Spatial Data Analysis
1
2020-2021
02038610
Optional
Portuguese
English
Face-to-face
SEMESTRIAL
6.0
Elective
2nd Cycle Studies - Mestrado
Recommended Prerequisites
This course makes the convergence and application of competencies in programming and data analysis. A prerequisite is the transversal use of the knowledge acquired in a bachelor’s degree in informatics engineering, computer science or data analysis.
Teaching Methods
The learning process takes place along theoretical, data lab classes, and work developed autonomously.
Materials for the classes include:
- PPT presentations
- demonstration videos
- real data sets
- geographic information system
- toolkit for geo-data analysis
Learning Outcomes
This unity addresses the topic of exploratory visualization and data analysis for spatial data, namelly geo-referenced data, for decision support. The domains of application are land use analysis, urban mobility, security and terrorism prevention, energy, water and waste management. The theoretical part of the unity addresses the concepts and computational methods. Practical classes are structured around the Data Lab. The Data Lab makes available real world data sets used within two projects. Project A uses geo-referenced data and has the goal of developing competences on the use of Geographic Information Systems and Analytic Tools for geo-referenced data. Project B has the goal of developing competences on the construction of decision support systems for urban design and planning.
Work Placement(s)
NoSyllabus
Concepts
Geographic Information Systems
Positioning
Behaviour Modeling
Land Use, Mobility and Infrastructures
Head Lecturer(s)
Carlos Manuel Robalo Lisboa Bento
Assessment Methods
Assessment
Exam: 50.0%
Project: 50.0%
Bibliography
GIS: A Computing Perspective, 3rd Edition, 2019
Michael Worboys and Matt Duckham
CRC Press
Location-based Services: Fundamentals and Operation
Axel Kupper Wiley
Mobile Positioning and Tracking: From Conventional to Cooperative Techniques, 2nd Edition, 2017
Simone Frattasi, Francescantonio Della Rosa
IEEE Press Wiley
Papers from Journal in the area that are downloadable from the course webpage