{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T22:53:30Z","timestamp":1775775210118,"version":"3.50.1"},"reference-count":53,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2024,6,27]],"date-time":"2024-06-27T00:00:00Z","timestamp":1719446400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key R&amp;D Program of China","doi-asserted-by":"publisher","award":["2022YFF0711601"],"award-info":[{"award-number":["2022YFF0711601"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key R&amp;D Program of China","doi-asserted-by":"publisher","award":["XDA23100103"],"award-info":[{"award-number":["XDA23100103"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Strategic Priority Research Program of the Chinese Academy of Sciences","award":["2022YFF0711601"],"award-info":[{"award-number":["2022YFF0711601"]}]},{"name":"Strategic Priority Research Program of the Chinese Academy of Sciences","award":["XDA23100103"],"award-info":[{"award-number":["XDA23100103"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>Natural disasters pose serious threats to human survival. With global warming, disaster chains related to extreme weather are becoming more common, making it increasingly urgent to understand the relationships between different types of natural disasters. However, there remains a lack of research on the frequent spatial-temporal intervals between different disaster events. In this study, we utilize textual records of natural disaster events to mine frequent spatial-temporal patterns of disasters in China. We first transform the discrete spatial-temporal disaster events into a graph structure. Due to the limit of computing power, we reduce the number of edges in the graph based on domain expertise. We then apply the GraMi frequent subgraph mining algorithm to the spatial-temporal disaster event graph, and the results reveal frequent spatial-temporal intervals between disasters and reflect the spatial-temporal changing pattern of disaster interactions. For example, the pattern of sandstorms happening after gales is mainly concentrated within 50 km and rarely happens at farther spatial distances, and the most common temporal interval is 1 day. The statistical results of this study provide data support for further understanding disaster association patterns and offer decision-making references for disaster prevention efforts.<\/jats:p>","DOI":"10.3390\/info15070372","type":"journal-article","created":{"date-parts":[[2024,6,27]],"date-time":"2024-06-27T11:19:02Z","timestamp":1719487142000},"page":"372","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Mining Spatial-Temporal Frequent Patterns of Natural Disasters in China Based on Textual Records"],"prefix":"10.3390","volume":"15","author":[{"given":"Aiai","family":"Han","sequence":"first","affiliation":[{"name":"State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wen","family":"Yuan","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wu","family":"Yuan","sequence":"additional","affiliation":[{"name":"School of Computer Science, Beijing Institute of Technology, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianwen","family":"Zhou","sequence":"additional","affiliation":[{"name":"Max-Planck-Institut f\u00fcr Radioastronomie, 53121 Bonn, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xueyan","family":"Jian","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rong","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinqi","family":"Gao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,6,27]]},"reference":[{"key":"ref_1","unstructured":"(2024, March 14). China Climate Bulletin 2021, Available online: https:\/\/www.cma.gov.cn\/zfxxgk\/gknr\/qxbg\/202203\/t20220308_4568477.html."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"458","DOI":"10.1038\/d41586-018-06783-6","article-title":"How do natural hazards cascade to cause disasters?","volume":"561","author":"AghaKouchak","year":"2018","journal-title":"Nature"},{"key":"ref_3","first-page":"1","article-title":"Landslide disaster genesis pattern in Enshi area, Hubei","volume":"28","author":"Peng","year":"2017","journal-title":"Chin. J. Geol. Hazard Control"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Xu, J., Bai, D., He, H., Luo, J., and Lu, G. (2022). Disaster Precursor Identification and Early Warning of the Lishanyuan Landslide Based on Association Rule Mining. Appl. Sci., 12.","DOI":"10.3390\/app122412836"},{"key":"ref_5","first-page":"287","article-title":"Research on global drought disaster chain analysis based on EM-DAT data","volume":"21","author":"Fu","year":"2023","journal-title":"J. China Inst. Water Resour. Hydropower Res."