scholarly journals MAPPING ROADWAY DRAINAGE DITCHES USING MOBILE LIDAR

2020 ◽  
Vol XLIII-B1-2020 ◽  
pp. 187-192
Author(s):  
Y.-C. Lin ◽  
D. Bullock ◽  
A. Habib
Keyword(s):  
Point Clouds ◽  
Global Navigation Satellite Systems ◽  
Grade System ◽  
High Grade ◽  
Drainage Ditches ◽  
Quality Of Data ◽  
Natural Sediment ◽  
3D Point Clouds ◽  
The Cross

Abstract. Roadside ditches serve an important role for draining storm water. Over time vegetation growth, natural sediment deposits, and other debris can change grade of ditches. Effectively monitoring and identifying these changes to prioritize ditch maintenance is important from both a pavement preservation perspective and prevention of localized flooding. This study evaluates the performance of two mobile LiDAR systems for mapping the cross-section of roadside ditches in the presence of vegetation. The geometric quality of data collected by two different wheel-based LiDAR systems were investigated. The mapped ditches were reported and visualized in 2D images as well as 3D point clouds. The cross-sections of man-made drainage ditches were extracted and the quality of mapped ditches was assessed against Real-Time Kinematic Global Navigation Satellite Systems (RTK-GNSS) survey. The overall point cloud accuracy was 4 cm for the medium-grade system, and 1 cm for the high-grade system. The mapping accuracy is 2 cm (medium-grade system) and 1 cm (high-grade system) for solid surface. For rough mowed areas and areas with significant vegetation, the vertical accuracy was found to be 7 cm and 11 cm, respectively, for both wheel-based systems.

scholarly journals DIGITAL TERRAIN MODELS FROM MOBILE LASER SCANNING DATA IN MORAVIAN KARST

2016 ◽  
Vol XLI-B3 ◽  
pp. 387-394 ◽  
Author(s):  
N. Tyagur ◽  
M. Hollaus
Keyword(s):  
Czech Republic ◽  
Laser Scanning ◽  
Point Clouds ◽  
Low Noise ◽  
Data Sets ◽  
The Czech Republic ◽  
Digital Terrain ◽  
3D Point Clouds ◽  
Moravian Karst

During the last ten years, mobile laser scanning (MLS) systems have become a very popular and efficient technology for capturing reality in 3D. A 3D laser scanner mounted on the top of a moving vehicle (e.g. car) allows the high precision capturing of the environment in a fast way. Mostly this technology is used in cities for capturing roads and buildings facades to create 3D city models. In our work, we used an MLS system in Moravian Karst, which is a protected nature reserve in the Eastern Part of the Czech Republic, with a steep rocky terrain covered by forests. For the 3D data collection, the Riegl VMX 450, mounted on a car, was used with integrated IMU/GNSS equipment, which provides low noise, rich and very dense 3D point clouds. <br><br> The aim of this work is to create a digital terrain model (DTM) from several MLS data sets acquired in the neighbourhood of a road. The total length of two covered areas is 3.9 and 6.1 km respectively, with an average width of 100 m. For the DTM generation, a fully automatic, robust, hierarchic approach was applied. The derivation of the DTM is based on combinations of hierarchical interpolation and robust filtering for different resolution levels. For the generation of the final DTMs, different interpolation algorithms are applied to the classified terrain points. The used parameters were determined by explorative analysis. All MLS data sets were processed with one parameter set. As a result, a high precise DTM was derived with high spatial resolution of 0.25 x 0.25 m. The quality of the DTMs was checked by geodetic measurements and visual comparison with raw point clouds. The high quality of the derived DTM can be used for analysing terrain changes and morphological structures. Finally, the derived DTM was compared with the DTM of the Czech Republic (DMR 4G) with a resolution of 5 x 5 m, which was created from airborne laser scanning data. The vertical accuracy of the derived DTMs is around 0.10 m.

scholarly journals DIGITAL TERRAIN MODELS FROM MOBILE LASER SCANNING DATA IN MORAVIAN KARST

