Building 3D City models: Testing and Comparing Laser scanning and low-cost UAV data using FOSS technologies

Autor: Rebelo, Carla Roque, Manuel Rodrigues, A., Tenedório, J. António, Gonçalves, J. Alberto, Marnoto, J.
Rok vydání: 2014
Předmět:
Zdroj: VIII Jornadas de SIG Libre
DUGiDocs – Universitat de Girona
instname
Popis: Presentació sobre eines de programari lliure per a la gestió automàtica dels volums dels edificis Presently, the use of new technologies for the acquisition of 3D geographical data on time is very important for urban planning. Applications include evaluation and monitoring of urban parameters (ie. volumetric data),indicators of an urban plan, or monitoring built-up areas and illegal buildings. This type of 3D data can be acquired through an Airborne Laser Scanning system, also known as LiDAR (Light Detection And Ranging) or by Unnamed Aerial Vehicles (UAV). The aim of this paper is to use and compare these two technologies for extracting building parameters (façade height and volume). Existing literature evaluates each technology separately. This work pioneers benchmarking between LiDAR and UAV point-clouds. The basic function of LiDAR is collecting a georeferenced and dense 3D point cloud from a laser scanner during flight. Therefore it is possible to obtain a similar 3D point cloud using processing algorithms for stereo aerial images, obtained by large or small-format digital cameras (the small-format camera implemented in Unmanned Aerial Vehicles). The choosen study area is located in Praia de Faro, an open sandy beach in Algarve (Southern Portugal), limited west by the Ria Formosa barrier island system. The area defined has an extension of 300×100m. The methodology is divided in two distinct stages: (1) parameters extraction, (2) comparative technology analysis. Lidar point- cloud resolution is approximately 6 pts/m2 and UAV point-cloud 60 pts/m2. FOSS technologies have proven to be the most adequate adequate platform for the development and diffusion of advanced analytical tools in the Geographical Information Sciences (GISci). Data management in this paper is supported by a Geographical Database Management System (GDBMS), implemented using PostgreSQL and PostGIS. Statistical analysis is performed using R whilst advanced spatial functions are used in GRASS
Databáze: OpenAIRE
Externí odkaz: