Analysis of Sensor Network Climate Data: The Case of The City of Padua

In recent years, the study of urban environmental conditions has gained significant attention due to its implications for public health, climate adaptation, and urban planning. Temperature, as a critical parameter, plays a key role in understanding local microclimates and their dynamic behavior. This thesis investigates data collected from a network of sensors installed in the city of Padua, designed to continuously monitor temperature. Using advanced data analysis techniques and network modeling, the research identifies connections and relationships among the sensors, enabling the discovery of patterns that may not be immediately apparent, revealing how their associations evolve over time and space. The results highlight key temporal variations and spatial clusters, offering insights that can enhance urban monitoring systems and inform more effective, climate-responsive urban planning.