scholarly journals PARAMETERIC ANALYSIS FOR AUTOMATED EXTRACTION OF ROAD EDGES FROM MOBILE LASER SCANNING DATA

Author(s):  
P. Kumar ◽  
P. Lewis ◽  
C. P. McElhinney

The applicability of Mobile Laser Scanning (MLS) systems continue to prove their worth in route corridor mapping due to the rapid, continuous and cost effective 3D data acquisition capability. LiDAR data provides a number of attributes which can be useful for extracting various road features. Road edge is a fundamental feature and its accurate knowledge increases the reliability and precision of extracting other road features. We developed an automated algorithm for extracting left and right edges from MLS data. The algorithm involved several input parameters which are required to be analysed in order to find their optimal values. In this paper, we present a detailed analysis of the dimension parameters of input data and raster cell in our algorithm. These parameters were analysed based on temporal, completeness and accuracy performance of our algorithm for their different sets of values. This analysis provided the estimation of an optimal values of parameters which were used to automate the process of extracting road edges from MLS data.

2020 ◽  
Vol 8 (3) ◽  
pp. 143-150
Author(s):  
Haqul Baramsyah ◽  
Less Rich

The digital single lens reflex (DSLR) cameras have been widely accepted to use in slope face photogrammetry rather than the expensive metric camera used for aerial photogrammetry. 3D models generated from digital photogrammetry can approach those generated from terrestrial laser scanning in term of scale and level of detail. It is cost effective and has equipment portability. This paper presents and discusses the applicability of close-range digital photogrammetry to produce 3D models of rock slope faces. Five experiments of image capturing method were conducted to capture the photographs as the input data for processing. As a consideration, the appropriate baseline lengths to capture the slope face to get better result are around 1/6 to 1/8 of target distance.  A fine quality of 3D model from data processing is obtained using strip method and convergent method with 80% overlapping in each photograph. A random camera positions with different distances from the slope face can also generate a good 3D model, however the entire target should be captured in each photograph. The accuracy of the models is generated by comparing the 3D models produced from photogrammetry with the 3D data obtained from laser scanner. The accuracy of 3D models is quite satisfactory with the mean error range from 0.008 to 0.018 m.


Author(s):  
Alireza Shams ◽  
Wayne A. Sarasua ◽  
Afshin Famili ◽  
William J. Davis ◽  
Jennifer H. Ogle ◽  
...  

Ensuring adequate pavement cross-slope on highways can improve driver safety by reducing the potential for ponding to occur or vehicles to hydroplane. Mobile laser scanning (MLS) systems provide a rapid, continuous, and cost-effective means of collecting accurate 3D coordinate data along a corridor in the form of a point cloud. This study provides an evaluation of MLS systems in terms of the accuracy and precision of collected cross-slope data and documentation of procedures needed to calibrate, collect, and process this data. Mobile light detection and ranging (LiDAR) data were collected by five different vendors on three roadway sections. The results indicate the difference between ground control adjusted and unadjusted LiDAR derived cross-slopes, and field surveying measurements less than 0.19% at a 95% confidence level. The unadjusted LiDAR data incorporated corrections from an integrated inertial measurement unit and high-accuracy real-time kinematic GPS, however it was not post-processed adjusted with ground control points. This level of accuracy meets suggested cross-slope accuracies for mobile measurements (±0.2%) and demonstrates that mobile LiDAR is a reliable method for cross-slope verification. Performing cross-slope verification can ensure existing pavement meets minimum cross-slope requirements, and conversely is useful in identifying roadway sections that do not meet minimum standards, which is more desirable than through crash reconnaissance where hydroplaning was evident. Adoption of MLS would enable the South Carolina Department of Transportation (SCDOT) to address cross-slope issues through efficient and accurate data collection methods.


2020 ◽  
pp. 2-11
Author(s):  
B.A. Novakovsky ◽  
◽  
A.V. Kudryavtsev ◽  
A.L. Entin ◽  
◽  
...  

