Supporting Dataset — Spatiotemporal Dynamics of Urban Resilience: An Integrated Assessment across Four Case Studies (1996–2024)

This dataset supports the manuscript: Spatiotemporal Dynamics of Urban Resilience: An Integrated Assessment across Four Case Studies (1996–2024), submitted to Humanities and Social Sciences Communications (Springer Nature). Overview: This supporting dataset provides the processed tabular data, model performance metrics, and planning framework thresholds underlying the results reported in the manuscript. All primary satellite inputs were derived from publicly available sources (ESA CCI, ERA5, Sentinel-2). This file contains the intermediate and derived datasets necessary to interpret, replicate, and build upon the study's findings. Study context The manuscript examines urban hydrological resilience across four contrasting case studies spanning 1996–2024: the Greater Bay Area (GBA), China (subtropical megalopolis); the United Arab Emirates (hyper-arid extreme events); southern Madagascar (Global South drought vulnerability); and the Andean páramos, Ecuador/Peru (natural reference system). The core analytical output is the Robustness Index (RI = μ(SM)/σ(SM)), derived from ESA CCI satellite soil moisture data, which underpins a three-tier spatial planning framework (Conservation: RI > 2.5; Mitigation: 1.5 3× the annual average), with NDVI increasing 275% within 30 days. Multi-source SVI+RSI fusion achieved a mean cross-validated R² of 0.417–0.649 for soil moisture prediction. The Andean páramos maintain RI = 3.8–4.2, serving as the natural reference benchmark. Ethical statement No human participants, personal data, or biological material were involved. All data are derived from publicly available satellite and reanalysis products. No ethical approval was required.