Web mapping is essential in many fields, including navigation, real estate, and tourism. With advances in mapping technology, 3D web mapping has been introduced by multiple geospatial platforms. Compared to 2D web mapping, 3D web mapping provides more details, better visual effects, and is crucial for applications like digital twins. In navigation, terrain is a fundamental element in 3D mapping. However, the vast amount of data from 3D models requires the use of multiple Levels of Detail (LoDs) to reduce data consumption and request time on the client side. Without further processing, different LoD models will have gaps at their boundaries. Such gaps can cause visual inconsistency and artifacts. Locking boundaries is a commonly used method to solve the gaps in different LoDs problems, that is to maintain the vertices on the boundaries during simplification. While this the method causes inefficiency in simplification. Nanite (Nan) proposed a method using triangle clustering to address issues with Level-of-detail (LoD) model gaps, inefficiencies in cluster simplifications, and visual inconsistencies caused by locked boundaries. This method can be applied to large-scale models, such as terrain data. However, this method was only applied to local data use cases and not to web mapping. Therefore, this thesis investigates adapting the triangle clustering method for web mapping. Considering the fact that the Nanite triangle clustering method performs well on multi-LoD models (Nan), we believe this method could also be migrated to the area of large-scale terrain. We proposed a method to construct multi-level LoD terrain for navigation based on Nanite method. In our approach, large-scale terrain data is distributed using web tiles for navigation purposes.
Keywords— WebGIS; Web mapping; 3D map; Multi-LoD

Road network models are essential for modern urban planning, transportation analysis, and digital map reconstruction. This thesis addresses the development of a comprehensive digital road network model that advances from linear representation to a lane-level and areal polygonal representation, based on OpenStreetMap (OSM) data. While OSM provides rich road network data, challenges remain in reconstructing high-resolution, lane-level networks that are both geometrically precise and topologically consistent.

The objective of this research is to create a reffned digital road model that enhances the geometric accuracy and topological integrity of road networks by transitioning from road-level centerlines to lane-level polygons and full areal representations. This model is designed to capture essential aspects and semantic information such as traffic modes (motorized and cycling), intersection complexity, and road connectivity.

To achieve these objectives, the lane network generation methodology integrates OSM data with graph theory and civil engineering principles, focusing on lane topology and connectivity. The approach enhances linear geometry into areal geometry by combining a buffer-based method for road ribbons with a node-based method for intersection geometry. This process generates multiple intermediate results, including a road-level data model, a traffic-level data model, and grouped strokes representing global and local adjacency as graph-like models. Additionally, lane-level networks, lane geometry, and areal representations of roads and intersections are developed. Key innovations include a generalized method for lane centerline and polygon generation, ensuring road-lane correspondence and consistency between low-LoD linear models and high-LoD areal models.

The final product is a digital road network model that accommodates variations in road shapes, realistic intersection geometry, and detailed trafffc lane information, enabling highly detailed urban simulations and transportation analyses. While challenges remain regarding lane alignment, complex intersections, and the lack of detailed trafffc signal data, this research successfully bridges the gap between OSM’s raw linear road centerline data and the lane-level areal representations.

Modern navigation heavily relies on Global Navigation Satellite Systems (GNSS) and digitized road network databases, but faces limitations in GNSS-denied areas and complex 2D road netowrks. This project addresses these challenges by developing a methodology to create and store a comprehensive 3D road and terrain dataset for enhanced navigation. In collaboration with TomTom, a company that aims to fulfill software requirements, making significant advancements in geolocation technology and societal contributions. The main research question of the project is: ”How can we create a 3D map of roads using information about the center of the road and elevation data?”. The approach to answer this question involves extracting 2D road polygons from centerline data based on width of the roads, the direction and the amount of lanes of them. These 2D polygons undergo enrichment with elevation data, with techniques like filtering, segmentation, and primitive extraction ensuring alignment with the digital terrain model. The methodology encompasses data acquistion, creation of polygons using the centerlines dataset, 2D-to-3D polygon conversion, elevation integration and data storage in CityJSON format.

In recent decades, it is well known that transportation systems have a crucial role in the economic development and social prosperity of modern societies. While road width can be considered as one of the most important factors of the road environments, there is no clear definition of it. To better understand this, we need to reconsider the width of a road not as a single numerical value but as a complex concept that can be interpreted in different ways. Different road users may refer to different width values for the same road. Thus, while estimating road width seems to come with great benefits for different real-world cases, a fundamental rethinking of the purpose of this entire process is necessary.
Road safety management is an application whose overall process is strongly affected by the width of the road. While there are conflicting theories about the effect that road width can have on road safety, we may need to reconsider a few things before exploring their relation. In this thesis, we introduce a novel approach for estimating road width and linking it with roads in such a way that the overall process of road safety management application could benefit.
Moreover, even road width estimation is not a new topic most of the studies so far use LiDAR point cloud or satellite images as input. In our approach, vector data coming from open-sources are used. Different inputs come with different limitations. The advantages, as well as the drawbacks of the different inputs, will be discussed.
Finally, one of the main objectives of this project is to develop a methodology that will be generally applicable. Vector data that can be found in different datasets would be used. Some additional deliverables will result from our efforts to overcome some of the challenges that have arisen in achieving this goal. A methodology that standardizes road vector data and a methodology that identifies the location and the type of the different intersections will be developed

