrough fort on 25 November 2006 was a result of the National Heritage Department through in-depth research on the old map. The recording process begins with the placement of measuring targets at strategic locations around the monument. Spherical target was used in the point cloud data registration. The scanning process is carried out using a laser scanning system known as a terrestrial scanner Leica C10. This monument was scanned at seven scanning stations located surrounding the monument with medium scanning resolution mode. Images of the monument have also been captured using a digital camera that is setup in the scanner. For the purposes of proper registration process, the entire spherical target was scanned separately using a high scanning resolution mode. The point cloud data was pre-processed using Leica Cyclone software. The pre-processing process starting with the registration of seven scan data set through overlapping spherical targets. The post-process involved in the generation of coloured point cloud model of the monument using third-party software. The orthophoto of the monument was also produced. This research shows that the method of laser scanning provides an excellent solution for recording historical monuments with true scale of and texture.

scholarly journals Multimodal spatial mapping and visualisation of Dinaledi Chamber and Rising Star Cave

2016 ◽  
Vol Volume 112 (Number 1/2) ◽  
Author(s):  
Ashley Kruger ◽  
Patrick Randolph-Quinney ◽  
Marina Elliott ◽  
◽  
◽  
...  
Keyword(s):  
Laser Scanning ◽  
Survey Methods ◽  
Ground Surface ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Excavation Process ◽  
Aerial Vehicle ◽  
Fossil Hominin ◽  
Excavation Site ◽  
Collection Methods

Abstract The Dinaledi Chamber of the Rising Star Cave has yielded 1550 identifiable fossil elements – representing the largest single collection of fossil hominin material found on the African continent to date. The fossil chamber in which Homo naledi was found was accessible only through a near-vertical chute that presented immense practical and methodological limitations on the excavation and recording methods that could be used within the Cave. In response to practical challenges, a multimodal set of recording and survey methods was thus developed and employed: (1) recording of fossils and the excavation process was achieved through the use of white-light photogrammetry and laser scanning; (2) mapping of the Dinaledi Chamber was accomplished by means of high-resolution laser scanning, with scans running from the excavation site to the ground surface and the cave entrance; (3) at ground surface, the integration of conventional surveying techniques as well as photogrammetry with the use of an unmanned aerial vehicle was applied. Point cloud data were used to provide a centralised and common data structure for conversion and to corroborate the influx of different data collection methods and input formats. Data collected with these methods were applied to the excavations, mapping and surveying of the Dinaledi Chamber and the Rising Star Cave. This multimodal approach provides a comprehensive spatial framework from individual bones to landscape level

scholarly journals AUTOMATED ROAD INFORMATION EXTRACTION FROM HIGH RESOLUTION AERIAL LIDAR DATA FOR SMART ROAD APPLICATIONS

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 533-539
Author(s):  
M. Previtali ◽  
L. Barazzetti ◽  
M. Scaioni
Keyword(s):  
High Resolution ◽  
Asset Management ◽  
Laser Scanning ◽  
Lidar Data ◽  
Automated Identification ◽  
Data Set ◽  
Large Variability ◽  
Airborne Laser ◽  
Multi Level ◽  
3D Information

Abstract. Automatic extraction of road features from LiDAR data is a fundamental task for different applications, including asset management. The availability of updated and reliable models is even more important in the context of smart roads. One of the main advantages of LiDAR data compared with other sensing instruments is the possibility to directly get 3D information. However, the task of deriving road networks form LiDAR data acquired with Airborne Laser Scanning (ALS) may be quite complex due to occlusions, low feature separability and shadowing from contextual objects. Indeed, even if roads elements can be identified in the ALS point cloud, the automated identification of the network starting form them can be involved due to large variability in the size of roads, shapes and presence of connected off-road features such as parking lots. This paper presents a workflow aimed at partially solving the automatic creation of a road network from high-resolution ALS data. The presented method consists of three main steps: (i) labelling of road points; (ii) a multi-level voting scheme; and (iii) the regularization of the extracted road segments. The developed method has been tested using the “Vaihingen”, “Toronto” and “Tobermory” data set provided by the ISPRS.

Development of the 3D dome model based on a terrestrial laser scanner

2018 ◽  
Vol 36 (2) ◽  
pp. 122-136 ◽  
Author(s):  
Abdul Fatah Firdaus Abu Hanipah ◽  
Khairul Nizam Tahar
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
3D Model ◽  
Laser Scanner ◽  
Terrestrial Laser Scanner ◽  
Model Assessment ◽  
Point Cloud Data ◽  
Data Set ◽  
Content Type ◽  
Cloud Data

Purpose Laser scanning technique is used to measure and model objects using point cloud data generated laser pulses. Conventional techniques to construct 3D models are time consuming, costly and need more manpower. The purpose of this paper is to assess the 3D model of the Sultan Salahuddin Abdul Aziz Shah Mosque’s main dome using a terrestrial laser scanner. Design/methodology/approach A laser scanner works through line of sight, which indicates that multiple scans need to be taken from a different view to ensure a complete data set. Targets must spread in all directions, and targets should be placed on fixed structures and flat surfaces for the normal scan and fine scan. After the scanning operation, point cloud data from the laser scanner were cleaned and registered before a 3D model could be developed. Findings As a result, the reconstruction of the 3D model was successfully developed. The samples are based on the triangle dimension, curve line, horizontal dimension and vertical dimension at the dome. The standard deviation and accuracy are calculated based on the comparison of the 21 samples taken between the high-resolution and low-resolution scanning data. Originality/value There are many ways to develop the 3D model and based on this study, the less complex ways also produce the best result. The authors implement the different types of dimensions for the 3D model assessment, which have not yet been considered in the past.

scholarly journals A BIG DATA APPROACH FOR COMPREHENSIVE URBAN SHADOW ANALYSIS FROM AIRBORNE LASER SCANNING POINT CLOUDS

2019 ◽  
Vol IV-4/W8 ◽  
pp. 131-137
Author(s):  
A. V. Vo ◽  
D. F. Laefer
Keyword(s):  
Point Cloud ◽  
Input Data ◽  
Laser Scanning ◽  
Point Clouds ◽  
Airborne Laser Scanning ◽  
Data Set ◽  
Cloud Data ◽  
Airborne Laser ◽  
Alternative Approach ◽  
Hadoop Cluster

<p><strong>Abstract.</strong> Because of the importance of access to sunlight, shadow analysis is a common consideration in urban design, especially for dense urban developments. As shadow computation is computationally expensive, most urban shadow analysis tools have to date circumvented the high computational costs by representing urban complexity only through simplified geometric models. The simplification process removes details and adversely affects the level of realism of the ultimate results. In this paper, an alternative approach is presented by utilizing the highest level of detail and resolution captured in the geometric input data source, which is an extremely high-resolution airborne laser scanning point cloud (300 points/m2). To cope with the high computational demand caused by the use of this dense and detailed input data set, the Comprehensive Urban Shadow algorithm is introduced to distribute the computation for parallel processing on a Hadoop cluster. The proposed comprehensive urban shadow analysis solution is scalable, reasonably fast, and capable of preserving the original resolution and geometric detail of the original point cloud data.</p>

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