scholarly journals Radiometric Correction of Terrestrial LiDAR Point Cloud Data for Individual Maize Plant Detection

2014 ◽  
Vol 11 (1) ◽  
pp. 94-98 ◽  
Author(s):  
Bernhard Hofle
Keyword(s):  
Point Cloud ◽  
Maize Plant ◽  
Point Cloud Data ◽  
Radiometric Correction ◽  
Terrestrial Lidar ◽  
Cloud Data

scholarly journals THE RESEARCH ON ACCURACY EVALUATION METHOD OF THE TOMOGRAPHIC SAR THREE-DIMENSIONAL RECONSTRUCTION OF URBAN BUILDING BASED ON TERRESTRIAL LIDAR POINT CLOUD

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 617-621
Author(s):  
L. Li ◽  
L. Pang ◽  
X. D. Zhang ◽  
H. Liu
Keyword(s):  
Point Cloud ◽  
Evaluation Method ◽  
Three Dimensional ◽  
Accuracy Evaluation ◽  
3D Point Cloud ◽  
Point Cloud Data ◽  
Terrestrial Lidar ◽  
Cloud Data ◽  
Dimensional Precision ◽  
Urban Buildings

Muti-baseLine SAR tomography can be used on 3D reconstruction of urban building based on SAR images acquired. In the near future, it is expected to become an important technical tool for urban multi-dimensional precision monitoring. For the moment，There is no effective method to verify the accuracy of tomographic SAR 3D point cloud of urban buildings. In this paper, a new method based on terrestrial Lidar 3D point cloud data to verify the accuracy of the tomographic SAR 3D point cloud data is proposed, 3D point cloud of two can be segmented into different facadeds. Then facet boundary extraction is carried out one by one, to evaluate the accuracy of tomographic SAR 3D point cloud of urban buildings. The experience select data of Pangu Plaza to analyze and compare, the result of experience show that the proposed method that evaluating the accuracy of tomographic SAR 3D point clou of urban building based on lidar 3D point cloud is validity and applicability

scholarly journals APPLICATION OF THE STEEP SLOPE RISK ASSESSMENT USING THREE DIMENSIONAL INFORMATION DATA

2019 ◽  
Vol XLII-3/W8 ◽  
pp. 381-386
Author(s):  
D. Y. Shin ◽  
J. S. Sim ◽  
K. S. Lee
Keyword(s):  
Risk Assessment ◽  
Inclination Angle ◽  
Point Cloud ◽  
Spatial Information ◽  
Three Dimensional ◽  
Steep Slope ◽  
Point Cloud Data ◽  
Registration Accuracy ◽  
Terrestrial Lidar ◽  
Cloud Data

<p><strong>Abstract.</strong> A collapse of slope is one of the natural disasters that often occur during the early spring and the rainy season. In order to prevent this kind of disaster, safety monitoring is carried out through risk assessment. This assessment consists of various parameters such as inclination angle and height of the slope, and inspectors evaluate the score using the compass, the laser range finder, and so on. This approach is, however, consumed a lot of the manpower and the time. This study, therefore, aims to evaluate the rapid and accurate steep slope risk by using a terrestrial LiDAR which takes 3 dimensional spatial information data. 3D spatial information data was acquired using the terrestrial LiDAR for steep slopes classified as very unstable slopes. Noise and vegetation of the acquired scan data were removed to generate point cloud data with a rock or mountain model without vegetation. The RMSE of the registration accuracy was 0.0156 m. From the point cloud data, the inclination angle, height, shape, valley, collapse and loss were evaluated. As a result, various risk assessment parameters can be checked at once. In addition, it is expected to be used as basic data for constructing steep slope DB, providing visualization data, and time series analysis in the future.</p>

scholarly journals Reconstruction of Single Tree with Leaves Based on Terrestrial LiDAR Point Cloud Data

2018 ◽  
Vol 10 (5) ◽  
pp. 686 ◽  
Author(s):  
Donghui Xie ◽  
Xiangyu Wang ◽  
Jianbo Qi ◽  
Yiming Chen ◽  
Xihan Mu ◽  
...  
Keyword(s):  
Point Cloud ◽  
Point Cloud Data ◽  
Terrestrial Lidar ◽  
Cloud Data ◽  
Single Tree

scholarly journals Integration of Constructive Solid Geometry and Boundary Representation (CSG-BRep) for 3D Modeling of Underground Cable Wells from Point Clouds

2020 ◽  
Vol 12 (9) ◽  
pp. 1452
Author(s):  
Ming Huang ◽  
Xueyu Wu ◽  
Xianglei Liu ◽  
Tianhang Meng ◽  
Peiyuan Zhu
Keyword(s):  
Point Cloud ◽  
Three Dimensional ◽  
Point Clouds ◽  
Adaptive Method ◽  
Boundary Representation ◽  
Point Cloud Data ◽  
Terrestrial Lidar ◽  
Cloud Data ◽  
Underground Cable ◽  
3D Information

The preference of three-dimensional representation of underground cable wells from two-dimensional symbols is a developing trend, and three-dimensional (3D) point cloud data is widely used due to its high precision. In this study, we utilize the characteristics of 3D terrestrial lidar point cloud data to build a CSG-BRep 3D model of underground cable wells, whose spatial topological relationship is fully considered. In order to simplify the modeling process, first, point cloud simplification is performed; then, the point cloud main axis is extracted by OBB bounding box, and lastly the point cloud orientation correction is realized by quaternion rotation. Furthermore, employing the adaptive method, the top point cloud is extracted, and it is projected for boundary extraction. Thereupon, utilizing the boundary information, we design the 3D cable well model. Finally, the cable well component model is generated by scanning the original point cloud. The experiments demonstrate that, along with the algorithm being fast, the proposed model is effective at displaying the 3D information of the actual cable wells and meets the current production demands.

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