Linghang Sun

Cascading urban disruptions, from routine roadworks to regional floods, affect mobility in ways that cut across employment, health services, and economic productivity. Yet no standardised methodology exists to synthesise heterogeneous disruption data across scales for sustainable city planning. This paper develops and applies a replicable faceted classification scheme (hereafter “taxonomy”) and a multi-source integration workflow for urban events affecting mobility. The methodology rests on three pillars: a systematic literature review (123 papers), a pan-European citizen survey ( n = 140), and analysis of official disaster databases (the Emergency Events Database [EM-DAT], 4,179 events; the Copernicus Emergency Management Service [CEMS], 962 activations). Standardised crosswalk tables and thematic comparison across sources enable consistent aggregation across these sources under the common taxonomy. Pilot patterns from the application indicate that transport-related disruptions are consistently salient across sources: 85.0% of survey respondents report roadworks and 62.9% public-transport delays. Temporal clustering is pronounced, with 38.5% of reported events occurring within the previous week. Inter-coder reliability for the crosswalk coding reached $$\kappa \ge 0.75$$ . Preparedness baselines suggest limited readiness: only 19.9% of respondents report being well or fully prepared. The taxonomy, crosswalk tables, and integration workflow provide a methodological foundation and pilot-stage design guidelines for urban disruption monitoring; full field validation will require sustained longitudinal data collection, probability-based sampling, and independent replication.