Conference Agenda

The 3DCityDB-Tools plug-in for QGIS enables users to connect to the open-source 3D City Database (3DCityDB) 4.x, load CityGML 1.0 and 2.0 data, and structure it as GIS layers within QGIS. The plug-in simplifies interaction with the complex structure of the 3DCityDB 4.x by providing a GUI-based tool and a server-side package for seamless data retrieval and management from QGIS. With the release of the CityGML 3.0 conceptual data model in 2021, the 3D City Database has been updated to version 5.0, introducing several changes to support the new characteristics of CityGML 3.0 and a significant redesign and restructuring of the database schema. However, the current 3DCityDB-Tools plug-in for QGIS does not support the latest CityGML and 3DCityDB versions. This paper presents the findings and experiences gathered to modify the plug-in’s server-side architecture to cope with the new 3DCityDB 5.0. Similar to what already happens with the current plug-in version, the proposed new approach enables the generation of GIS layers following the Simple-Feature-for-SQL model, optimising query performance and improving attribute management. The resulting vector-based layers can be seamlessly imported into QGIS, allowing for interaction between QGIS and the underlying CityGML data stored in the latest version of the 3DCityDB.

Modern geo-data management plays a crucial role in designing digital twins in distributed system environments, enabling seamless integration, analysis, and visualization of spatial information. With the rise of graph databases and linked data, geospatial relationships can be efficiently modeled and queried using technologies such as Gremlin, a graph traversal language. On the other hand, Simple Features (see ISO19107) and the Dimensionally Extended 9-Intersection Model (DE-9IM) as two traditional examples provide standardized frameworks for spatial representation and topological reasoning, ensuring interoperability across systems. The fusion of geospatial standards with schema-free geo-data management advances the support of real-time decision-making and scalable geospatial applications, making modern geo-data management a cornerstone of intelligent, interconnected digital environments. This paper provides one step towards this goal by using an abstract graph-schema to represent the intra- and inter-relations of simplicial- and polytope-complexes and applying the traditional geoinformatics interpretation of topology, the philosophy of the Dimensionally Extended 9-Intersection Model (DE-9IM). This approach can be seen as a step towards the implentation of a domain-specific query language for property graphs that represent complex interrelated vector data.

Extreme weather events such as heavy rains are an increasing challenge. The potential impact of flooding on residential buildings can be simulated using digital twins. However, when using geometric-semantic information from diverse data resources, such as 3D city models, zoning or cadastre, the data must be carefully selected and programmatically prepared for the simulation. In this study, we present how a use-case driven classification was generated for the residential buildings in the city of Dresden, which is used to estimate the damage potential. The research focuses on both the supervised building classification with a neural network and the open source software framework. Data management is done with the 3DCityDB in PostgreSQL. QGIS is used for visualisation and user interaction. The Python-plugin automatically classifies more than 70,000 residential buildings based on 37 residential building classes. The hierarchical classification is challenging due to the ground truth sample size of about 21,000 and the heterogeneous distribution of the samples. The core of the method is the training and validation utilising random forest as machine learning method. With the developed toolset, classification results can be visually checked in a subsequent step using QGIS. Additionally, the classification, might be corrected manually for individual buildings using mobile mapping data, if necessary. Eventually, the assigned classes are fed back into the official CityGML city model as a new attribute, enabling a realistic damage potential analysis, in a free and publicly available 3D-WebGIS platform. The project is funded under the Smart Cities pilot programme of Germany.