 |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | The course aims to provide a comprehensive understanding of the city and the system of cities, the challenges faced by cities, especially the rapidly-developing large cities, and the key tools for interventions in response to critical pressures linked to economic development, urbanization, globalization, migration, social inclusion, climate change, resource efficiency, technology etc. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6235) | Mo 09:00AM - 11:50AM | Rm 102, E1 | KAN, Ge Lin WANG, Binzhe ZHAO, Wufan ZHOU, Muzhi | 25 | 0 | 25 | 0 |
| VECTOR | [3-0-1:3] |
|---|---|
| DESCRIPTION | This course introduces students to the basic concepts and methods in Geographic Information System (GIS), and their applications in urban design and governance, environmental and infrastructure sustainability, and smart city management. This course integrates social science and informatics perspectives, and is suitable for students with various backgrounds. In addition to learning traditional GIS data, spatial analytical techniques, and GIS software, this course also develops skills of manipulating spatially detailed urban sensing Big Data (about urban activities, environmental qualities, and mobility patterns). |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6329) | We 01:30PM - 04:20PM | Rm 228, E1 | LI, Chaosu | 15 | 0 | 15 | 0 | |
| LA01 (6330) | We 04:30PM - 05:20PM | Rm 228, E1 | LI, Chaosu | 15 | 0 | 15 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | The course looks at some of the major drivers of urban inequality and poverty, and the key actions that cities are taking to reduce urban inequalities through urban design, infrastructure and policy. Students are introduced with tools to analyze the socio-demographic profile of households and neighborhoods/communities and their relation to spatial distribution and clustering in cities of both the developing and the developed world. A particular emphasis is placed on identifying spatial strategies that can alleviate the concentration of urban poverty and inequality to enhance urban social cohesion by optimizing access to jobs, housing, education, health, public space, transport and community infrastructure. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6236) | We 03:00PM - 05:50PM | Rm 202, E1 | ZHANG, Zhuoni | 15 | 0 | 15 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| PRE-REQUISITE | UGOD 5020 |
| DESCRIPTION | The course introduces students to basic practices and tools that will enhance their ability to conduct empirical research and analysis in applied economics and relevant disciplines in a data-rich world. By the end of the course, the students will be proficient in a variety of data management, visualization, and quantitative techniques necessary to efficiently conduct independent research. The course format is “hands-on”, and students will conduct most of their work on their personal computers using R and RStudio. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6237) | Tu 06:00PM - 08:50PM | Rm 201, W1 | YANG, Lin | 15 | 0 | 15 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| CO-REQUISITE | UGOD 5020 |
| DESCRIPTION | Life course analysis provides a framework to understand many topics across different disciplines, such as family and fertility, migration, child development and education, paid and unpaid work, and wellbeing, heath and ageing. Those decisions or outcomes of individuals are a result of how individuals interact with each other in the specific culture and historical context that is shaped by our city, policy, and environment. This course will introduce the field of life course research and basic concepts, cover a range of established research topics, with a focus on the theoretical and substantive research in addition to the translation of these research questions into empirical applications. Another central goal will be the introduction of event history techniques and sequence analysis. Students will learn how social survey data, administrative data, and geographic information are synthesized to answer those research questions. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6238) | We 09:00AM - 11:50AM | Rm 101, W2 | ZHOU, Muzhi | 15 | 0 | 15 | 0 |
| VECTOR | [2-1-0:3] |
|---|---|
| DESCRIPTION | Going beyond conventional GIS and geospatial analysis, this course delves into the realm of complexity-science methods, including fractal geometry, power law statistics, space syntax, complex networks, scaling hierarchy, and cellular automata. By embracing pivotal concepts like "natural streets" and "natural cities," alongside the tools such as Axwoman and head/tail breaks, students will explore city structure and dynamics from a complexity-science perspective. These concepts, methods and tools will be applied to open-access geospatial big data such as OpenStreetMap, nighttime imagery, and location-based social media data for revealing insights into cities for better transforming modern cities towards a sustainable planet. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6324) | Mo 06:30PM - 08:20PM | Rm 101, W2 | JIANG, BIN | 15 | 0 | 15 | 0 | |
