Mila Koeva, Monika Kuffer, Claudio Persello
3D modelling
RS, GIS data for the city, will be provided for the city of Sofia if this will be the case study location. For the case study in the Netherlands data will be provided from the Dutch Kadaster and internship is possible. Joined supervision with additional experts is planned.
Digital twin (smart city/3D modelling) topic currently attracts the attention and interest of many cities, authorities, industrial and research organizations at national, European and international level. By adopting Big Data and IoT technologies, the city stakeholders are support in making evidenced based planning and decision making by implementing data-driven processes using shared data instead of being restricted by access to data. Commonly, data is spread across different organizations without common semantics and a solid technology base, which restricts access to important data The interoperability of data is missing, and it is a target goal of use case scenarios that depend on linking and analysis of heterogeneous data. Therefore, the integration of different data in a common platform is of primary interest. Unfortunately, the current approaches and tools for digital twins/smart cities, are not fit to be used at municipal level, as well as tools are not well equipped to perform continuous monitoring of city processes, to collect city data and guide decision making. In order to support city monitoring and analysis suitable for different domains (land monitoring, urban planning, sustainable development or economic analysis), to identify problem issues before they arise, to find new opportunities, and to decide through experimentation, a physical city needs to be paired to a virtual one through digital twinning.
The concept of the digital twin is not new, but now it has a different view. It combines Artificial Intelligence, Big Data and Remote Sensing potential to find new opportunities and to interact with virtual models to simulate “what-if” scenarios. Such scenarios can be useful in predictions or post effect data analysis on a city level (e.g., Covid -19 post effect of property market, urban heat island - UHI, Solar potential, etc.)
This research will focus on applying innovative methods (in some cases machine learning), integration of different 3D data for creation and applications of Digital Twins/3D city models. There are several possible directions:
1. Automation in LOD2 building generation based on RS data using deep learning (possible case study area can be The Netherlands or Sofia - Bulgaria).
2. Digital twins/3D city modelling in support of effective urban planning (solar potential analysis, UHI, etc.). (possible case study area can be Sofia - Bulgaria).
3. Analyzing the impact of COVID-19 on property prices, taking into account the 3rd dimension. (case study can be in The Netherlands with possibility of internship in the Dutch Kadaster)
https://www.youtube.com/watch?v=Nl4d-fatEq0&feature=youtu.be