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"04018006","DOI":"10.1061\/(ASCE)NH.1527-6996.0000291","article-title":"Analyzing Spatial-Temporal Distribution of Natural Hazards in China by Mining News Sources","volume":"19","author":"Liu","year":"2018","journal-title":"Nat. Hazards Rev."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1881","DOI":"10.1007\/s11069-023-06097-5","article-title":"Analysis of Spatial and Temporal Characteristics of Major Natural Disasters in China from 2008 to 2021 Based on Mining News Database","volume":"118","author":"Yang","year":"2023","journal-title":"Nat. Hazards"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"629","DOI":"10.5194\/nhess-16-629-2016","article-title":"Hazard Interaction Analysis for Multi-Hazard Risk Assessment: A Systematic Classification Based on Hazard-Forming Environment","volume":"16","author":"Liu","year":"2016","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2003","DOI":"10.1007\/s11069-020-04259-3","article-title":"A Review of the Research into the Relations between Hazards in Multi-Hazard Risk Analysis","volume":"104","author":"Wang","year":"2020","journal-title":"Nat. Hazards"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/S1872-5791(08)60001-9","article-title":"Preliminary Study on Geological Hazard Chains","volume":"14","author":"Han","year":"2007","journal-title":"Earth Sci. Front."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Van Asch, T., Corominas, J., Greiving, S., Malet, J.-P., and Sterlacchini, S. (2014). Medium-Scale Multi-Hazard Risk Assessment of Gravitational Processes. Mountain Risks: From Prediction to Management and Governance, Springer.","DOI":"10.1007\/978-94-007-6769-0"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"2108","DOI":"10.1007\/s11629-020-6513-5","article-title":"A Catastrophic Natural Disaster Chain of Typhoon-Rainstorm-Landslide-Barrier Lake-Flooding in Zhejiang Province, China","volume":"18","author":"Cui","year":"2021","journal-title":"J. Mt. Sci."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"100545","DOI":"10.1016\/j.wace.2022.100545","article-title":"Flash Floods and Landslides in the City of Recife, Northeast Brazil after Heavy Rain on May 25\u201328, 2022: Causes, Impacts, and Disaster Preparedness","volume":"39","author":"Marengo","year":"2023","journal-title":"Weather Clim. Extrem."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1859","DOI":"10.5194\/nhess-15-1859-2015","article-title":"Flash Flood Occurrence and Relation to the Rainfall Hazard in a Highly Urbanized Area","volume":"15","author":"Papagiannaki","year":"2015","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"869","DOI":"10.2166\/nh.2023.022","article-title":"Probabilistic Analysis on the Influences of Heatwaves during the Onset of Flash Droughts over China","volume":"54","author":"Zhang","year":"2023","journal-title":"Hydrol. Res."},{"key":"ref_16","first-page":"1","article-title":"FPGA\/GPU-Based Acceleration for Frequent Itemsets Mining: A Comprehensive Review","volume":"54","author":"Cumplido","year":"2022","journal-title":"ACM Comput. Surv."},{"key":"ref_17","unstructured":"Agrawal, R., and Ramakrishnan, S. (1994, January 12\u201315). Fast algorithms for mining association rules in large databases. Proceedings of the 20th International Conference on Very Large Data Bases (VLDB\u201994), Santiago de Chile, Chile."},{"key":"ref_18","first-page":"1","article-title":"Mining Frequent Patterns without Candidate Generation","volume":"29","author":"Han","year":"2000","journal-title":"SIGMOD Rec. (ACM Spec. Interes. Gr. Manag. Data)"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Zhang, Z., and Wu, W. (2008, January 26\u201328). Composite spatio-temporal co-occurrence pattern mining. Proceedings of the Wireless Algorithms, Systems, and Applications, Dallas, TX, USA.","DOI":"10.1007\/978-3-540-88582-5_43"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Alatrista Salas, H., Bringay, S., Flouvat, F., Selmaoui-Folcher, N., and Teisseire, M. (2012, January 29). The Pattern Next Door: Towards Spatio-Sequential Pattern Discovery. Proceedings of the Advances in Knowledge Discovery and Data Mining, Kuala Lumpur, Malaysia.","DOI":"10.1007\/978-3-642-30220-6_14"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3161602","article-title":"Spatio-Temporal Data Mining: A Survey of Problems and Methods","volume":"51","author":"Atluri","year":"2018","journal-title":"ACM Comput. Surv."