| T01 (6328) | Mo 08:30PM - 09:20PM | Rm 101, W2 | JIANG, BIN | 15 | 0 | 15 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | This course focuses on applying machine and deep learning methods for remote sensing and covers a variety of practical applications of remote sensing image processing in complex urban environments. Through a mixture of theoretical and hands-on sessions, students will gain a deeper understanding of advanced image analysis methods and will be able to apply new concepts and approaches to enhance their problem-solving abilities in the interdisciplinary field using multi-source geo-information. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6242) | Mo 01:30PM - 04:20PM | Rm 202, E1 | ZHAO, Wufan | 20 | 0 | 20 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | This course explores the theories, principles, and methods for analyzing spatiotemporal behaviors, with a focus on understanding patterns in human mobility, urban dynamics, and transportation systems (especially micro-mobility systems). Students will learn to apply computational techniques to geographic and mobility data, integrating concepts from transportation studies to examine how individuals and populations interact with their environment over time and space. The first part of the course introduces spatiotemporal behavior, while the second part involves case studies, analysis, and simulation of spatiotemporal behavior using methods such as agent-based modeling and machine learning. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6332) | Tu 01:30PM - 04:20PM | Rm 101, W2 | LI, Qiumeng | 15 | 0 | 15 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | The module’s objective is to familiarise students with the modelling of urban systems and their analytical applications. Two major techniques will be introduced in this course: Network Science and Agent-based Modeling (ABM). In the Network Science section, students will learn the basic concepts and recent developments in network science and its applications in urban studies. They will learn how to represent various urban systems using a graph structure and apply advanced machine-learning techniques, including Graph Neural Networks (GNN) and Computer Vision (CV) techniques, to analyse the urban system, including street networks and mobility patterns. For the ABM part of the course, students are expected to understand the core concepts of ABM, including agents, environments, and behaviours. They will design and implement ABM for urban systems using tools like NetLogo or Mesa, simulate models, and analyse outcomes to study urban dynamics such as human dynamics and urban development. Additionally, students are expected to integrate advanced machine learning tools such as GNN and CV techniques in their projects. Prerequisites: basic knowledge of Python and GIS software. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6334) | Mo 09:00AM - 11:50AM | Rm 101, W2 | TBA | 15 | 0 | 15 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | This course will provide an overview of qualitative and mixed research, with an emphasis on its application in urban studies. The course will begin with a discussion of the main types of research methodologies and the history of mixed research. We will delve into the techniques for collecting, analyzing, integrating, and reporting data from multiple sources will be introduced. The course will also discuss different forms of causality, causal inference, and theory testing in qualitative and comparative case study approaches. Participants will be encouraged to engage with the latest trends in mixed methods including qualitative comparative analysis, process tracing, and analytical narratives. The main goal of this course is to equip participants with relevant knowledge, skills and awareness of using the proper methods in solving the research questions in social science studies. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6335) | Tu 09:00AM - 11:50AM | Rm 105, E3 | TBA | 15 | 0 | 15 | 0 |
| VECTOR | [1 credit] |
|---|---|
| DESCRIPTION | Selected topics in hands-on data analyses, such as statistical software (R, STATA, or SAS), data management, and visualization, will be introduced to students in urban governance and design for their research. The course is offered once a year. Graded P or F. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| T01 (6239) | Tu 04:30PM - 05:20PM | Rm 101, W2 | WANG, Binzhe | 20 | 11 | 9 | 0 |
| DESCRIPTION | Master's thesis research supervised by co-advisors from different disciplines. A successful defense of the thesis leads to the grade Pass. No course credit is assigned. |
|---|
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| R01 (6240) | TBA | No room required | TBA | 999 | 20 | 979 | 0 |
| DESCRIPTION | Original and independent doctoral thesis research supervised by co-advisors from different disciplines. A successful defense of the thesis leads to the grade Pass. No course credit is assigned. |
|---|
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| R01 (6241) | TBA | No room required | TBA | 999 | 4 | 995 | 0 |