Geographical Data and Models for Decision-making
The Technical Doctoral School of IT and Design at Aalborg University
Welcome to the course "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
Location: A.C. Meyers Vænge 15, Copenhagen, Room 2.3.044
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 visualise 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:
• Data-Driven Decision Making, Typology of Decision-Making & Scenario Building
• (Geo)Data: Data Repositories, Metadata, Citizen Science
• Data Quality and Harmonisation & MAUP Problems
• Data Visualization & Interpolation
• Map Algebra
• Cumulative Impact Assessment
• Normalisation and Weighting Methods, Stakeholder Analysis
• Multi-Criteria Evaluation and Cost Surface
• Sensitivity Analysis
• Predictive Modelling and the Role of AI
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.
Important information concerning PhD courses: We have long experienced problems with 'no-show' for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before the start of the course. Registered illness is, of course, an acceptable reason for not showing up on those days.