The paper considers GIS software which may be utilized for airborne lidar data processing. Software list includes proprietary MicroStation with TerraScan plugin, Global Mapper, ArcGIS, ERDAS Imagine, LAStools, as well as free and open source SAGA, WhiteboxTools, and PDAL.io. Possibilities of import-export, 2D and 3D data visualization, point cloud editing and derivation of GIS datasets are examined for each software. Computational efficiency assessment is performed for the procedure of interpolation point elevation data in different software. As a result, the advantages and disadvantages of the considered programs were identified in relation to various tasks. Key words: airborne laser scanning, software, geoinformation mapping, computational efficiency.


2018 ◽  
Vol 933 (3) ◽  
pp. 52-62
Author(s):  
V.S. Tikunov ◽  
I.A. Rylskiy ◽  
S.B. Lukatzkiy

Innovative methods of aerial surveys changed approaches to information provision of projecting dramatically in last years. Nowadays there are several methods pretending to be the most efficient for collecting geospatial data intended for projecting – airborne laser scanning (LIDAR) data, RGB aerial imagery (forming 3D pointclouds) and orthoimages. Thermal imagery is one of the additional methods that can be used for projecting. LIDAR data is precise, it allows us to measure relief even under the vegetation, or to collect laser re-flections from wires, metal constructions and poles. Precision and completeness of the DEM, produced from LIDAR data, allows to define relief microforms. Airborne imagery (visual spectrum) is very widespread and can be easily depicted. Thermal images are more strange and less widespread, they use different way of image forming, and spectral features of ob-jects can vary in specific ways. Either way, the additional spectral band can be useful for achieving additional spatial data and different object features, it can minimize field works. Here different aspects of thermal imagery are described in comparison with RGB (visual) images, LIDAR data and GIS layers. The attempt to estimate the feasibility of thermal imag-es for new data extraction is made.


2020 ◽  
Vol 12 (15) ◽  
pp. 2497
Author(s):  
Rohan Bennett ◽  
Peter van Oosterom ◽  
Christiaan Lemmen ◽  
Mila Koeva

Land administration constitutes the socio-technical systems that govern land tenure, use, value and development within a jurisdiction. The land parcel is the fundamental unit of analysis. Each parcel has identifiable boundaries, associated rights, and linked parties. Spatial information is fundamental. It represents the boundaries between land parcels and is embedded in cadastral sketches, plans, maps and databases. The boundaries are expressed in these records using mathematical or graphical descriptions. They are also expressed physically with monuments or natural features. Ideally, the recorded and physical expressions should align, however, in practice, this may not occur. This means some boundaries may be physically invisible, lacking accurate documentation, or potentially both. Emerging remote sensing tools and techniques offers great potential. Historically, the measurements used to produce recorded boundary representations were generated from ground-based surveying techniques. The approach was, and remains, entirely appropriate in many circumstances, although it can be timely, costly, and may only capture very limited contextual boundary information. Meanwhile, advances in remote sensing and photogrammetry offer improved measurement speeds, reduced costs, higher image resolutions, and enhanced sampling granularity. Applications of unmanned aerial vehicles (UAV), laser scanning, both airborne and terrestrial (LiDAR), radar interferometry, machine learning, and artificial intelligence techniques, all provide examples. Coupled with emergent societal challenges relating to poverty reduction, rapid urbanisation, vertical development, and complex infrastructure management, the contemporary motivation to use these new techniques is high. Fundamentally, they enable more rapid, cost-effective, and tailored approaches to 2D and 3D land data creation, analysis, and maintenance. This Special Issue hosts papers focusing on this intersection of emergent remote sensing tools and techniques, applied to domain of land administration.


2017 ◽  
Vol 5 (2) ◽  
pp. 293-310 ◽  
Author(s):  
Ryan A. Kromer ◽  
Antonio Abellán ◽  
D. Jean Hutchinson ◽  
Matt Lato ◽  
Marie-Aurelie Chanut ◽  
...  

