A seminal study on transportation system resilience has recently been published in the Journal of Geo-Information Science , led by Dr. Junqing Tang and Prof. Pengjun Zhao and their team from the School of Urban Planning and Design at Peking University. Through a systematic review, the research provides a comprehensive examination of spatiotemporal big data applications in transportation resilience studies, including mainstream data types, four key application domains (quantitative assessment, monitoring and early warning, simulation and prediction, and system optimization), and their corresponding methodologies, along with emerging research trends.
The findings reveal that quantitative assessment currently represents the most developed application area, while real-time monitoring and early warning systems remain significantly understudied, presenting a crucial gap in current research. Simulation studies face particular challenges in scaling up predictions due to limitations in data quality and computational requirements. Most system optimization research remains theoretical, with relatively few empirical studies effectively utilizing multi-source spatiotemporal big data, indicating substantial potential for further development.
The study documents a paradigm shift in transportation resilience management—from reactive post-event analysis to proactive full lifecycle monitoring. This transition aligns with developments in space weather research, where pre-event conditions are now acknowledged as equally critical for predicting system responses. However, the research identifies persistent challenges comparable to those in atmospheric sciences, particularly regarding data limitations and the requirement for more sophisticated observational networks. The findings demonstrate that comprehensive understanding of transportation system behavior necessitates the integration of diverse data sources and analytical methodologies, mirroring current approaches in space environment studies.
Published in the Journal of Geo-Information Science , this study establishes a fundamental basis for future investigations, emphasizing the need for improved data integration frameworks and interdisciplinary cooperation to advance both theoretical and applied aspects of transportation resilience. The study offers significant insights for developing more robust transportation infrastructure capable of withstanding intensifying climatic and urban pressures.
For more details, please refer to the original article:
Review and prospects: Application of spatio-temporal big data in transportation system resilience studies.
https://www.sciengine.com/JGIS/doi/10.12082/dqxxkx.2024.240107（If you want to read the English version of the full text, please click on the “iFLYTEK Translation” in the article page.）
Review and Prospect of Spatio-temporal Big Data in Transportation System Resilience Research
25-Mar-2025