Route choice of cyclists recently became a hot topic of research for different disciplines such as transport and urban planning. Among other factors that influence these route choices, the urban environment has been identified as one in a network, road or aesthetic level. However, how the morphology of the built environment influences the cyclists remains rather unexplored. Considering that two routes are equally distant and safe, would a cyclist choose the most idyllic route in terms of its spatial openness? This thesis aims to explore the extent that the visible views of the urban environment affect the route choosing of a cyclist while traveling in the center of Amsterdam, The Netherlands. It also For this purpose, 127 GPS trajectories of the Fietstelweek dataset of 2015 are compared with alternative routes suggested by OpenStreetMap (OSM) via the OpenRouteService Directions API. The suggested alternatives can be either the fastest routes, the longest routes or those recommended by OSM (in terms of travel distance, travel time or safety. Throughout this MSc thesis a methodology based on the visibility of the cyclistis proposed. The visibility analysisis based on the ray casting algorithm in a 3D environment and gives as an output 3D isovists. The 3D isovists are used in order to measure the spatial openness as the ratio of the amount of visible sky, visible buildings and visible ground, as well as the shape of the 3D isovist itself. Opposite to similar researches that are performing the visibility analysis on the actual GPS routes, this thesis project applies the visibility analysis to a simplified version of the OSM street network in the centre of Amsterdam. The simplified OSM street network consists of street segments, the nodes of which represent real road intersections. The output of the visibility analysis per street segment is later mapped to the GPS trajectories and the alternative routes as an aggregated value. Finally, the routes are compared to each other with the ANOVA statistical method (N=127) and the Tukey’s post hoc test, resulting to a quantification of the differences of the GPS routes in terms of spatial openness. The results of the statistical analysis indicate the importance of the distance in the cyclists route choices but also the importance of the ratio of buildings and visible sky, the ratio of buildings and ground as well as a significant preference of the cyclists towards non-homogeneous routes with variation on the street profiles. We consider the methodology as an interesting proposal of measuring attributes that are difficult to be interpreted by using the traditional space syntax methodology and as a new way to provide design guidelines of the city to urban planners and architects when a detailed 3D environment is provided.

This synthesis project is focused on implementing an Internet of Things (IoT) network to measure environmental data in the city of Delft. This network consists of sensor platforms that are placed in the urban environment. Each sensor platform is mounted on fixed locations and it is not moved during the measurement time. The aim is to raise community’s environmental awareness to improve the quality of the environment.
Recent developments in technology made it possible to fabricate small, efficient, and reliable sensors boards which are the base of these sensors platforms and making them efficient and reliable. Sensor boards like Arduino, Raspberry Pi, and LoPy are some examples of these small sensor boards. In this project, the LoPy is used which is a sensor board that is equipped with Bluetooth Low Energy, Wifi and a LoRa radio. This last one is a communication technology that makes longer communication distances possible.
The sensor network measures four different environmental indicators that will be distributed to the public: temperature, humidity, noise and air quality. The network then communicates via LoRa this data to one centralized server where the data is stored, processed and sent back to the citizens. This data is made publicly accessible to academia, citizens and the stakeholders alike. The network is also made interactive, people who pass by can interact with the sensors and request specific environmental data in real time.
The sensor network has been build and deployed in the city. During the uptime of the network it succeeded to provide the data to the citizens via the feedback mechanisms: a website with a dashboard and an automated twitter account. Local differences have been measured with temperature and humidity sensors. With regard to the noise sensor and air quality sensors no definitive conclusions could be drawn.