The analysis of geographic information, such as those describing human movements, is crucial due to its impact on several aspects of our society, such as disease spreading (e.g., the COVID-19 pandemic), urban planning, well-being, pollution, and more. This course will teach the fundamental concepts and techniques underlying the analysis of geographic and mobility data, presenting data sources (e.g., mobile phone records, GPS traces, geotagged social media posts), data preprocessing techniques, statistical patterns, predicting and generative algorithms, and real-world applications (e.g., diffusion of epidemics, socio-demographics, link prediction in social networks). The course will also provide a practical perspective through the use of advanced geoanalytics Python libraries.

Syllabus:
- Spatial Reference Systems
- Data formats
- Trajectory and Flows
- Spatial Tessellations
- Open-source tools for geospatial analysis
- Digital spatial and mobility data
- Preprocessing mobility data
- Privacy issues in mobility data
- individual and collective mobility laws
- Next-location and flow prediction
- Trajectory and flow generation
- Applications