2016 ◽  
Vol XLI-B3 ◽  
pp. 387-394 ◽  
Author(s):  
N. Tyagur ◽  
M. Hollaus
Keyword(s):  
Czech Republic ◽  
Laser Scanning ◽  
Point Clouds ◽  
Low Noise ◽  
Data Sets ◽  
The Czech Republic ◽  
Digital Terrain ◽  
3D Point Clouds ◽  
Moravian Karst

During the last ten years, mobile laser scanning (MLS) systems have become a very popular and efficient technology for capturing reality in 3D. A 3D laser scanner mounted on the top of a moving vehicle (e.g. car) allows the high precision capturing of the environment in a fast way. Mostly this technology is used in cities for capturing roads and buildings facades to create 3D city models. In our work, we used an MLS system in Moravian Karst, which is a protected nature reserve in the Eastern Part of the Czech Republic, with a steep rocky terrain covered by forests. For the 3D data collection, the Riegl VMX 450, mounted on a car, was used with integrated IMU/GNSS equipment, which provides low noise, rich and very dense 3D point clouds. &lt;br&gt;&lt;br&gt; The aim of this work is to create a digital terrain model (DTM) from several MLS data sets acquired in the neighbourhood of a road. The total length of two covered areas is 3.9 and 6.1 km respectively, with an average width of 100 m. For the DTM generation, a fully automatic, robust, hierarchic approach was applied. The derivation of the DTM is based on combinations of hierarchical interpolation and robust filtering for different resolution levels. For the generation of the final DTMs, different interpolation algorithms are applied to the classified terrain points. The used parameters were determined by explorative analysis. All MLS data sets were processed with one parameter set. As a result, a high precise DTM was derived with high spatial resolution of 0.25 x 0.25 m. The quality of the DTMs was checked by geodetic measurements and visual comparison with raw point clouds. The high quality of the derived DTM can be used for analysing terrain changes and morphological structures. Finally, the derived DTM was compared with the DTM of the Czech Republic (DMR 4G) with a resolution of 5 x 5 m, which was created from airborne laser scanning data. The vertical accuracy of the derived DTMs is around 0.10 m.

The Research of Quantitative Analysis Methods on Product Form Information Based on the Cross-Section Diagram Set

2012 ◽  
Vol 229-231 ◽  
pp. 1675-1678
Author(s):  
Zhi Tang ◽  
Meng Ya Cai ◽  
Sheng Ze Wang ◽  
Bo Sun ◽  
Yue Ming Hao
Keyword(s):  
Cross Section ◽  
Morphological Characteristics ◽  
Product Form ◽  
Quality Of Data ◽  
The Cross ◽  
Change State ◽  
Machine Interaction ◽  
External Characteristics ◽  
Form Information

The external morphological characteristics of the handle grip impacts the man-machine interaction especially that of with fingers. Hence, the research on the external morphological of existed products has important significance on the improvement of man-machine interaction when designing a product. Most of the traditional ways of obtaining or describing product form information are established on a variety of views which do not consist the quality of data analysing dynamically or quantitatively. The aim of this article is exploring a new method based on the cross-section diagram set of the product. The method works in a more accurate way in obtaining the diagram information of product, meanwhile, it describes the change state of products' external characteristics by the simplex dimension of information. The method allows a dynamic and quantized way analysing the external characteristics of the product.

scholarly journals DERIVING 3D POINT CLOUDS FROM TERRESTRIAL PHOTOGRAPHS - COMPARISON OF DIFFERENT SENSORS AND SOFTWARE

2016 ◽  
Vol XLI-B5 ◽  
pp. 685-692 ◽  
Author(s):  
Robert Niederheiser ◽  
Martin Mokroš ◽  
Julia Lange ◽  
Helene Petschko ◽  
Günther Prasicek ◽  
...  
Keyword(s):  
Point Cloud ◽  
State Of The Art ◽  
User Interaction ◽  
Point Clouds ◽  
Rock Face ◽  
3D Point Clouds ◽  
Software Packages ◽  
User Friendly ◽  
Insight Into

