Heterogeneous recovery trajectories after extreme rainfall and their drivers: A study in Mentougou, Beijing
Year: 2026
Type: article
Abstract: Short-duration, high-intensity extreme rainfall events increasingly disrupt urban systems, underscoring the importance of enhancing urban disaster resistance and post-disaster recovery resilience under escalating climate-related risks. However, research on recovery resilience following severe rainfall is often constrained by limited data availability, insufficient temporal resolution, and inadequate characterization of spatiotemporal heterogeneity in recovery patterns. To address these challenges, this study employs daily NASA VIIRS nighttime lights (NTL) time-series data to dynamically monitor the post-disaster recovery of residential activity areas in Beijing Mentougou District following the catastrophic “23·7” extreme rainfall event in 2023. Pixel-level Recovery Rate Indices (RRI) were constructed from NTL signals, and time-series clustering was applied to identify heterogeneous recovery trajectories. Furthermore, explanatory modeling was used to investigate the key drivers underlying different recovery pathways. Results show that five distinct recovery patterns can be delineated, forming a continuous gradient from “rapid recovery” to “severely delayed or ongoing recovery.” Recovery signals were concentrated primarily in built-up valleys and transportation corridors, whereas high-mountain regions exhibited limited brightness rebound, highlighting significant topographic constraints on repair activities. Driver analysis indicates that socioeconomic factors, including population density, settlement compactness, and GDP density, play a substantial role in facilitating post-disaster recovery. In contrast, elevation and slope exert inhibitory effects by constraining transportation accessibility and limiting the feasibility of reconstruction activities. The proposed recovery trajectory analytical framework enables quantitative monitoring and pattern recognition of short-term post-disaster recovery, providing scientific support for formulating differentiated recovery strategies and resilience-enhancement measures in mountainous areas under extreme climatic hazards.
Source: Journal of dynamic disasters.
Authors: Qi Wang, Tao Chen, Guofeng Su, Lida Huang
Institution: Tsinghua University
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid:
OpenAlex ID: W7129597135