Main issues must be clearly stated

The digital twin project of the City Council of Las Palmas de Gran Canaria, which was awarded last September, aims to improve planning and decision making through tourism and mobility data.


Las Palmas de Gran Canaria, Spain

Main facts/points outlined in body of text

  • The digital twin of Las Palmas de Gran Canaria will provide a digital representation of the city with a highly detailed and accurate three-dimensional model covering essential elements of the urban structure, such as public spaces, roads, buildings and surrounding natural features. It will be integrated with smart beach and big data mobility platforms.
  • This is a project promoted by the departments of Tourism, Modernization and Mobility through the Sociedad Municipal de Aparcamientos de Las Palmas de Gran Canaria (Sagulpa), which has been awarded to Esri Spain with a two-month execution period and a cost of 94,995 euros. The project is subsidized by the MAC Interreg Program.
  • The digital twin of Las Palmas de Gran Canaria will make it possible to consult information in real time and make future simulations based on historical data. Among its main functions, it will accelerate innovation by allowing simulation and experimentation in a virtual environment.
  • It will foster collaboration between the administration and private companies and local communities by providing a common and understandable platform.
  • It will helpreduce time and costs in the urban planning process by identifying problems and solutions early and shortening project timelines through more efficient communication between stakeholders.
  • Having a virtual replica of the city will contribute to improving the lives of residents and the experience of tourists through early decision making, as well as immersive destination awareness.
  • It will also enable the city council to plan more effectively in areas such as traffic and public transport. For example, it will facilitate speed analysis on various road segments to determine bottlenecks and reduce congestion, and provide actual driving speeds and travel speeds for use in transportation models.
  • It will also be possible to identify and prioritize congestion points, detect the impact of seasonality, events or incidents on traffic density, evaluate the most used exits and intersections, and analyze detours used by drivers to avoid conflict areas. In the future, other analyses and projections on municipal matters such as urban planning, roads and works or parks and gardens will be possible.