Graduate Courses
The Department's programme of courses for graduate research students can be accessed by clicking on this link. Each course listed on the programme should normally run at least once every two years. The list of courses and/or their scheduling may be updated from time-to-time. The Department will release information on the final scheduling of course just before the start of each academic year.
Important:
NUS will adopt three new academic terminologies from 1 August 2023 - “Module” will be renamed “Course”, “Modular Credit (MC)” will be renamed “Unit”, and “Cumulative Average Point (CAP)” will be renamed “Grade Point Average (GPA)”. The definition of a Module/Course and MC/Unit will remain the same, and there will be no change to the computation of the CAP/GPA.
Semester 1 - AY2025/26
ASSOC PROFESSOR MAX LUPASCU
Units: 4
Workload: 1-2-0-5-2
Preclusion: GE6215 Pre-requisite(s)/Cross-listing(s): Nil
This course is intended to provide an introduction to integrative aspects of earth environmental sciences, varying from climatology, geomorphology, hydrology to ecology, at the research level. Environmental systems are studied at several scales and research design is examined within the context of experimental methods in physical geography. The course includes lectures, reading assignments and seminars. Students are expected to participate actively throughout. This course is for all graduate students during the first semester in which they are registered in the department of geography. A formal research proposal for beginning graduate students (MA and PhD level) is expected at the end.
C.A.: 100%
DR LUO WEI
Workload: 1-0-2-4-3
Pre-requisite(s): Nil
Preclusion(s)/Cross-listing(s): Nil
This course is designed for students with some experience in geographic information systems (GIS) who want to learn how to extend GIS to perform custom analyses, to automate common GIS tasks, or just to learn how spatial data is structured and managed “under the hood”. Topics will include the fundamentals of programming (in Python), geo-processing function libraries, spatial data structures and access, and geometry and spatial algorithms. No prior programming experience is required.
DR YAN YINGWEI
Units: 4
Workload: 1-1-1-4-3
Preclusion(s): Students with prior GIS training should consult with the lecturer in charge to decide if the module is suitable.
This course aims to introduce students the fundamental concepts and components of Geographic Information Systems (GIS). Fundamental concepts covered include spatial data models, data quality, cartographic principles, and spatial analysis. Hands-on training provided includes spatial data development, attribute management, geovisualization, and spatial analysis operations. Some selected cases of GIS applications in social sciences, humanities, environmental studies, and management will be introduced.
The role of GIS as an integrated platform for decision making will be highlighted. The module is for students who have no prior GIS background but wish to apply geospatial techniques in their respective fields of interest.
C.A.: 100%;
ASSOC PROFESSOR FENG CHEN-CHIEH
Units: 4
Workload: 1-1-3-3-2
Pre-requisite(s)/ Preclusion(s)/Cross-listing(s): Nil
This course provides students with an opportunity to gain hands-on experience in GIS applications across a range of different subject areas, including geography, geology, environmental science, ecology, civil engineering, urban planning, real estate, health sciences, social sciences and humanities. Through this course, students are expected to explore different modelling approaches, discuss applications of the models, and work on lab exercises and research projects.
C.A.: 100%;
DR BENNY CHIN
Units: 4
Workload: 1.5-0-1.5-4-0-3
Pre-requisite(s)/ Preclusion(s)/Cross-listing(s): Nil
Data visualization is crucial for understanding geographical phenomena, and statistical thinking is essential for effective visualization. This course offers students a comprehensive understanding of geospatial data visualization and analysis techniques. Students will develop a strong foundation in statistical methods and spatial thinking abilities while learning to create compelling visualizations using Python. Key topics include statistical patterns, point patterns, areal patterns, and geovisualization. Through hands-on experience with Python libraries, students will enhance their spatial data science skills. By the end of the course, students will be well-equipped to analyze, visualize, and communicate geospatial data insights effectively
C.A.: 100%
ALL TEACHING STAFF
Units: 4
Workload: Minimum 10 hours per week.
Pre-requisite(s)/ Preclusion(s)/Cross-listing(s): Nil
The level 5000 Independent Study Module is designed to enable a graduate student or small group of graduate students to explore an approved topic relating to their planned area of research. Students should normally expect to meet with their mentor three times over the duration of the course.
A proposal must be drawn up between the student(s) and mentor and approved by the Graduate Coordinator/Deputy Graduate Coordinator before the end of week 3 of the semester. This study proposal must state clearly the obligations of the student, the agreed-upon mode of assessment, the relevance of the chosen topic to his/her studies, and provide a clear guarantee that the assignment is in addition to work envisaged as part of their thesis. A culminating piece or pieces of written work (report and/or essay) is/are required. Where students have worked as a group, members of the group may submit individual pieces of written work or, alternatively, may work collectively on a joint piece of written work, depending on the approved agreement.
C.A.: 100%;
To comprise written work with a length that, under normal circumstances, falls within the range 4000-6000 words (excluding references and any appendices but including tables and figure and table captions) for individual reports or essays, or 6000-8000 words (excluding references and any appendices but including tables and figure and table captions) for a group-based, single (collective) piece of written work.
All CA will be double-marked. Where there is a large and unresolved discrepancy between the marks awarded by the two markers (>10%), work may be evaluated by a third marker.
ALL TEACHING STAFF
Units: 4
Workload: Minimum 10 hours per week.
Pre-requisite(s)/Preclusion(s)/Cross-listing(s): Nil
The level 6000 Independent Study Course is designed to enable the student to explore in some depth a topic in Geography that is of relevance to their research interests. Unlike with GE5660, there is no provision for group work with GE6660. Students should normally expect to meet with their mentor three times over the duration of the course.
A proposal must be drawn up between the student(s) and mentor and approved by the Graduate Coordinator/Deputy Graduate Coordinator before the end of week 3 of the semester. This study proposal must state clearly the obligations of the student, the agreed-upon mode of assessment, the relevance of the chosen topic to his/her studies, and provide a clear guarantee that the assignment is in addition to work envisaged as part of their thesis. A culminating piece or pieces of written work (report and/or essay) is/are required.
C.A.: 100%
NOTE
To comprise written work with a length that, under normal circumstances, falls within the range 4000-6000 words in total (excluding references and any appendices but including tables and figure and table captions).
All CA will be double-marked. Where there is a large and unresolved discrepancy between the marks awarded by the two markers (>10%), work may be evaluated by a third marker.