{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T04:45:32Z","timestamp":1775796332339,"version":"3.50.1"},"reference-count":46,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2024,2,16]],"date-time":"2024-02-16T00:00:00Z","timestamp":1708041600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Smart Cities"],"abstract":"<jats:p>Flooding in urban areas is expected to become even more common due to climatic changes, putting pressure on cities to implement effective response measures. Practical mechanisms for assessing flood risk have become highly desired, but existing solutions have been devoted to evaluating only specific cities and consider only limited risk perspectives, constraining their general applicability. This article presents an innovative approach for assessing the flood risk of delimited urban areas by exploiting geospatial information from publicly available databases, providing a method that is applicable to any city in the world and requiring minimum configurations. A set of mathematical equations is defined for numerically assessing risk levels based on elevation, slope, and proximity to rivers, while the existence of emergency-related urban infrastructure is considered as a risk reduction factor. Then, computed risk levels are used to classify areas, allowing easy visualisation of flood risk for a city. This smart city approach not only serves as a valuable tool for assessing the expected flood risk based on different parameters but also facilitates the implementation of cutting-edge strategies to effectively mitigate critical situations, ultimately enhancing urban resilience to flood-related disaster.<\/jats:p>","DOI":"10.3390\/smartcities7010027","type":"journal-article","created":{"date-parts":[[2024,2,16]],"date-time":"2024-02-16T08:02:17Z","timestamp":1708070537000},"page":"662-679","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Flood-Resilient Smart Cities: A Data-Driven Risk Assessment Approach Based on Geographical Risks and Emergency Response Infrastructure"],"prefix":"10.3390","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3507-8249","authenticated-orcid":false,"given":"Jo\u00e3o Paulo Just","family":"Peixoto","sequence":"first","affiliation":[{"name":"IFBA, Federal Institute of Education, Science and Technology of Bahia, 40301-015 Valen\u00e7a, Brazil"},{"name":"PPGM-UEFS, State Universisty of Feira de Santana, 44036-900 Feira de Santana, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3988-8476","authenticated-orcid":false,"given":"Daniel G.","family":"Costa","sequence":"additional","affiliation":[{"name":"SYSTEC-ARISE, Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6386-9753","authenticated-orcid":false,"given":"Paulo","family":"Portugal","sequence":"additional","affiliation":[{"name":"SYSTEC-ARISE, Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3115-0901","authenticated-orcid":false,"given":"Francisco","family":"Vasques","sequence":"additional","affiliation":[{"name":"INEGI, Faculty of Engineering, University of Porto, 4169-007 Porto, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2024,2,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"103842","DOI":"10.1016\/j.ijdrr.2023.103842","article-title":"A dynamic emergency decision support model for emergencies in urban areas","volume":"95","author":"Meng","year":"2023","journal-title":"Int. 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