Building a geospatial inventory of electricity infrastructure exposure to climate risks in the Greater Bay Area
Project Description
This project focuses on geospatial database development, data validation, and spatial screening analysis rather than advanced modelling. Building on work completed during Summer 2026, the student will first undertake a systematic review of an existing geospatial inventory of electricity infrastructure in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), including power plants and substations derived from open-source datasets. The student will carefully examine the data sources, workflows, attribute structure, spatial accuracy, and documentation produced in the earlier phase of the project, with the objective of improving transparency, reproducibility, and data quality.
Following this review, the student will refine, update, and expand the infrastructure database where feasible using publicly available geospatial data sources. Tasks may include identifying missing assets, correcting location inconsistencies, improving attribute information, documenting metadata, and assessing the completeness and limitations of the existing inventory. The student will also review and replicate the spatial screening procedures previously developed, including low-elevation and coastal-proximity indicators, to ensure that all methods and outputs can be reproduced independently.
The project will then explore additional climate-related exposure indicators that can be implemented using open geospatial datasets. Potential extensions include flood-prone areas, low-lying terrain, coastal proximity, typhoon-related exposure proxies, and other indicators relevant to infrastructure resilience. The objective is not to generate precise risk estimates but rather to develop transparent, replicable, and clearly documented screening metrics that can support subsequent resilience and vulnerability research.
The project is particularly suitable for students with an interest in Geographic Information Systems (GIS), spatial data management, and environmental assessment. Familiarity with GIS concepts such as coordinate systems, spatial overlays, attribute management, and map production will be advantageous.
Expected outputs include: (1) a reviewed and enhanced geospatial inventory of electricity infrastructure in the GBA; (2) documentation of data sources, assumptions, workflows, and limitations; (3) a suite of maps illustrating infrastructure distribution and exposure indicators; and (4) a short technical report describing the methods, findings, data gaps, and recommendations for future development. The project contributes directly to ongoing research on energy-system resilience and climate adaptation by strengthening the spatial evidence base for analysing electricity infrastructure exposure in the Greater Bay Area.
Following this review, the student will refine, update, and expand the infrastructure database where feasible using publicly available geospatial data sources. Tasks may include identifying missing assets, correcting location inconsistencies, improving attribute information, documenting metadata, and assessing the completeness and limitations of the existing inventory. The student will also review and replicate the spatial screening procedures previously developed, including low-elevation and coastal-proximity indicators, to ensure that all methods and outputs can be reproduced independently.
The project will then explore additional climate-related exposure indicators that can be implemented using open geospatial datasets. Potential extensions include flood-prone areas, low-lying terrain, coastal proximity, typhoon-related exposure proxies, and other indicators relevant to infrastructure resilience. The objective is not to generate precise risk estimates but rather to develop transparent, replicable, and clearly documented screening metrics that can support subsequent resilience and vulnerability research.
The project is particularly suitable for students with an interest in Geographic Information Systems (GIS), spatial data management, and environmental assessment. Familiarity with GIS concepts such as coordinate systems, spatial overlays, attribute management, and map production will be advantageous.
Expected outputs include: (1) a reviewed and enhanced geospatial inventory of electricity infrastructure in the GBA; (2) documentation of data sources, assumptions, workflows, and limitations; (3) a suite of maps illustrating infrastructure distribution and exposure indicators; and (4) a short technical report describing the methods, findings, data gaps, and recommendations for future development. The project contributes directly to ongoing research on energy-system resilience and climate adaptation by strengthening the spatial evidence base for analysing electricity infrastructure exposure in the Greater Bay Area.
Supervisor
DELINA Laurence Laurencio
Quota
2
Course type
UROP1000
UROP1100
UROP2100
UROP3100
UROP3200
UROP4100
Applicant's Roles
1. Review and evaluate the Summer 2026 project outputs, including the geospatial database, GIS workflows, maps, screening indicators, and documentation.
2. Validate and enhance the electricity infrastructure inventory by identifying data gaps, checking spatial accuracy, refining attributes, and improving metadata.
3. Replicate and extend spatial screening analyses, including low-elevation, coastal-proximity, flood, and other climate-exposure indicators using open geospatial datasets.
4. Produce and interpret maps illustrating infrastructure distribution and exposure patterns, with clear explanations of assumptions, uncertainties, and limitations.
5. Document methods and findings in a concise technical report, including recommendations for future database development and resilience research.
2. Validate and enhance the electricity infrastructure inventory by identifying data gaps, checking spatial accuracy, refining attributes, and improving metadata.
3. Replicate and extend spatial screening analyses, including low-elevation, coastal-proximity, flood, and other climate-exposure indicators using open geospatial datasets.
4. Produce and interpret maps illustrating infrastructure distribution and exposure patterns, with clear explanations of assumptions, uncertainties, and limitations.
5. Document methods and findings in a concise technical report, including recommendations for future database development and resilience research.
Applicant's Learning Objectives
1. Develop practical skills in GIS-based energy infrastructure research, including geospatial data management, validation, mapping, and spatial analysis.
2. Learn how to assess, replicate, and improve geospatial datasets and screening methods, with attention to data quality, transparency, and reproducibility.
3. Understand how spatial indicators and proxy data can be used to evaluate climate-related exposure and infrastructure resilience when detailed engineering data are unavailable.
2. Learn how to assess, replicate, and improve geospatial datasets and screening methods, with attention to data quality, transparency, and reproducibility.
3. Understand how spatial indicators and proxy data can be used to evaluate climate-related exposure and infrastructure resilience when detailed engineering data are unavailable.
Complexity of the project
Challenging