{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T19:34:46Z","timestamp":1743104086991,"version":"3.40.3"},"publisher-location":"Cham","reference-count":29,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030461393"},{"type":"electronic","value":"9783030461409"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-46140-9_23","type":"book-chapter","created":{"date-parts":[[2020,4,22]],"date-time":"2020-04-22T07:03:10Z","timestamp":1587538990000},"page":"239-251","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A Place to Go: Locating Damaged Regions After Natural Disasters Through Mobile Phone Data"],"prefix":"10.1007","author":[{"given":"Galo","family":"Castillo-L\u00f3pez","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mar\u00eda-Bel\u00e9n","family":"Guaranda","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fabricio","family":"Layedra","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Carmen","family":"Vaca","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,4,23]]},"reference":[{"key":"23_CR1","doi-asserted-by":"crossref","unstructured":"Andrade, X., Layedra, F., Vaca, C., Cruz, E.: RiSC: quantifying change after natural disasters to estimate infrastructure damage with mobile phone data. In: 2018 IEEE International Conference on Big Data (Big Data), pp. 3383\u20133391. IEEE (2018)","DOI":"10.1109\/BigData.2018.8622374"},{"key":"23_CR2","unstructured":"Ashktorab, Z., Brown, C., Nandi, M., Culotta, A.: Tweedr: mining twitter to inform disaster response. In: ISCRAM (2014)"},{"key":"23_CR3","unstructured":"CDB: CDB, World Bank partner to increase disaster resilience through improved procurement (2018). https:\/\/www.caribank.org\/newsroom\/news-and-events\/cdb-world-bank-partner-increase-disaster-resilience-through-improved-procurement"},{"key":"23_CR4","unstructured":"The World Bank: Disaster risk management (2019). https:\/\/www.worldbank.org\/en\/topic\/disasterriskmanagement\/overview"},{"issue":"S2","key":"23_CR5","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1080\/13632460802013511","volume":"12","author":"OD Cardona","year":"2008","unstructured":"Cardona, O.D., Ordaz, M.G., Marulanda, M.C., Barbat, A.H.: Estimation of probabilistic seismic losses and the public economic resilience\u2014an approach for a macroeconomic impact evaluation. J. Earthq. Eng. 12(S2), 60\u201370 (2008)","journal-title":"J. Earthq. Eng."},{"key":"23_CR6","doi-asserted-by":"crossref","unstructured":"Castillo, G., Layedra, F., Guaranda, M.B., Lara, P., Vaca, C.: The silence of the cantons: estimating villages socioeconomic status through mobile phones data. In: 2018 International Conference on eDemocracy & eGovernment (ICEDEG), pp. 172\u2013178. IEEE (2018)","DOI":"10.1109\/ICEDEG.2018.8372308"},{"key":"23_CR7","unstructured":"Cerutti, V., Fuchs, G., Andrienko, G., Andrienko, N., Ostermann, F.: Identification of disaster-affected areas using exploratory visual analysis of georeferenced tweets: application to a flood event. Association of Geographic Information Laboratories in Europe, Helsinki, Finland, p. 5 (2016)"},{"key":"23_CR8","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"250","DOI":"10.1007\/978-3-319-26187-4_21","volume-title":"Web Information Systems Engineering \u2013 WISE 2015","author":"S Cresci","year":"2015","unstructured":"Cresci, S., Cimino, A., Dell\u2019Orletta, F., Tesconi, M.: Crisis mapping during natural disasters via text analysis of social media messages. In: Wang, J., et al. (eds.) WISE 2015. LNCS, vol. 9419, pp. 250\u2013258. