Automatically generated 3D city models are becoming less of a futuristic, demanding or even impossible to attain goal, and more of a necessary, or vastly sought after, means for a multitude of applications. The current prevalence of open geographic information, such as nationwide-covering LiDAR datasets in the Netherlands, opens up opportunities for different parties to experiment in a search for solutions based on LiDAR data. A current approach in answering this demand for 3D city models is 3dfier, which is an ongoing project to automatically generate, disseminate and maintain a 3D city model based on open source airborne LiDAR datasets as a main source. Trees are currently not included in the 3D city models generated by 3dfier, while trees are an integral part of any city landscape.

In this thesis, an implementation is developed that goes through multiple stages of the construction of 3D tree models. First, an initial classification method of the available LiDAR point cloud data is done. This results in a new intermediate point cloud that consists of mostly points belonging to trees. These classified tree points need to be segmented, such that each segment consists of a group of points that represent a single tree. A second classification is constructed after the segmentation, which is called data cleaning. This step ensures that every segment that consists of tree points, is checked for misclassifications and outliers and that these are removed. After cleaning every segment, tree models can be constructed in various LODs and additionally, the types of trees are classified based on identifying features of these trees.

The conclusions of this research are that it is possible to construct 3D tree models based on airborne LiDAR point cloud data and that these can be made to fit in an existing 3D city model. This is demonstrated by creating a 3D city tree model for an existing 3D city model and merging them into one dataset. While further work is required to achieve a seamless fit, the integrated results show that the datasets complement each other well.

The needs and interests for 3D data based on large-scale topography are increasing. A wide variety of these 3D data needs have emerged in multiple domains and for many different applications. Though, research have shown that the interoperability of this 3D data nowadays still is a challenging task. Many barriers are caused by different perspectives of organisations, technical issues during conversions of data and a lack of guidelines. For this research, a case study is done in The Netherlands, one of the countries that experimented a lot with topographical data already. The Dutch Cadastre, Kadaster, has been working on a country wide covering 3D topographical basemap. However, also some of the Dutch source holders of large-scale topography have taken steps towards the development of 3D city models. The question that now arises, and also the main research question of this thesis, is: “How can a variety of 3D city models be integrated in a country wide covering 3D basemap based on large-scale topography?”. In order to achieve an answer to this question, the methodology has been split up into three components. The first component contained a literature study on 3D city models. The second component of the methodology included the interaction with stakeholders, such as Kadaster and various source holders of the Dutch topographical data. This interaction is performed by means of interviews and surveys. The third component contained the technical part, in which different 3D test data is collected and compared. The test data is for almost all stakeholders provided in CityGML, which is an international 3D standard used for 3D models. Various differences in the 3D data of the stakeholders are found. These differences can be found in the contents, the source data, the process and the management. Based on these test data and their differences, a workflow is developed in order to integrate the data. This workflow uses open source tools as cjio and citygml4j for the manipulation, integration and conversion of the data. This resulted in an integrated 3D model, containing both the data from Kadaster as well as the data from the source holders. Results have shown that the differences between the test data, semantically as well as geometrically, led to gaps and height differences in the final integrated model. This study has proven that different 3D city models can be integrated in a country wide covering model, which can be converted to various formats (CityGML, CityJSON and OBJ). A workflow is developed that integrates the test data of 5 Dutch source holders with the data from Kadaster. A few challenges during the conversion and integration of data had to be overcome. These challenges were either caused by errors in the code of the test data or by bugs and errors in the software tools. In the end, two proposals were given for further organisational developments towards a national 3D basemap based on large-scale topographical data. These proposals were based on the results of the literature study, the interviews with stakeholders and the data comparison and integration. In option 1, a national 3D basemap, developed and managed by Kadaster, is proposed. In option 2, a new basis registration, the 3D BGT, is proposed. In this situation Kadaster will provide a 3D basemap once and the source holders will collect and parse the mutations in 3D.

3D reconstruction of the built environment is a widely studied Geomatics topic. Resulting city models are used for a great variety of purposes. The reconstruction of roofs remains challenging. These roofs are not only building blocks for the city models but are of direct interest as well. The company READAAR uses roof segments for the detection of asbestos and PV potential analysis. Typical clients for such analysis are muncipalities and provinces. Currently, READAAR extracts roof segments from the gridded LiDAR dataset: algemeen hoogtebestand nederland 2 (AHN2). The use of LiDAR data however comes with some limitations. Most importantly, outside the Netherlands, LiDAR data is not always available as it is relatively expensive to gather. Furthermore, the point density of the AHN is 6-10 points/m^2, which limits the amount of detail that can be extracted. In the Netherlands countrywide aerial stereo imagery is available at a resolution of 10cm, this potentially gives a point density of 100 points/m^2 after image matching. This research explores the possibilities of using aerial stereo imagery instead of LiDAR data for the efficient large-scale extraction of 3D roof segments. A workflow is designed in which stereo matching and extraction of segments are integrated. This makes the workflow both efficient and easily scalable. Roof segments are extracted in two steps. First, a watershed segmentation is applied to retrieved color segments. Second, these color segments are clustered based on their orientation. The resulting roof segments generally have a higher quality than the segments retrieved with READAARs LiDAR-based approach. However, problems do occur, especially in shaded areas. This could possibly be solved by integrating LiDAR data when available. Another recommendation for future research is improving the matching by using multi-view matching or possibly neural networks. Furthermore, the segmentation could potentially be improved by using multiple images from different years and processing building blocks.

In this report, we briefly summarize the methodology behind the development of a web application for the municipality of the Hague. This application was developed by a group of students during the Synthesis Project (academic period 2017-2018) of the MSc Geomatics programme of TU Delft University, the Netherlands. The main purpose of this application is the estimation of Sky View Factor (SVF), a necessary element for modern urban planning. To calculate SVF, the methodology used is based on 3D point clouds in order to incorporate the urban environment in its entirety (including vegetation). Development of the webpage, along with use for different location across the Hague, have shown that this approach provides a fast and at the same time, quite accurate calculation for SVF.