In large and complex civil engineering projects, well-managed information enables easier and faster access to the required data when available. In the Architecture, Engineering and Construction (AEC) industry, professionals and data managers constantly seek to optimize the information management process to better collaborate in projects that include GIS & BIM integrated workflows. The publication of ISO 19650-1:2018 & ISO 19650-2:2018 (ISO 19650-1&2:2018) standards on best practices for information management, including BIM, was recognized as an opportunity to the digital organization of these processes. As a result, main BIM software vendors have started supporting ISO 19650-1&2:2018 in their platforms, and (non)-governmental organizations have started adopting them in their projects. However, the advancement in the field of GIS BIM integration and the tightly integrated workflows drew the attention towards the need for supporting ISO 19650-1&2:2018in Web GIS for web services. I3S web service is an example of an open OGC Community standard that allows the consumption of 3D GIS data and 3D GIS data converted from 3D BIM data in Web GIS. In this thesis, field analysis addresses the challenges and the role of the Web GIS platform in projects information management processes of the Hoogwaterbeschermingprogramma (HWBP) as a case study. Then, literature studies review ISO 19650-1&2:2018 in the context of the HWBP to highlight the need for a Common Data Environment (CDE) in the Web GIS platform to support ISO 19650-1&2:2018. Moreover, the review tackles the CDE components specified in Part-2 of ISO 19650-1&2:2018, such as metadata allocation. Finally, this thesis discussed the implementation of the CDE components for I3S web services in ArcGIS Online as a Web GIS platform. The novel contribution of this thesis is providing a contextual overview of ISO 19650-1&2:2018 standards in the project information management processes that include working with GIS & BIM data. Moreover, using the British national annex (BS EN ISO 19650-1&2), a flowchart was developed for the metadata allocation systems of information container workflows. Furthermore, the reference implementation discussed a variety of options to implement the metadata allocation components in Web GIS. The discussion provided a solution and PoC functionalities of the CDE components for managing I3S web services. The resulting solution on the CDE components can be utilized to configure CDE workflows and technical solutions to enable ISO 19650-1&2:2018 compliant workflowsin Web GIS.

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.

3D city models are continuously becoming more popular among practitioners due to the volume and versatility of information they contain, which makes them suitable to be used in various applications. However, there is no mechanism to allow maintaining them updated at the same pace that cities evolve, or when error correction is necessary, eventually diminishing their value. Many cities around the world already possess such models which are mostly used for experimentation and research purposes. Such an example is also the city of Rotterdam, whose 3D city model is not regularly updated and has to be outsourced for that purpose. This thesis investigates into addressing this issue by proposing and implementing an integrative maintenance workflow. The workflow is designed to fulfill what the maintenance needs of a typical municipality are expected to be. Those needs were identified after conducting an analysis of the current situation and collecting information from practitioners within the municipality through interviews. The workflow is a combination of 3D city model versioning and visual editing capabilities with the aim to effectively maintain CityJSON encoded models in an intuitive way. Its implementation includes two prototype software implementations: a versioning component, which is utilized to create a workflow inspired by git flow and allows concurrent maintenance and alternative scenario testing in a non-linear and distributed way, and a visual editing component capable of editing CityJSON encoded 3D city models by extending Blender’s functionality. Following the implementation, the workflow was tested by simulating real world maintenance scenarios. The tests demonstrate the feasibility of maintaining 3D city models with such a workflow and more specifically the suitability of git based workflows. At the same time some key parameters of the versioning mechanism are identified which if tuned properly they can optimize the performance, behavior and robustness of 3D city model versioning. With both components being prototype solutions the workflow is far from operational and there is certainly a lot of space for improvement regarding both components. Utilizing the workflow in practice would be the ideal way for collecting useful feedback. Besides that, there are already extensions of Blender that combined with the visual updating component of the workflow can offer advanced integration of editing and analysis capabilities.

CityJSON is a JSON-based encoding for a subset of the CityGML data model and an alternative to the CityGML exchange-format. This new encoding reduces the data size and simplifies the usage. These files can be stored in relational and NoSQL databases. Relational and NoSQL databases have integrated JSON. CityJSON has therefore the potential to be stored and perform efficiently in relational and NoSQL databases. The databases are tested as part of a client-server architecture, because JSON is used in web applications and the 3D city models can not entirely be stored on mobile devices. GraphQL is used as the API layer between the database and the client, because it has the ability to optimise the usage of the network. This is necessary for location-based web applications on mobile devices to stay functional. This research attempts based on this use case to answer the following question: How suitable are MongoDB and PostgreSQL for the storage and querying of CityJSON using GraphQL? CityJSON has first been mapped to the relational database PostgreSQL and the NoSQL database MongoDB. CityGML has also been mapped to PostgreSQL with 3DCityDB to clarify the impact of different exchange formats. The databases are after that accessed and queried through GraphQL. The queries are based on the selection process of an AR application. The architecture is tested based on the number of queries between the databases and GraphQL, the request sizes, the response sizes and the retrieval times. The results show that the usage of JSON maps attributes more flexibly than the mapping of 3DCityDB, which can result in less tables and therefore less joins or queries. On the other hand, querying on a JSON attribute might result in higher retrieval times than querying an attribute with a predefined data type, but this is not investigated. Additionally, the usage of JSON makes it possible to store fields with varying data types such as the hierarchy of arrays. A difficulty can be that software such as GraphQL does not support fields with varying data types and is therefore less flexible. The developer has to work around that. In general, there are no real signs yet that MongoDB and PostgreSQL are not suitable for the storage and querying of CityJSON using GraphQL. Possible signs are that the indexing mechanism with the vertices list can not be stored in MongoDB and only to some extent in PostgresQL, but this might not be a problem since the indexes can be resolved to integer or real coordinates. The attribute presentLoDs can not be stored in MongoDB as well, but this might be solved with a small adjustment. The main recommendations of this research are that the SQL/MQL queries should be implemented as efficiently as possible without being connected to GraphQL first. This should be done to understand the performance of the databases and to understand the impact of GraphQL better. Besides this, a more general understanding of the suitability for all use cases could be provided with a framework that tests more types of queries.