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Geographical Data and Models for Decision-making
October 16 - October 18
GEOGRAPHICAL DATA AND MODELS FOR DECISION-MAKING
The Technical Doctoral School of IT and Design at Aalborg University
Welcome to Geographical Data and Models for Decision-Making
Organizer: Jamal Jokar Arsanjani (jja@plan.aau.dk), Ida Maria Bonnevie (idarei@plan.aau.dk), Irma Kveladze (ikv@plan.aau.dk)
Lecturers: Ida Maria Bonnevie, Jamal Jokar Arsanjani, Irma Kveladze
ECTS: 3
Date/Time: 16 -18 October 2024, 9:00-15:00
Deadline: 25 September 2024
Max no. Of participants: 20
Description: Optimal and efficient Land use and Sea use planning requires developing spatial decision support systems in which various geographical, attribute, quantitate and quantitative datasets can be integrated and overlaid. Doing so will allow the relevant decision-makers and stakeholders to contribute to the decision-making process while being able to trace the entire decision-making process and interactively visualize the outcomes of different scenarios.
This PhD course aims to introduce the PhD students to various methodologies for designing and implementing spatial decision support systems for land use planning and maritime spatial planning while considering climate change and its futuristic effects on nature, society, and land and marine ecosystems.
The course will include hands-on examples brought up to the course by the participants and will provide them with an overview of existing decision support systems, and discuss relevant evaluation criteria and decision alternatives and the uncertainties associated with them.
The course will cover the following topics:
• Introduction to spatial decision support systems
• Introduction to Geodata and Data Repository
• Data Visualization
• Data Quality and Harmonisation
• Map Algebra
• Typology of Decision-Making Systems
• Normalisation and Weighting Methods
• Multi-Criteria Decision Making and Cost Surface
• Sensitivity Analysis
• Cumulative Impact Assessment
• Artificial Intelligence (AI)
• Case studies – feedback on students work.
Before the course each PhD student must deliver a description of their PhD work and scientific reflections on their potential use of spatial decision support systems.
After the course, the PhD students must submit a draft paper (4-6 pages) on their own use of spatial decision support systems.
Prerequisites: the ability and passion to solve societal challenges using decision support systems in a data-driven manner.
Disclaimer:
DDSA has explicit permission from Arcanic and the owners of the https://phdcourses.dk/ website to display the courses on ddsa.dk.
