Hello GIS Community,
I am currently working on a research-focused project that explores the development of a GIS-based Household Vulnerability Index (HVI) for coastal regions of Bangladesh. In hazard-prone areas, especially those affected by cyclones and storm surges, vulnerability is not uniform—household-level differences play a critical role in disaster impact and response.
My approach integrates multiple spatial and socio-economic indicators, including:
- Elevation and proximity to coastline
- Housing structure type
- Access to cyclone shelters
- Demographic factors (elderly, children, persons with disabilities)
Using GIS and spatial analysis tools, I aim to develop a predictive model that can support:
- Targeted early warning dissemination
- Priority-based evacuation planning
- Data-driven disaster risk reduction strategies
One of the key challenges I am facing is data availability and validation at the household level, especially in data-scarce environments.
I would greatly appreciate insights from the community on:
- Best practices for validating composite vulnerability indices
- Integrating remote sensing data with socio-economic datasets
- Any similar case studies or workflows you have worked on
Looking forward to your valuable suggestions and discussion!
Thank you.