Terrestrial photogrammetry nowadays offers a reasonably cheap, intuitive and effective approach to 3D-modelling. However, the important choice, which sensor and which software to use is not straight forward and needs consideration as the choice will have effects on the resulting 3D point cloud and its derivatives. <br><br> We compare five different sensors as well as four different state-of-the-art software packages for a single application, the modelling of a vegetated rock face. The five sensors represent different resolutions, sensor sizes and price segments of the cameras. The software packages used are: (1) Agisoft PhotoScan Pro (1.16), (2) Pix4D (2.0.89), (3) a combination of Visual SFM (V0.5.22) and SURE (1.2.0.286), and (4) MicMac (1.0). We took photos of a vegetated rock face from identical positions with all sensors. Then we compared the results of the different software packages regarding the ease of the workflow, visual appeal, similarity and quality of the point cloud. <br><br> While PhotoScan and Pix4D offer the user-friendliest workflows, they are also “black-box” programmes giving only little insight into their processing. Unsatisfying results may only be changed by modifying settings within a module. The combined workflow of Visual SFM, SURE and CloudCompare is just as simple but requires more user interaction. MicMac turned out to be the most challenging software as it is less user-friendly. However, MicMac offers the most possibilities to influence the processing workflow. The resulting point-clouds of PhotoScan and MicMac are the most appealing.

scholarly journals FOVEON VS BAYER: COMPARISON OF 3D RECONSTRUCTION PERFORMANCES

2019 ◽  
Vol XLII-2/W9 ◽  
pp. 755-761
Author(s):  
M. Vlachos ◽  
D. Skarlatos ◽  
P. Bodin
Keyword(s):  
Reference Point ◽  
Point Cloud ◽  
Main Idea ◽  
Point Clouds ◽  
Second Phase ◽  
Quality Of Information ◽  
Bayer Pattern ◽  
3D Point Clouds ◽  
Separate Point

<p><strong>Abstract.</strong> The main idea of this particular study was to validate if the new FOVEON technology implemented by sigma cameras can provide better overall results and outperform the traditional Bayer pattern sensor cameras regarding the radiometric information that records as well as the photogrammetric point cloud quality that can provide. Based on that, the scope of this paper is separated into two evaluations. First task is to evaluate the quality of information reconstructed during de-mosaicking step for Bayer pattern cameras by detecting potential additional colour distortion added during the de-mosaicking step, and second task is the geometric comparisons of point clouds generated by the photos by Bayer and FOVEON sensors against a reference point cloud. The first phase of the study is done using various de-mosaicking algorithms to process various artificial Bayern pattern images and then compare them with reference FOVEON images. The second phase of the study is carried on by reconstructing 3D point clouds of the same objects captured by a Bayer and a FOVEON sensor respectively and then comparing the various point clouds with a reference one, generated by a structured light hand-held scanner. The comparison is separated into two parts, where initially we evaluate five separate point clouds (RGB, Gray, Red, Green, Blue) for each camera sensor per site and then a second comparison is evaluated on colour classified RGB point cloud segments.</p>

scholarly journals COMPARISON OF ZEB1 AND LEICA C10 INDOOR LASER SCANNING POINT CLOUDS

2016 ◽  
Vol III-1 ◽  
pp. 143-149
Author(s):  
Beril Sirmacek ◽  
Yueqian Shen ◽  
Roderik Lindenbergh ◽  
Sisi Zlatanova ◽  
Abdoulaye Diakite
Keyword(s):  
Data Acquisition ◽  
Point Cloud ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Point Clouds ◽  
Quality Of Data ◽  
Local Point ◽  
Measurement Planning ◽  
Data Acquisition And Processing

