Wang, S., He, J., Ma, R., Cheng, Z. & Ding, H. A Comprehensive Vector Dataset of Bus Networks Across China for the Year 2024. Sci Data 12, 524 (2025).
Papagiannaki, K. et al. Developing a large-scale dataset of flood fatalities for territories in the Euro-Mediterranean region, FFEM-DB. Sci Data 9, 166 (2022).
Aerts, J. C. J. H. et al. Integrating human behaviour dynamics into flood disaster risk assessment. Nature Clim Change 8, 193–199 (2018).
Rentschler, J., Salhab, M. & Jafino, B. A. Flood exposure and poverty in 188 countries. Nat Commun 13, 3527 (2022).
Rogers, J. S., Maneta, M. P., Sain, S. R., Madaus, L. E. & Hacker, J. P. The role of climate and population change in global flood exposure and vulnerability. Nat Commun 16, 1287 (2025).
Guo, X. et al. The extraordinary Zhengzhou flood of 7/20, 2021: How extreme weather and human response compounding to the disaster. Cities 134, 104168 (2023).
Strauss, B. H. et al. Economic damages from Hurricane Sandy attributable to sea level rise caused by anthropogenic climate change. Nat Commun 12, 2720 (2021).
Lehmkuhl, F. et al. Assessment of the 2021 summer flood in Central Europe. Environ Sci Eur 34, 107 (2022).
Kimutai, J. et al. Climate Change and High Exposure Increased Costs and Disruption to Lives and Livelihoods from Flooding Associated with Exceptionally Heavy Rainfall in Central Europe. http://hdl.handle.net/10044/1/114694, https://doi.org/10.25561/114694 (2024).
Wang, W., Yang, S., Stanley, H. E. & Gao, J. Local floods induce large-scale abrupt failures of road networks. Nat Commun 10, 2114 (2019).
Lin, X., Lu, Q., Chen, L. & Brilakis, I. Assessing dynamic congestion risks of flood-disrupted transportation network systems through time-variant topological analysis and traffic demand dynamics. Advanced Engineering Informatics 62, 102672 (2024).
Banik, S. & Vanajakshi, L. Impact of Rainfall on Traffic Mobility and Reliability Under Indian Traffic Conditions. Transp. in Dev. Econ. 10, 29 (2024).
Gao, W., Hu, X. & Wang, N. Resilience analysis in road traffic systems to rainfall events: Road environment perspective. Transportation Research Part D: Transport and Environment 126, 104000 (2024).
Jagadish, H. V. et al. Big data and its technical challenges. Commun. ACM 57, 86–94 (2014).
Li, Y., Yu, R., Shahabi, C. & Liu, Y. Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting. in (2018).
Liang, Y. et al. BasicTS: An Open Source Fair Multivariate Time Series Prediction Benchmark. in Benchmarking, Measuring, and Optimizing (eds. Gainaru, A., Zhang, C. & Luo, C.) 87–101, https://doi.org/10.1007/978-3-031-31180-2_6 (Springer International Publishing, Cham, 2023).
Loder, A., Ambühl, L., Menendez, M. & Axhausen, K. W. UTD19: Understanding traffic capacity of urban networks. Institute for Transport Planning and Systems, ETH Zurich, https://doi.org/10.3929/ethz-b-000437802 (2020).
Thorndahl, S. et al. Weather radar rainfall data in urban hydrology. Hydrology and Earth System Sciences 21, 1359–1380 (2016).
Hersbach, H. et al. The ERA5 global reanalysis. Quarterly Journal of the Royal Meteorological Society 146, 1999–2049 (2020).
Li, B. et al. High-resolution multi-source traffic data in New Zealand. Sci Data 11, 1216 (2024).
OpenStreetMap Contributor. Open Street Map. Planet dump retrieved from https://www.openstreetmap.org/ (2017).
Biçici, S. & Zeybek, M. Improvements on Road Centerline Extraction by Combining Voronoi Diagram and Intensity Feature from 3D UAV-Based Point Cloud. in Innovations in Smart Cities Applications Volume 5 (eds. Ben Ahmed, M., Boudhir, A. A., Karaș, İ. R., Jain, V. & Mellouli, S.) 935–944, https://doi.org/10.1007/978-3-030-94191-8_76 (Springer International Publishing, Cham, 2022).
Saalfeld, A. Topologically Consistent Line Simplification with the Douglas-Peucker Algorithm. Cartography and Geographic Information Science 26, 7–18 (1999).
Lin, X. & Lu, Q. IUTF Dataset(Enhanced): Enabling Cross-Border Resource for Analysing the Impact of Rainfall on Urban Transportation Systems, https://doi.org/10.6084/m9.figshare.30022807.v1 (2025).
Abatzoglou, J. T., Dobrowski, S. Z., Parks, S. A. & Hegewisch, K. C. TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958–2015. Sci Data 5, 170191 (2018).
Met Office. UK and regional series. Met Office https://www.metoffice.gov.uk/research/climate/maps-and-data/uk-and-regional-series (2023).
