Building a geospatial inventory of electricity infrastructure exposure to climate risks in the Greater Bay Area
Project Description
This project focuses on database development and spatial analysis rather than advanced modelling. The student will develop a geospatial inventory of electricity infrastructure in the GBA using open-source data, including the Open Infrastructure Map, the Baker Institute China Energy & Infrastructure Map, and Hong Kong’s Common Spatial Data Infrastructure. The inventory will include transmission lines (where available), substations, power plants, and major urban features. The student will then overlay basic climate risk proxies (such as flood-prone areas, low-lying zones, and typhoon exposure indicators) to qualitatively assess infrastructure exposure. The goal is not precise vulnerability estimation but the construction of transparent and replicable exposure indicators suitable for scenario-based resilience analysis. The project requires a student with a background in Geographic Information Systems (GIS) concepts, including layer management, spatial overlays, and simple exposure mapping. Outputs will include a curated geospatial dataset, a set of illustrative maps, and a short explanatory note outlining assumptions, data gaps, and limitations. This project feeds directly into the broader research by providing spatial context where detailed grid schematics are unavailable, while offering the student hands-on experience in integrating infrastructure and climate data.
Supervisor
DELINA Laurence Laurencio
Quota
2
Course type
UROP1000
UROP1100
UROP2100
UROP3100
UROP3200
UROP4100
Applicant's Roles
1. Collect and curate geospatial data on power plants, substations, and transmission lines from open sources.
2. Overlay basic climate risk layers (elevation, flood zones, typhoon exposure proxies) using GIS software.
3. Produce clear, annotated maps illustrating infrastructure exposure patterns.
4. Document where proxies are used and explain what can and cannot be inferred.
2. Overlay basic climate risk layers (elevation, flood zones, typhoon exposure proxies) using GIS software.
3. Produce clear, annotated maps illustrating infrastructure exposure patterns.
4. Document where proxies are used and explain what can and cannot be inferred.
Applicant's Learning Objectives
1. Gain introductory experience with spatial datasets for energy research.
2. Learn how proxy data are used when direct infrastructure data are unavailable.
3. Understand the spatial dimensions of climate risk and infrastructure resilience.
2. Learn how proxy data are used when direct infrastructure data are unavailable.
3. Understand the spatial dimensions of climate risk and infrastructure resilience.
Complexity of the project
Challenging