The continuously increasing population within cities imposes the future challenges related to planning and managing the sustainable environment, where people’s health and wellbeing is prioritized. Currently more than half of the world’s population live in cities which results in the rise of the human footprint, affecting the local climate. Simultaneously the planet’s climate is changing towards less predictable weather conditions with high extremes, e.g., heavy rainfalls, followed by long dry periods or severe heatwaves. Frequently extreme weather conditions are associated with flooding and hurricanes, while heatwaves represent an equally important danger for the health of city’s citizens.
UHI has been recognized as one of the leading environmental issues of the 21st century. The UHI is defined as the area within a city with the higher surface or air temperatures compared to its surroundings. The higher urban temperatures are resulting in health-related issues among the population, greater energy demands, and various economic losses. Thus, the current work is focusing on researching the air temperatures in the urban canopy layer, which are mainly affected by the heat radiated from the urban surfaces during the night. Moreover, there are differences in the heat exchange phases between the neighborhoods, which are caused by the heterogenicity of the morphological characteristics of the city. Such information can be of great use for the development of UHI mitigation strategies, but it is currently very sparse or not detailed enough. Therefore this master thesis investigates the possibility for generation of more detailed models, taking into account the intraurban variability. For the development of the statistical models explaining the UHI effect in the city of the Hague different spatial and sensor datasets have been used. The data about the temperatures in the city for 2017 have been collected with the means of the Netatmo weather stations. Additionally, different spatial representations and their effect on the statistical analysis have been investigated. In combination with the different spatial models, six distinct UHI contributing factors have been researched, namely the Buildings density, the Land cover index, the Vegetation index, the Sky View Factor, the Non-permeable surfaces in the city and the Vehicle traffic density. These variables have been calculated and utilized in the statistical analysis of their relationship with the air temperatures in the Hague. The results indicated a weak relationship between the air temperatures and the different spatial characteristics of the city where only the Sky View Factor and the Non-permeable surfaces proved to be statistically significant variables.

Along with the rise of the smart city movement, Internet of Things is an upcoming phenomenon. Objects and devices are becoming more and more wirelessly interconnected, communicating information between themselves and to human beings. As an extension on static sensor networks that gather real-time environmental data, the feasibility of implementing a dynamic sensor network based on LoRa
communication is researched. To achieve such a dynamic system, a self-developed sensor platform was constructed, based on the microcontroller LoPy. Sensors attached to it include a hygrometer, thermometer and microphone.
The emphasis of the research was on localisation of the sensors, to put the gathered sensor data into geographical context. A WiFi fingerprinting radiomap was constructed based on available MAC-addresses, their signal strengths, and GPS coordinates. The GPS module was only used for composing the radiomap. When the radiomap is completed, the module can be switched off, only to be switched on for periodical updates of the radiomap. The quality of the radiomap methodology was evaluated by constructing it of measurements gathered in four days, and testing it for the remaining three days. This test gave a correctness of 50% while another 38% of measurements were localised in a neighbouring cell. The correctness can be improved by having a longer training period.
The quality of the collected sensor data turned out to be dependent on the weather conditions and the placement location on the carrier vehicle. Vehicle requirements were specified as driving through the city centre and having a schedule and route producing as little noise, heat and air pollution as possible. Another topic of research was LoRa communication, which was deemed as very limited for dynamic implementations, as the sending of location-related data takes up a large part of the already limited message size. To decrypt the sent message and store it in a meaningful database, Node-RED was used. Despite visualisation of measurements showed promising results, there is margin for improvement as far as data capturing is concerned.