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2306","DOI":"10.3390\/ijgi4042306","article-title":"Spatiotemporal Data Mining: A Computational Perspective","volume":"4","author":"Shekhar","year":"2015","journal-title":"ISPRS Int. J. Geo-Inf."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Wang, X., Wang, J., Wang, L., Wang, S., and Ding, L. (2022, January 1\u20133). TCPMS-FCP: A Traffic Congestion Pattern Mining System Based on Spatio-Temporal Fuzzy Co-Location Patterns. Proceedings of the Web Information Systems Engineering\u2014WISE 2022, Biarritz, France.","DOI":"10.1007\/978-3-031-20891-1_47"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2818251","DOI":"10.1155\/2018\/2818251","article-title":"A MapReduce-Based Parallel Frequent Pattern Growth Algorithm for Spatiotemporal Association Analysis of Mobile Trajectory Big Data","volume":"2018","author":"Xia","year":"2018","journal-title":"Complexity"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"102692","DOI":"10.1016\/j.jnca.2020.102692","article-title":"MARIO: A Spatio-Temporal Data Mining Framework on Google Cloud to Explore Mobility Dynamics from Taxi Trajectories","volume":"164","author":"Ghosh","year":"2020","journal-title":"J. Netw. Comput. Appl."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1007\/s10115-014-0750-2","article-title":"Partial Spatio-Temporal Co-Occurrence Pattern Mining","volume":"44","author":"Celik","year":"2015","journal-title":"Knowl. Inf. Syst."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-020-74248-w","article-title":"Discovering Spatial Interaction Patterns of near Repeat Crime by Spatial Association Rules Mining","volume":"10","author":"He","year":"2020","journal-title":"Sci. Rep."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Aydin, B., and Angryk, R. (2015, January 14\u201317). Spatiotemporal Frequent Pattern Mining on Solar Data: Current Algorithms and Future Directions. Proceedings of the 15th IEEE International Conference on Data Mining Workshop (ICDMW), Atlantic City, NJ, USA.","DOI":"10.1109\/ICDMW.2015.10"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Vega-Oliveros, D.A., Cotacallapa, M., Ferreira, L.N., Quiles, M.G., Zhao, L., Macau, E.E.N., and Cardoso, M.F. (2019, January 8\u201312). From Spatio-Temporal Data to Chronological Networks: An Application to Wildfire Analysis. Proceedings of the 34th ACM\/SIGAPP Symposium on Applied Computing, Limassol, Cyprus.","DOI":"10.1145\/3297280.3299802"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41467-020-17634-2","article-title":"Spatiotemporal Data Analysis with Chronological Networks","volume":"11","author":"Ferreira","year":"2020","journal-title":"Nat. Commun."},{"key":"ref_31","unstructured":"Oberoi, K.S., and del Mondo, G. (2021, January 5\u20137). Graph-Based Pattern Detection in Spatio-Temporal Phenomena. Proceedings of the 16th Spatial Analysis and Geomatics Conference (SAGEO 2021), La Rochelle, France."},{"key":"ref_32","first-page":"800","article-title":"AirVis: Visual Analytics of Air Pollution Propagation","volume":"26","author":"Deng","year":"2020","journal-title":"IEEE Trans. Vis. Comput. Graph."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1936","DOI":"10.1080\/13658816.2019.1599124","article-title":"Frequent Subgraph Mining in Oceanographic Multi-Level Directed Graphs","volume":"33","author":"Petelin","year":"2019","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"104391","DOI":"10.1016\/j.tourman.2021.104391","article-title":"Application of Graph Theory to Mining the Similarity of Travel Trajectories","volume":"87","author":"Park","year":"2021","journal-title":"Tour. Manag."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1016\/j.ins.2022.07.046","article-title":"A Graph Based Approach for Mining Significant Places in Trajectory Data","volume":"609","author":"Wang","year":"2022","journal-title":"Inf. Sci."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"2467","DOI":"10.1016\/j.procs.2023.10.238","article-title":"Modeling Complex Object Changes in Satellite Image Time-Series: Approach Based on CSP and Spatiotemporal Graphs","volume":"225","author":"Ayadi","year":"2023","journal-title":"Procedia Comput. Sci."},{"key":"ref_37","first-page":"2342","article-title":"Multi-model fusion extraction method for chinese text implicative meteorological disasters event information","volume":"24","author":"Hu","year":"2022","journal-title":"J. Geoinfo. Sci."},{"key":"ref_38","unstructured":"(2024, May 28). School of Computer Science and Technology, BIT, Yuan Wu. Available online: https:\/\/cs.bit.edu.cn\/szdw\/jsml\/fjs\/yw\/index.htm."