To serve the underserved – Identifying the underserved communities
Day 2 Session 2 (1:30 PM)
Presenters:
Wanyun Shao
Christopher Koliba
Corinne Schuster-Wallace
Social vulnerability reflects how populations can be disproportionately affected by hazards due to their demographic and socioeconomic characteristics. This workshop provides attendees with a hands-on introduction to identifying socially vulnerable populations through the development of a Social Vulnerability Index (SVI). Participants will engage in interactive discussions on the concept of social vulnerability and key variables that contribute to social vulnerability, explore the procedures to construct a social vulnerability index. Attendees will evaluate the methodology and provide feedback, fostering a collaborative learning experience aimed at refining SVI construction techniques.
Learning Outcomes:
- Understand the concept of social vulnerability and its relevance in flood risk mitigation operation and management.
- Identify key demographic and socioeconomic variables for constructing a Social Vulnerability Index.
- Learn the basic procedure for applying the common unsupervised machine learning technique Principal Component Analysis (PCA) to analyze demographic data and extract dominant factors.
- Develop a composite Social Vulnerability Index score for geographic units based on factor scores.
- Critically evaluate and provide feedback on the procedure for constructing a Social Vulnerability Index.
Prerequisites:
Knowledge:
- A basic understanding of statistics and familiarity with demographic datasets is recommended
- No prior knowledge of machine learning is required, as the session will provide an introductory-level explanation of PCA
Hardware/Software:
None
Accounts:
None