We present a comparison of point cloud generation and quality of data acquired by Zebedee (Zeb1) and Leica C10 devices which are used in the same building interior. Both sensor devices come with different practical and technical advantages. As it could be expected, these advantages come with some drawbacks. Therefore, depending on the requirements of the project, it is important to have a vision about what to expect from different sensors. In this paper, we provide a detailed analysis of the point clouds of the same room interior acquired from Zeb1 and Leica C10 sensors. First, it is visually assessed how different features appear in both the Zeb1 and Leica C10 point clouds. Next, a quantitative analysis is given by comparing local point density, local noise level and stability of local normals. Finally, a simple 3D room plan is extracted from both the Zeb1 and the Leica C10 point clouds and the lengths of constructed line segments connecting corners of the room are compared. The results show that Zeb1 is far superior in ease of data acquisition. No heavy handling, hardly no measurement planning and no point cloud registration is required from the operator. The resulting point cloud has a quality in the order of centimeters, which is fine for generating a 3D interior model of a building. Our results also clearly show that fine details of for example ornaments are invisible in the Zeb1 data. If point clouds with a quality in the order of millimeters are required, still a high-end laser scanner like the Leica C10 is required, in combination with a more sophisticated, time-consuming and elaborative data acquisition and processing approach.

scholarly journals AN EMPRICAL POINT ERROR MODEL FOR TLS DERIVED POINT CLOUDS

2016 ◽  
Vol XLI-B5 ◽  
pp. 557-563 ◽  
Author(s):  
Mustafa Ozendi ◽  
Devrim Akca ◽  
Hüseyin Topan
Keyword(s):  
Real World ◽  
Incidence Angle ◽  
A Priori ◽  
Laser Scanner ◽  
Point Clouds ◽  
Error Model ◽  
Random Errors ◽  
Data Set ◽  
3D Point Clouds

The random error pattern of point clouds has significant effect on the quality of final 3D model. The magnitude and distribution of random errors should be modelled numerically. This work aims at developing such an anisotropic point error model, specifically for the terrestrial laser scanner (TLS) acquired 3D point clouds. A priori precisions of basic TLS observations, which are the range, horizontal angle and vertical angle, are determined by predefined and practical measurement configurations, performed at real-world test environments. A priori precision of horizontal (𝜎&lt;sub&gt;𝜃&lt;/sub&gt;) and vertical (𝜎&lt;sub&gt;𝛼&lt;/sub&gt;) angles are constant for each point of a data set, and can directly be determined through the repetitive scanning of the same environment. In our practical tests, precisions of the horizontal and vertical angles were found as 𝜎&lt;sub&gt;𝜃&lt;/sub&gt;=±36.6&lt;sup&gt;𝑐𝑐&lt;/sup&gt; and 𝜎&lt;sub&gt;𝛼&lt;/sub&gt;=±17.8&lt;sup&gt;𝑐𝑐&lt;/sup&gt;, respectively. On the other hand, a priori precision of the range observation (𝜎&lt;sub&gt;𝜌&lt;/sub&gt;) is assumed to be a function of range, incidence angle of the incoming laser ray, and reflectivity of object surface. Hence, it is a variable, and computed for each point individually by employing an empirically developed formula varying as 𝜎&lt;sub&gt;𝜌&lt;/sub&gt;=±2−12 𝑚𝑚 for a FARO Focus X330 laser scanner. This procedure was followed by the computation of error ellipsoids of each point using the law of variance-covariance propagation. The direction and size of the error ellipsoids were computed by the principal components transformation. The usability and feasibility of the model was investigated in real world scenarios. These investigations validated the suitability and practicality of the proposed method.

scholarly journals PLANAR CONSTRAINTS FOR AN IMPROVED UAV-IMAGE-BASED DENSE POINT CLOUD GENERATION

2015 ◽  
Vol XL-1/W4 ◽  
pp. 269-274 ◽  
Author(s):  
F. He ◽  
A. Habib ◽  
A. Al-Rawabdeh
Keyword(s):  
Point Cloud ◽  
Experimental Tests ◽  
Point Clouds ◽  
Geometric Information ◽  
Planar Surfaces ◽  
3D Point Clouds ◽  
Dense Image ◽  
Dense Point ◽  
Uav Image

