Redirigiendo al acceso original de articulo en 24 segundos...
Inicio  /  Infrastructures  /  Vol: 2 Núm: 1 Par: 0 (2017)  /  Artículo
ARTÍCULO
TITULO

Comparative Analysis of Triangulation Libraries for Modeling Large Point Clouds from Land and Their Infrastructures

Luis Lopez-Fernandez    
Pablo Rodriguez-Gonzalvez    
David Hernandez-Lopez    
Damian Ortega-Terol    
Diego Gonzalez-Aguilera    

Resumen

Although the generation of large points clouds from geomatic techniques allows us to realize the topography and appearance of the terrain and its infrastructures (e.g., roads, bridges, buildings, etc.), all these 3D point clouds require an unavoidable step to be conveniently treated: the definition of the surface that connects these points in space through digital surface models (DSM). In addition, these point clouds sometimes have associated attributes and geometric constraints such as breaklines and/or exclusion areas, which require the implementation of efficient triangulation techniques that can cope with a high volume of information. This article aims to make a comparative analysis of different Delaunay triangulation libraries, open or with academic versions available for the scientific community, so that we can assess their suitability for the modeling of the territory and its infrastructures. The comparison was carried out from a two-fold perspective: (i) to analyze and compare the computational cost of the triangulation; (ii) to assess the geometric quality of the resulting meshes. The different techniques and libraries have been tested based on three different study cases and the corresponding large points clouds generated. The study has been useful to identify the limitations of the existing large point clouds triangulation libraries and to propose statistical variables that assess the geometric quality of the resulting DSM.

 Artículos similares

       
 
George Westergaard, Utku Erden, Omar Abdallah Mateo, Sullaiman Musah Lampo, Tahir Cetin Akinci and Oguzhan Topsakal    
Automated Machine Learning (AutoML) tools are revolutionizing the field of machine learning by significantly reducing the need for deep computer science expertise. Designed to make ML more accessible, they enable users to build high-performing models wit... ver más
Revista: Information

 
Hamed Taherdoost and Mitra Madanchian    
Blockchain technology has become a powerful disruptive force that upends established ideas in several industries. A fascinating point of convergence is that of blockchain technology and Business Process Management (BPM), where the distributed and immutab... ver más
Revista: Information

 
Riguga Su, Chaobin Yang, Zhibo Xu, Tingwen Luo, Lilong Yang, Lifeng Liu and Chao Wang    
Urban landscape has important effects on urban climate, and the local climate zone (LCZ) framework has been widely applied in related studies. However, few studies have compared the relative contributions of LCZ on the urban thermal environment across di... ver más

 
Marcin Klosok, Daria Gendosz de Carrillo, Piotr Laszczyca, Tomasz Plociniczak, Halina Jedrzejowska-Szypulka and Tomasz Sawczyn    
Revista: Applied Sciences

 
Siarhei Autsou, Karolina Kudelina, Toomas Vaimann, Anton Rassõlkin and Ants Kallaste    
Servomotors have found widespread application in many areas, such as manufacturing, robotics, automation, and others. Thus, the control of servomotors is divided into various principles and methods, leading to a high diversity of control systems. This ar... ver más
Revista: Applied Sciences