CRP445 ARTIFICIAL INTELLIGENCE IN URBAN PLANNING AND DESIGN
| Course Code: | 1210445 |
| METU Credit (Theoretical-Laboratory hours/week): | 3 (2.00 - 2.00) |
| ECTS Credit: | 5.0 |
| Department: | City and Regional Planning |
| Language of Instruction: | English |
| Level of Study: | Undergraduate |
| Course Coordinator: | Assoc.Prof.Dr. MÜZEYYEN ANIL ŞENYEL KÜRKÇÜOĞLU |
| Offered Semester: | Fall Semesters. |
Course Objectives
The course aims to equip students with the knowledge and skills to integrate artificial intelligence (AI) into urban planning and design processes. By exploring AI techniques such as geospatial AI (GeoAI) and visualization in urban design, students will learn how to analyze urban data, classify land use, develop and apply urban design principles. The course emphasizes practical applications through tools like Google Earth Engine, Orfeo ToolBox, and stable diffusion models, preparing students to address complex urban challenges related to sustainability, resilience, and smart city development.
Course Content
The course presents a thorough examination of the intersection between Artificial Intelligence (Al) and urban planning principles and practices. It is aimed to provide students with a comprehensive understanding of how Al techniques can be applied to address challenges and opportunities in urban planning and design. Participants will learn the evolution of Al and its core elements, with a particular focus on its integration with Geographical Information Systems (GIS), urban growth modelling and visual representation tools. By practical applications, students will gain a comprehensive understanding of the contemporary capabilites and limitations of Al tools in analyzing and decision-making processes in urban development as well as urban design visualizations. Overall, the course aims to equip students with the basic knowledge, skills, and critical thinking about Al tools and techniques in the context of urban planning and design. By the end of the course, students should be able to analyze urban datasets and growth simulation models, apply basic visualization skills of Al through theoretical lectures and discussions, realworld case studies, hands-on exercises and assignments. In addition, students will gain ability to critically evaluate the ethical and societal im lications of Al-driven approaches.
Course Learning Outcomes
The students are expected to comprehend the basic concepts and algorithms in AI, and various applications of AI in urban planning and design. They will be able to use some AI tools to make land use land cover analysis, visual design and other urban planning and design related analyses.
Program Outcomes Matrix
| Level of Contribution | |||||
| # | Program Outcomes | 0 | 1 | 2 | 3 |
| 1 | Knowledge and internalization of the concepts of social responsibility and public interest | ✔ | |||
| 2 | Giving priority to these concepts in planning and practice | ✔ | |||
| 3 | Commitment to professional ethics and values | ✔ | |||
| 4 | Capacity to independently carry out individual tasks and studies | ✔ | |||
| 5 | Ability to work as a responsible team member as well as a leader in team works | ✔ | |||
| 6 | Professional competency to carry out plans and projects with the utmost quality | ✔ | |||
| 7 | In the fields of planning and design: * Knowledge of planning theories * Ability to integrate theory and practice * Competency in problem definition, critical approach, and usage of analysis methods and techniques * Skills of inter-disciplinary and multi-dimensional thinking, analysis, synthesis, implementation, and development of alternative plans and design solutions | ✔ | |||
| 8 | In both Turkish and English: * Knowledge of professional terminology * Ability to carry out and present original studies * Skills of expressing oneself | ✔ | |||
| 9 | Lifelong learning skills and attributes | ✔ | |||
| 10 | Competency in process design and management | ✔ | |||
0: No Contribution 1: Little Contribution 2: Partial Contribution 3: Full Contribution