| Title | Open Data Integration in 3D CityGML-based Models Generation |
|---|---|
| ID_Doc | 79097 |
| Authors | Maieron, MA; de Oliveira, JPM |
| Title | Open Data Integration in 3D CityGML-based Models Generation |
| Year | 2021 |
| Published | |
| Abstract | Facing the increasing complexity of large urban centers caused by population growth and the dynamic nature of cities, their managers seek to optimize services and infrastructures in terms of scalability, environment, and security to adapt to demand, making their cities smarter. Therefore, these new modern centers' administrators should apply smart governance techniques to manage the physical and data infrastructure and seek alignment with the global open data initiative. As a point of intersection between physical and data infrastructure, 3D models of cities have been playing an important role in people's daily lives, being a fundamental element for several applications. In this context, CityGML, a semantic model for 3D data representation adopted by several cities, appears as a possible solution for modeling. This paper presents an approach of integrating open data in the semi-automatic generation of 3D models based on CityGML, "enriching" semantic information about the instances with the association with the OpenStreetMaps database. A case study was performed using data provided by the Municipality of Porto Alegre, BR. The model generated in CityGML goes through semantic, geometric, and schema level validations, proving the proposed approach's feasibility. |
| https://doi.org/10.5220/0010383201670174 |
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