3D city models are frequently used to acquire and store energy-related information of buildings to be used in energy applications, such as solar potential analyses and energy demand calculations. In this context, the most common data model is CityGML, which provides an application domain extension called the Energy ADE to store energy-related data in a systematic manner in XML format. On the other hand, CityJSON has been developed as a JSON-based encoding to exchange 3D city models, with the aim of eliminating the hierarchical structure and shortcomings of the XML-based CityGML. However, even though an extension mechanism exists in CityJSON, an energy-related CityJSON extension is not present in the current literature. Therefore, the aim of this thesis is to develop and test a CityJSON Energy Extension. To achieve this, the space heating demand calculation of buildings is chosen as the use case to validate and test the Extension.
In this thesis, a simplified version of the Energy ADE, called the Energy ADE KIT profile, is used as the first step to create a semi-direct translation to a CityJSON Energy Extension. After validating the Extension with the official validator of CityJSON, the space heating demand is calculated for a subset of the Rijssen-Holten in the Netherlands according to the Dutch standard NTA 8800. Required input data is collected from various data sources and stored in the CityJSON Energy Extension to test its usability for the use case. The Extension is then improved depending on the results of the tests based on the use case. The results show that the semi-direct translation lacked numerous objects and attributes to store certain input data, while the final version of the Extension fully supports the use case. Furthermore, while the semi-direct translation contained deep hierarchical structures, these were eliminated in the final Extension to comply with the design decisions behind CityJSON. The main differences between the Energy ADE and the CityJSON Energy Extension reflected this philosophy as well, where the former was built with a deep hierarchical structure, while the latter flattens this hierarchy by using the characteristics of JSON. In addition, a comparison in file sizes showed that the input 3D city model of the study area in CityJSON format had a file size of 40.6 MB, whereas the output CityJSON + Energy Extension file with all input and output data was 65.8 MB. It was discussed that this increase of 25.2 MB in file size is not significant, considering the high increase in the number of objects stored in the file. On the other hand, space heating demand calculation resulted in negative values for 32 buildings in the study area, which was not expected. While the possible reasons were detected, a solution could not be developed in the given time frame of the thesis. Overall, this thesis showed that the CityJSON Energy Extension can provide an easy-to-use alternative to CityGML Energy ADE, where the Extension files can be simply parsed by software and easily understood by the user without reaching large file sizes.

Most construction work requires building permit checks. Therefore, to promote sustainable and high-quality urban development, it is necessary to improve the building permit application process and accelerate the digital process of building permit checks.

Many studies about the digitalization of building permitting use the BIM, mainly coded in its reference open standard IFC by buildingSMART, to check compliance. However, many regulations need to consider some building context that is not supported by the current buildingSMART. This will affect the permit checks of these building contexts. The use of 3D city models for building permit checks is an alternative to BIM. 3D city models are powerful tools for city-level analysis and they can do extensions on different City Objects which able to cover the building context in the regulation, therefore it has good applicability to problems related to urban planning.

At present, there are little researches on building permit inspection based on 3D city models, so this study aims to provide an approach to use 3D city models and its extensions to support digital building permit checks. CityJSON has advantages over the CityGML data format in the development process, so it was selected as the 3D city model used in this study.

The first step is to choose the regulations for building permit checks. This involves the interpretation of the regulations, formalization process. In this study, the use case research method was selected, and the parking standards for cars and bicycles in Rotterdam were selected as the research object. We built a logic-based mechanism to map the content of the law to the corresponding 3D model. Next, we built the CityJSON conceptual model, which included four types of urban objects and expanded them. Then, the data we obtained and the data model will be stored and extended in a CityJSON model and then used for calculation and analysis in the developed tool.

Finally, through the tools developed, we successfully carried out a parking legal building permit inspection on the new building test data and stored and visualized the results. By using the framework and tool developed in this research, we can replicated the process to different places and regulations.

