Daylight is a significant factor in the decision-making process of urban planners and architects when intervening in an urban environment. A considerable element in such a complex environment, assessed in daylight simulations, is greenery, particularly trees, due to their interaction with sunlight and their shading effects.
This thesis investigates the impact of diverse tree 3D representations produced by Actueel Hoogtebestand Nederland (AHN) point cloud data when performing daylight simulation on scenes integrating them. The assessed tree 3D representations are point cloud based representation using small cubes instead of the points from the original point cloud, voxels, alpha shapes of individual trees, and convex hull of branch points. The tool for the daylight simulation was the Daylight Availability Workflow of Climate Studio plugin in Rhino
software which produces time series of simulated illuminance values based on the location and the local solar data, the scene, the material properties of the objects of the scene and surface on which simulation is performed. Specifically, regarding the assigned materials for the voxel presentation, two approaches were followed; one related to the predefined opaque material properties in Rhino software and the other to transparent materials defined by the density point inside a voxel. The reference of the simulations was a dataset of actual illuminance values recorded by the sensor located on the west facade of the CCC building, where is the
position that the simulation was conducted. Also, to examine how the seasonal changes influence the simulation results, simulations for two months, February and June, were performed. For the June simulations, a synthesized point cloud was generated by combining the AHN points with additional points representing the tree canopy.
Next, results from all days in both months the results showed that the point cloud based representation caused a significant overestimation of simulated illuminance values, whereas the Alpha Shape and Convex Hull representations resulted in underestimation. In contrast, the simulation outcomes for voxel representations depended on their material properties (opaque or transparent), spatial allocation, and size. It was proven that for February via the voxel representations of sizes close to 0.10 m there was the best fit between simulations and sensor data, yet it is not clear which voxel material is the most optimal for all the different
sky conditions. However, in June the simulations were not as accurate as in February, as the synthesized point cloud representation probably did not include a sufficient number of points and as the simulation system performed less accurately for days under clear sky conditions.
Consequently, the study demonstrates that voxel representations with sizes around 0.10 m provide the most reliable results for tree modeling in daylight simulations in February, while clarifying the limitations that gave rise to to the poorer performance of alternative representations and of June simulations.

By providing shade for residents in urban areas, cool spaces have been shown to be essential for mitigating the effects of heat stress. In response, the Municipality of Amsterdam developed a map showing walking distances to these spaces. However, the map lacks key information on capacity, accessibility, and precise distance measurements. This project addresses these gaps by identifying quality indicators for cool places and mapping their locations and quality scores across Amsterdam. Additionally, it establishes methods for computing the shortest and shadiest pedestrian routes to these spaces, enabling efficient routing to and from any given location.

To address the research questions, the following procedures were conducted. First, shade maps of Amsterdam were created for each warm month using the Daily Shadow Pattern tool of the Urban Multi-scale Environmental Predictor (UMEP). Second, cool spaces were identified and evaluated based on accessibility, shading, usability, capacity, heat risk, and Physiological Equivalent Temperature (PET) indicators. Lastly, after obtaining and processing the pedestrian network from the Open Street Map database, shade weight was calculated for each street segment, and cool spaces were incorporated into the network, allowing users to generate datasets of the shortest and shadiest distances to cool spaces, and an algorithm that performs four different routing options: the shortest, the shadiest, and two combinations of the shortest and shadiest paths with different weighting ratios either between two locations or from a starting point to its nearest cool space.

The project produced datasets which provide insights into Amsterdam’s cool spaces, their quality, and the shadiest and shortest routes to these locations. Additionally, the code to make these datasets has been made available on GitHub.