Authors: Zeyu Zhao, Jiayu Chen, Helen X.H. Bao, Yuhan Zheng, Zhaoyi Li, John E. Taylor, Tianguang Meng, Dongping Fang
Year: 2026
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Research line: AI and computational methods for spatial analysis
One-line summary
Synthesizes millions of geotagged citizen appeals with IoT infrastructure logs to quantify a “resilience perception gap” — the disconnect between physical infrastructure recovery and residents’ subjective lived experience after a disaster.
Abstract
Conventional resilience metrics prioritise physical infrastructure restoration on the assumption that technical service recovery equates to societal recovery. This study uses a catastrophic historic rainstorm as a natural experiment to quantify the resilience perception gap. By synthesizing millions of geotagged citizen appeals with real-time IoT infrastructure logs, the authors show the gap is structured (not noise) and driven by urbanisation inequalities and the hierarchy of human needs. Physical metrics overestimate resilience for survival necessities (30.2% lag) while underestimating livelihood needs (10.4% surplus).
Cross-listed research lines
Primary: AI / computational methods for spatial analysis (ML in Step 4) Also relevant to: Crisis / public health response (resilience, disaster recovery)