Urban Flood Resilience Assessment for High-Density Cities Using Graph-Based Zoning

A dataset supporting research on morphology-sensitive flood resilience in high-density urban areas. It integrates graph-based morphological zoning and explainable machine learning to examine spatial variations in resilience mechanisms, using ultra-high-density coastal Macau as a case study. The dataset was created by Ziyi Chen and last updated on May 13, 2026.

Use Cases

• Analyze spatial variations in flood resilience based on urban morphological zones.
• Identify threshold effects and inter-factor interactions of built-environment variables using nonlinear modeling.
• Compare the performance of conventional unified evaluation frameworks against morphology-sensitive approaches.
• Develop zone-specific resilience planning strategies for climate adaptation.

Strengths

• Dataset size is 635.5 MB, indicating a medium-scale collection of data.
• Includes results from explainable machine learning models identifying nonlinear relationships between resilience and infrastructure, vegetation, and urban form.
• Focuses on a specific case study of ultra-high-density coastal Macau, providing concrete spatial context.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

Ziyi Chen via figshare

Collection Method

Likely contains results from integrating graph-based morphological zoning and explainable machine learning models.

Freshness

Last updated 2026-05-13 08:00:01; freshness should be verified.

Geography

Ultra-high-density coastal Macau