Abstract. We present an automated terrestrial laser scanning (ATLS) system with automatic near-real-time change detection processing. The ATLS system was tested on the Séchilienne landslide in France for a 6-week period with data collected at 30 min intervals. The purpose of developing the system was to fill the gap of high-temporal-resolution TLS monitoring studies of earth surface processes and to offer a cost-effective, light, portable alternative to ground-based interferometric synthetic aperture radar (GB-InSAR) deformation monitoring. During the study, we detected the flux of talus, displacement of the landslide and pre-failure deformation of discrete rockfall events. Additionally, we found the ATLS system to be an effective tool in monitoring landslide and rockfall processes despite missing points due to poor atmospheric conditions or rainfall. Furthermore, such a system has the potential to help us better understand a wide variety of slope processes at high levels of temporal detail.


2017 ◽  
Vol 24 (s1) ◽  
pp. 174-181 ◽  
Author(s):  
Zygmunt Paszotta ◽  
Malgorzata Szumilo ◽  
Jakub Szulwic

Abstract This paper intends to point out the possibility of using Internet photogrammetry to construct 3D models from the images obtained by means of UAVs (Unmanned Aerial Vehicles). The solutions may be useful for the inspection of ports as to the content of cargo, transport safety or the assessment of the technical infrastructure of port and quays. The solution can be a complement to measurements made by using laser scanning and traditional surveying methods. In this paper the authors recommend a solution useful for creating 3D models from images acquired by the UAV using non-metric images from digital cameras. The developed algorithms, created and presented software allows to generate 3D models through the Internet in two modes: anaglyph and display in shutter systems. The problem of 3D image generation in photogrammetry is solved by using epipolar images. The appropriate method was presented by Kreiling in 1976. However, it applies to photogrammetric images for which the internal orientation is known. In the case of digital images obtained with non-metric cameras it is required to use another solution based on the fundamental matrix concept, introduced by Luong in 1992. In order to determine the matrix which defines the relationship between left and right digital image it is required to have at least eight homologous points. To determine the solution it is necessary to use the SVD (singular value decomposition). By using the fundamental matrix the epipolar lines are determined, which makes the correct orientation of images making stereo pairs, possible. The appropriate mathematical bases and illustrations are included in the publication.


Author(s):  
J. Gehrung ◽  
M. Hebel ◽  
M. Arens ◽  
U. Stilla

Abstract. Change detection is an important tool for processing multiple epochs of mobile LiDAR data in an efficient manner, since it allows to cope with an otherwise time-consuming operation by focusing on regions of interest. State-of-the-art approaches usually either do not handle the case of incomplete observations or are computationally expensive. We present a novel method based on a combination of point clouds and voxels that is able to handle said case, thereby being computationally less expensive than comparable approaches. Furthermore, our method is able to identify special classes of changes such as partially moved, fully moved and deformed objects in addition to the appeared and disappeared objects recognized by conventional approaches. The performance of our method is evaluated using the publicly available TUM City Campus datasets, showing an overall accuracy of 88 %.


2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Fan Yang ◽  
Xintao Wen ◽  
Xiaoshan Wang ◽  
Xiaoli Li ◽  
Zhiqiang Li

Earthquake disasters can have a serious impact on people’s lives and property, with damage to buildings being one of the main causes of death and injury. A rapid assessment of the extent of building damage is essential for emergency response management, rescue operations, and reconstruction. Terrestrial laser scanning technology can obtain high precision light detection and ranging (LiDAR) point cloud data of the target. The technology is widely used in various fields; however, the quantitative analysis of building seismic information is the focus and difficulty of ground-based LiDAR data analysis processing. This paper takes full advantage of the high-precision characteristics of ground-based LiDAR data. A triangular network vector model (TIN-shaped model) was created in conjunction with the alpha shapes algorithm, solving the problem of small, nonvisually identifiable postearthquake building damage feature extraction bias. The model measures the length, width, and depth of building cracks, extracts the amount of wall tilt deformation, and labels the deformation zone. The creation of this model can provide scientific basis and technical support for postearthquake emergency relief, assessment of damage to buildings, extraction of deformation characteristics of other structures (bridges, tunnels, dams, etc.), and seismic reinforcement of buildings. The research data in this paper were collected by the author’s research team in the first time after the 2013 Lushan earthquake and is one of the few sets of foundation of LiDAR data covering the full range of postearthquake building types in the region, with the data information mainly including different damage levels of different structural types of buildings. The modeling analysis of this data provides a scientific basis for establishing the earthquake damage matrix of buildings in the region.


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