783AA Geospatial Analytics A.A. 2025/26

Introduction

The analysis of geographic information, such as human movements, is crucial due to its impact on several aspects of our society, including disease spreading, urban planning, well-being, pollution, and more. This course will teach the fundamental concepts and techniques underlying the analysis of geographic and mobility data.

Instructors

• Luca Pappalardo: KDD Laboratory, ISTI-CNR and Scuola Normale Superiore, Pisa
• Mirco Nanni: KDD Laboratory, ISTI-CNR, Pisa

Teaching Assistants

• Giuliano Cornacchia: Postdoc researcher, ISTI-CNR
• Giovanni Mauro: Postdoc researcher, Scuola Normale Superiore

Hours and Rooms

The lectures will be held on the following days and times:

• Monday: 16:00 - 18:00, Room Fib L1
• Tuesday: 16:00 - 18:00, Room Fib M1 The beginning of lectures is scheduled for 15 September 2025, and the end of lectures is scheduled for 16 December 2025. The lectures will be only in person and will NOT be live-streamed.

Learning Goals

The course aims to provide students with the knowledge and skills necessary to analyze geographic and mobility data. The assessment of the course consists of an oral exam, which will test the knowledge acquired by the student during the course. Topics covered include:

• Spatial Reference Systems
• Data formats
• Trajectory and Flows
• Spatial Tessellations
• Open-source tools for geospatial analysis
• Digital spatial and mobility data
• Preprocessing mobility data
• Individual and collective mobility laws
• Next-location and flow prediction
• Trajectory and flow generation
• Applications

Module 1: Data Analysis

• Fundamentals of Geographical Information Systems
  • Geographic coordinates systems
  • Vector data model
  • Trajectories
  • Spatial Tessellations
  • Flows
• Digital spatial and mobility data
  • Mobile Phone Data
  • GPS data
  • Social media data
  • Other data (POIs, Road Networks, etc.)
• Preprocessing mobility data
  • Filtering compression
  • Stop detection
  • Trajectory segmentation
  • Trajectory similarity and clustering

Module 2: Patterns and Laws

• Individual mobility laws
• Collective mobility laws
• Mobility pattern mining

Module 3: Models

• Prediction
  • Next-location prediction
  • Crowd flow prediction
  • Spatial interpolation
• Generation
  • Trajectory generation
  • Flow generation

Calendar

The course calendar includes the following topics and activities:

1. Introduction to the Course
2. Fundamental Concepts I
3. Fundamental Concepts II
4. Practical session on Fundamental Concepts
5. Spatial Data Analysis I
6. Spatial Data Analysis II
7. Practical session on Spatial Data Analysis
8. Mobility Data I
9. Mobility Data II
10. Practical session on Mobility Data
11. Preprocessing I
12. Preprocessing II
13. Practical session on Preprocessing
14. Individual Mobility Laws
15. Mobility Models I
16. Practical session on Individual Mobility Laws and Models
17. Mobility Models II
18. Practical session on Collective Mobility Laws and Models
19. Mobility Pattern Mining I
20. Mobility Pattern Mining II
21. Next-location prediction
22. Practical session on Mobility Pattern Mining and Next-location Prediction

Previous Geospatial Analytics Websites

Previous versions of the Geospatial Analytics course are available for the following academic years:

• 783AA Geospatial Analytics A.A. 2024/25
• 783AA Geospatial Analytics A.A. 2023/24
• 783AA Geospatial Analytics A.A. 2022/23

University of Pisa

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Overview:

The University of Pisa is a renowned Italian university with a rich history and a strong academic reputation. It offers a wide range of undergraduate and postgraduate programs across various disciplines.

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Services Offered:

The university provides a comprehensive range of services to its students, including:

Facilities:

Access to libraries, laboratories, sports facilities, and other resources.

Administrative Support:

Assistance with enrollment, tuition fees, and other administrative matters.

Student Life:

Opportunities for extracurricular activities, clubs, and social events.

Academic Guidance:

Support from academic advisors and career counselors.

Language Courses:

Programs to improve Italian language skills.

Accommodation:

Assistance with finding suitable housing options.

Career Service:

Guidance and resources for career development and job searching.

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Student Life and Campus Experience:

The University of Pisa offers a vibrant and diverse campus experience. Students can engage in a variety of extracurricular activities, join student clubs, and participate in social events. The city of Pisa itself provides a rich cultural and historical environment for students to explore.

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Key Reasons to Study There:

Strong Academic Reputation:

The university is known for its high-quality academic programs and research.

International Focus:

The university actively promotes international collaboration and offers programs taught in English.

Cultural Heritage:

Pisa is a historic city with numerous cultural attractions and landmarks.

Affordable Tuition:

The university offers relatively affordable tuition fees compared to other European universities.

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Academic Programs:

The University of Pisa offers a wide range of academic programs, including:

Degree Programs:

Bachelor's and Master's degrees in various disciplines, including science, engineering, humanities, social sciences, and medicine.

Foundation Course:

A preparatory course for international students who wish to enroll in Italian universities.

Summer and Winter Schools:

Short-term programs for students to gain specialized knowledge and skills.

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Other:

The university has a strong commitment to research and innovation. It is also actively involved in international collaborations and partnerships.