Examining the role of indicators and scale in social vulnerability index construction: A comparative geospatial analysis of inductive and hierarchical models

Social vulnerability indices (SVIs) are tools for spatially identifying populations vulnerable to natural hazards. However, their construction involves methodological choices that can introduce epistemic uncertainty. While previous efforts have explored how construction processes influence outcomes, further validation is needed to ensure SVIs accurately capture vulnerability. This study advances validation efforts by examining how scale, both areal units (Census block groups and tracts) and geographic boundaries (state, coastal, and city), impact SVI construction and indicator behavior. We applied two indicator sets, the Centers for Disease Control (CDC) SVI and the Hazards Vulnerability and Resilience Institute SoVI, and compared across three index structures: inductive with z-score standardization, hierarchical with percentile ranking normalization, and hierarchical with z-score standardization. Using geospatial and hotspot mapping, we analyze how interactions across index model stages impact vulnerability rankings and spatial patterns. We also examine how indicators influence shifts across scales in vulnerable areas. Results show that scale and indicator selection shift spatial patterns and reshape indicators' roles in SVIs. Notably, the hierarchical structure with z-score standardization—unlike those used in the CDC SVI or SoVI—produced the most consistent rankings, hotspot identification, and indicator performance. These findings highlight the importance of scale-indicator interactions and model structure selection in SVI design.