In this paper, we proposed a new refinement procedure for the semi-global dense image matching. In order to remove outliers and improve the disparity image derived from the semi-global algorithm, both the local smoothness constraint and point cloud segments are utilized. Compared with current refinement technique, which usually assumes the correspondences between planar surfaces and 2D image segments, our proposed approach can effectively deal with object with both planar and curved surfaces. Meanwhile, since 3D point clouds contain more precise geometric information regarding to the reconstructed objects, the planar surfaces identified in our approach can be more accurate. In order to illustrate the feasibility of our approach, several experimental tests are conducted on both Middlebury test and real UAV-image datasets. The results demonstrate that our approach has a good performance on improving the quality of the derived dense image-based point cloud.

scholarly journals COMPARISON OF ZEB1 AND LEICA C10 INDOOR LASER SCANNING POINT CLOUDS

2016 ◽  
Vol III-1 ◽  
pp. 143-149 ◽  
Author(s):  
Beril Sirmacek ◽  
Yueqian Shen ◽  
Roderik Lindenbergh ◽  
Sisi Zlatanova ◽  
Abdoulaye Diakite
Keyword(s):  
Data Acquisition ◽  
Point Cloud ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Point Clouds ◽  
Quality Of Data ◽  
Local Point ◽  
Measurement Planning ◽  
Data Acquisition And Processing

We present a comparison of point cloud generation and quality of data acquired by Zebedee (Zeb1) and Leica C10 devices which are used in the same building interior. Both sensor devices come with different practical and technical advantages. As it could be expected, these advantages come with some drawbacks. Therefore, depending on the requirements of the project, it is important to have a vision about what to expect from different sensors. In this paper, we provide a detailed analysis of the point clouds of the same room interior acquired from Zeb1 and Leica C10 sensors. First, it is visually assessed how different features appear in both the Zeb1 and Leica C10 point clouds. Next, a quantitative analysis is given by comparing local point density, local noise level and stability of local normals. Finally, a simple 3D room plan is extracted from both the Zeb1 and the Leica C10 point clouds and the lengths of constructed line segments connecting corners of the room are compared. The results show that Zeb1 is far superior in ease of data acquisition. No heavy handling, hardly no measurement planning and no point cloud registration is required from the operator. The resulting point cloud has a quality in the order of centimeters, which is fine for generating a 3D interior model of a building. Our results also clearly show that fine details of for example ornaments are invisible in the Zeb1 data. If point clouds with a quality in the order of millimeters are required, still a high-end laser scanner like the Leica C10 is required, in combination with a more sophisticated, time-consuming and elaborative data acquisition and processing approach.

scholarly journals Evaluating the Quality of TLS Point Cloud Colorization

2020 ◽  
Vol 12 (17) ◽  
pp. 2748
Author(s):  
Arttu Julin ◽  
Matti Kurkela ◽  
Toni Rantanen ◽  
Juho-Pekka Virtanen ◽  
Mikko Maksimainen ◽  
...  
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Production Efficiency ◽  
Point Clouds ◽  
Measuring Instruments ◽  
Efficient Production ◽  
White Balance ◽  
3D Point Clouds ◽  
Imaging Sensors

Terrestrial laser scanning (TLS) enables the efficient production of high-density colored 3D point clouds of real-world environments. An increasing number of applications from visual and automated interpretation to photorealistic 3D visualizations and experiences rely on accurate and reliable color information. However, insufficient attention has been put into evaluating the colorization quality of the 3D point clouds produced applying TLS. We have developed a method for the evaluation of the point cloud colorization quality of TLS systems with integrated imaging sensors. Our method assesses the capability of several tested systems to reproduce colors and details of a scene by measuring objective image quality metrics from 2D images that were rendered from 3D scanned test charts. The results suggest that the detected problems related to color reproduction (i.e., measured differences in color, white balance, and exposure) could be mitigated in data processing while the issues related to detail reproduction (i.e., measured sharpness and noise) are less in the control of a scanner user. Despite being commendable 3D measuring instruments, improving the colorization tools and workflows, and automated image processing pipelines would potentially increase not only the quality and production efficiency but also the applicability of colored 3D point clouds.

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