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Cui, Y., Che, W., Liu, T., Qin, B., Wang, S., and Hu, G. (2020, January 16\u201320). Revisiting Pre-Trained Models for Chinese Natural Language Processing. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Findings, Online.","DOI":"10.18653\/v1\/2020.findings-emnlp.58"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"680","DOI":"10.1002\/2013RG000445","article-title":"Reviewing and visualizing the interactions of natural hazards","volume":"52","author":"Gill","year":"2014","journal-title":"Rev. Geophys."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"2503","DOI":"10.28991\/CEJ-2023-09-10-010","article-title":"Modelling Flood Wave Propagation as a Result of Dam Piping Failure Using 2D-HEC-RAS","volume":"9","author":"Mohamed","year":"2023","journal-title":"Civ. Eng. J."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1","DOI":"10.55599\/ejssm.v7i6.42","article-title":"Tropical Cyclone Tornadoes: A Review of Knowledge in Research and Prediction","volume":"7","author":"Edwards","year":"2021","journal-title":"E-J. Sev. Storms Meteorol."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1146\/annurev-publhealth-071421-051636","article-title":"Public Health Implications of Drought in a Climate Change Context: A Critical Review","volume":"44","author":"Salvador","year":"2023","journal-title":"Annu. Rev. Public Health"},{"key":"ref_44","unstructured":"Al-Dousari, A., and Hashmi, M.Z. (2023). Sources, Drivers, and Impacts of Sand and Dust Storms: A Global View. Dust and Health: Challenges and Solutions, Springer International Publishing."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1016\/j.earscirev.2015.04.002","article-title":"Southern North Sea Storm Surge Event of 5 December 2013: Water Levels, Waves and Coastal Impacts","volume":"146","author":"Spencer","year":"2015","journal-title":"Earth-Sci. Rev."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"517","DOI":"10.14778\/2732286.2732289","article-title":"GRAMI: Frequent Subgraph and Pattern Mining in a Single Large Graph","volume":"7","author":"Elseidy","year":"2014","journal-title":"Proc. VLDB Endow."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1007\/978-3-540-24775-3_5","article-title":"Discriminative Methods for Multi-Labeled Classification","volume":"3056","author":"Godbole","year":"2004","journal-title":"Adv. Knowl. Discov. Data Mining."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"2607","DOI":"10.1007\/s11069-014-1446-3","article-title":"Spatial and Temporal Changes of Meteorological Disasters in China during 1950\u20132013","volume":"75","author":"Guan","year":"2015","journal-title":"Nat. Hazards"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"827","DOI":"10.1007\/s11069-021-04858-8","article-title":"Meteorological Disaster Frequency at Prefecture-Level City Scale and Induced Losses in Mainland China during 2011\u20132019","volume":"109","author":"Xu","year":"2021","journal-title":"Nat. Hazards"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"2011","DOI":"10.1007\/s11069-023-06108-5","article-title":"Evolution Characteristics of the Rainstorm Disaster Chains in the Guangdong\u2013Hong Kong\u2013Macao Greater Bay Area, China","volume":"119","author":"Wang","year":"2023","journal-title":"Nat. Hazards"},{"key":"ref_51","first-page":"233","article-title":"Spatial and Temporal Characteristics of Four Main Types of Meteorological Disasters in East China","volume":"33","author":"Shi","year":"2020","journal-title":"Atmosfera"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"757","DOI":"10.1002\/hyp.1365","article-title":"Distributed Simulations of Landslides for Different Rainfall Conditions","volume":"18","author":"Dhakal","year":"2004","journal-title":"Hydrol. Process."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1007\/s10064-022-02763-3","article-title":"Rainstorm-Induced Large-Scale Landslides in Northeastern Chongqing, China, August 31 to September 2, 2014","volume":"81","author":"Li","year":"2022","journal-title":"Bull. Eng. Geol. Environ."}],"container-title":["Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2078-2489\/15\/7\/372\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T15:06:32Z","timestamp":1760108792000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2078-2489\/15\/7\/372"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,6,27]]},"references-count":53,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2024,7]]}},"alternative-id":["info15070372"],"URL":"https:\/\/doi.org\/10.3390\/info15070372","relation":{},"ISSN":["2078-2489"],"issn-type":[{"value":"2078-2489","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,6,27]]}}}