Indice

783AA Geospatial Analytics A.A. 2025/26

Instructors:

Teaching assistants:

Hours and Rooms

Day of Week Hour Room
Monday 16:00 - 18:00 Room Fib L1
Tuesday 16:00 - 18:00 Room Fib M1

The lectures will be only in person and will NOT be live-streamed

Learning goals

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.

The assessment of the course consists of an oral exam, aimed to test the knowledge acquired by the student during the course.

Topics:

Module 1: Data Analysis

Module 2: Patterns and Laws

Module 3: Models

Calendar

Day Topic Slides/Code Material Teacher
1. 15/09, 16:00-18:00, Fib L1 Introduction to the Course [slides] About the course Introduction to Geospatial Analytics and Human Mobility [book chapter] Introduction to geographic information systems, Chapter 1; [paper] Human Mobility: Models and Applications, Section 1 L. Pappalardo, M. Nanni
2. 16.09 16:00-18:00 Fib M1 Fundamental Concepts I [slides] Fundamental concepts [book chapter] Introduction to geographic information systems, Chapter 2 (Coordinate Systems); [video] Intro to coordinate systems and UTM projection L. Pappalardo
3. 29.09 16:00-18:00 Fib L1 Fundamental Concepts II [slides] Fundamental concepts [paper] A survey of deep learning for human mobility, Section 2.1, Appendix A; L. Pappalardo
4. 30.09 16:00-18:00 Fib M1 Practical session on Fundamental Concepts L. Pappalardo, G. Mauro
5. 06.10 16:00-18:00 Fib L1 Spatial Data Analysis I M. Nanni
6. 07.10 16:00-18:00 Fib M1 Spatial Data Analysis II M. Nanni
7. 13.10 16:00-18:00 Fib L1 Practical session on Spatial Data Analysis M. Nanni, G. Cornacchia
8. 14:10 16:00-18:00 Fib M1 Mobility Data I L. Pappalardo
9. 20.10 16:00-18:00 Fib L1 Mobility Data II L. Pappalardo
10. 21.10 16:00-18:00 Fib M1 Practical session on Mobility Data L. Pappalardo, G. Cornacchia
11. 27.10 16:00-18:00 Fib L1 Preprocessing I M. Nanni
12. 28.10 16:00-18:00 Fib M1 Preprocessing II M. Nanni
13. 03.11 16:00-18:00 Fib L1 Practical session on Preprocessing M. Nanni, G. Cornacchia
14. 04.11 16:00-18:00 Fib M1 Individual Mobility Laws and Models I L. Pappalardo
15. 10.11 16:00-18:00 Fib L1 Individual Mobility Laws and Models II L. Pappalardo
16. 11.11 16:00-18:00 Fib M1 Practical session on Individual Mobility Laws and Models L. Pappalardo, G. Mauro
17. 17.11 16:00-18:00 Fib L1 Collective Mobility Laws and Models L. Pappalardo
18. 18.11 16:00-18:00 Fib M1 Practical session on Collective Mobility Laws and Models L. Pappalardo, G. Mauro
19. 24.11 16:00-18:00 Fib L1 Mobility Pattern Mining I M. Nanni
20. 25.11 16:00-18:00 Fib M1 Mobility Pattern Mining II M. Nanni
21. 01.12 16:00-18:00 Fib L1 Next-location prediction M. Nanni
22. 02.12 16:00-18:00 Fib M1 Practical session on Mobility Pattern Mining and Next-location Prediction M. Nanni, G. Mauro

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