Q\&A fora have developed into a precious tool for online knowledge exchange. Being community-driven, openly accessible and free, getting an answer to a complicated question can nowadays be a matter of minutes. This research investigates the specific case of gis.stackexchange, a technical Q&A forum used by Geographic Information Systems professionals. A central topic is the interaction between users. Based on existing research, an automated approach is elaborated and a big data analysis is performed. Also, a link between the outcomes and self-reflective behaviour found on the community meta forum is established. Factors positively influencing interaction as defined by the approach are identified (implication of the author(s), presence of images and code snippets). Furthermore, weaknesses such as the low share of interactions associated to an alteration (of the original post) are also discussed. These outcomes eventually lead to a series of recommendations for the forum itself and related formats.

Unlike outdoor environments, there is no wide-spread solution to positioning inside a building. Indoorsolutions rely on pre-installation of infrastructure, such as Bluetooth beacons or ultra-wide bandtechnology. Recently, there has been growing interest in the use of Augmented Reality (AR) for indoorpositioning. AR devices use an algorithm known as Simultaneously Localisation and Mapping (SLAM)to scan an environment and find a position inside. This make it possible to estimate a position on-theflywithout any pre-installations. The Microsoft Hololens (MH) is a head-mounted display AR devicethat is able to perform SLAM. The use of SLAM for indoor positioning can be beneficial in the case ofEmergency Response (ER). The place of impact in ER is unknown and there is no time to install anyinfrastructure beforehand.Two problems arise with the use of SLAM for indoor positioning. (1) A position is a pin point in spacethat is defined by a reference frame. In the case of SLAM, the frame is the scanned object. In mostsituations, a map or floor plan is more appropriate as reference frame, in order to give a full context.(2) The SLAM algorithm suffers from drift, a growing error over time. This research tries to solve theseproblems using shape registration. The SLAM output can be aligned to a reference floor plan, by use ofa spatial matching technique. This alignment is a continuous process to account for the drift errors ofthe SLAM algorithm.Three spatial matching techniques are compared: Iterative Closest Points (ICP) iteratively tries to minimizethe distance between two shapes using least squares; Instantaneous Kinematics (IK) is a varianton ICP that makes use of a velocity vector; and Hough Transform makes use of the Hough domainproperties, where rotation is invariant to translation and scale. These algorithms are compared on theiraccuracy, computation time and robustness.It is concluded that the Hough Transform algorithm gives the most accurate results and is fastest. In thisresearch it was found that an average accuracy of < 1m can be maintained over 80% of the experiments,with maximum errors up to 5 meter. In 20% of the experiments, the error can extremely diverge upto >100 meter. It is suggested that the quality of the scan and the existence of artefacts (e.g.furniture,people) are the cause of these errors. That makes the method unsuitable for indoor positioning in thecase of Emergency Response, that needs extremely reliable systems. Research is needed to create a morerobust method, that uses better outlier detection methods. However, the results are promising and doopen the door for indoor navigation using Augmented Reality.

This study presents a methodology to convert from the most dominant 3D city model standard in 3D GIS to BIM. Namely, CityGML to IFC. IFC is chosen because it is the common open standard to exchange data in the BIM world. For the aim of this study, the two standards are divided into 5 comparable sub-parts; Semantics, Geometry, Geographical coordinates, Topology, and Encoding. The characteristics of each of these sub-parts are studied and a theoretical conversion method is proposed for it from the first standard to the other. This is done by performing a semantic and geometrical mapping between the two standards, converting the georeferencing from Global to local, converting the encoding that the two standards use from XML to STEP, deciding which topological relations are to be retained, and providing a basic implementation that is created using Python to combine the above tasks. The work presented in this thesis can provide a foundation for future work in converting CityGML to IFC. It provides an insight into the relationship between the two standards and a methodology for the conversion from one to the other, and the process of developing software to perform such conversion. This is done in a way that can be extended for future specific needs.