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-26187-4_21"},{"issue":"4","key":"23_CR9","doi-asserted-by":"publisher","first-page":"667","DOI":"10.1080\/13658816.2014.996567","volume":"29","author":"JP De Albuquerque","year":"2015","unstructured":"De Albuquerque, J.P., Herfort, B., Brenning, A., Zipf, A.: A geographic approach for combining social media and authoritative data towards identifying useful information for disaster management. Int. J. Geogr. Inf. Sci. 29(4), 667\u2013689 (2015)","journal-title":"Int. J. Geogr. Inf. Sci."},{"issue":"6","key":"23_CR10","doi-asserted-by":"publisher","first-page":"1087","DOI":"10.5194\/nhess-15-1087-2015","volume":"15","author":"J Fernandez Galarreta","year":"2015","unstructured":"Fernandez Galarreta, J., Kerle, N., Gerke, M.: UAV-based urban structural damage assessment using object-based image analysis and semantic reasoning. Nat. Hazards Earth Syst. Sci. 15(6), 1087\u20131101 (2015)","journal-title":"Nat. Hazards Earth Syst. Sci."},{"issue":"S1","key":"23_CR11","doi-asserted-by":"publisher","first-page":"S179","DOI":"10.1193\/1.3636416","volume":"27","author":"S Ghosh","year":"2011","unstructured":"Ghosh, S., et al.: Crowdsourcing for rapid damage assessment: the global earth observation catastrophe assessment network (GEO-CAN). Earthq. Spectra 27(S1), S179\u2013S198 (2011)","journal-title":"Earthq. Spectra"},{"key":"23_CR12","doi-asserted-by":"crossref","unstructured":"Gil, H.A.P.: Efectos del sismo del 16 de abril de 2016 en el sector productivo agropecuario de manab\u00ed. La T\u00e9cnica (17), 30\u201342 (2017)","DOI":"10.33936\/la_tecnica.v0i17.692"},{"key":"23_CR13","unstructured":"Giugale, M.: Time to insure developing countries against natural disasters (2017). https:\/\/www.worldbank.org\/en\/news\/opinion\/2017\/10\/11\/time-to-insure-developing-countries-against-natural-disasters"},{"key":"23_CR14","unstructured":"Gr\u00fcnthal, G.: European macroseismic scale 1998. Technical report, European Seismological Commission (ESC) (1998)"},{"key":"23_CR15","unstructured":"Guha-Sapir, D., Hargitt, D., Hoyois, P.: Thirty years of natural disasters 1974\u20132003: the numbers. Presses univ. de Louvain (2004)"},{"key":"23_CR16","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1016\/j.wace.2015.10.002","volume":"11","author":"P Hoeppe","year":"2016","unstructured":"Hoeppe, P.: Trends in weather related disasters-consequences for insurers and society. Weather Clim. Extremes 11, 70\u201379 (2016)","journal-title":"Weather Clim. Extremes"},{"issue":"1","key":"23_CR17","doi-asserted-by":"publisher","first-page":"297","DOI":"10.1146\/annurev-resource-073009-104211","volume":"3","author":"D Kellenberg","year":"2011","unstructured":"Kellenberg, D., Mobarak, A.M.: The economics of natural disasters. Annu. Rev. Resour. Econ. 3(1), 297\u2013312 (2011)","journal-title":"Annu. Rev. Resour. Econ."},{"issue":"3","key":"23_CR18","doi-asserted-by":"publisher","first-page":"e1500779","DOI":"10.1126\/sciadv.1500779","volume":"2","author":"Y Kryvasheyeu","year":"2016","unstructured":"Kryvasheyeu, Y., et al.: Rapid assessment of disaster damage using social media activity. Sci. Adv. 2(3), e1500779 (2016)","journal-title":"Sci. Adv.."},{"key":"23_CR19","doi-asserted-by":"crossref","unstructured":"MacEachren, A.M., et al.: SensePlace2: GeoTwitter analytics support for situational awareness. In: 2011 IEEE Conference on Visual Analytics Science and Technology (VAST), pp. 181\u2013190. IEEE (2011)","DOI":"10.1109\/VAST.2011.6102456"},{"issue":"8","key":"23_CR20","doi-asserted-by":"publisher","first-page":"1272","DOI":"10.3390\/rs10081272","volume":"10","author":"S Olen","year":"2018","unstructured":"Olen, S., Bookhagen, B.: Mapping damage-affected areas after natural hazard events using sentinel-1 coherence time series. Remote Sens. 10(8), 1272 (2018)","journal-title":"Remote Sens."},{"key":"23_CR21","doi-asserted-by":"publisher","first-page":"104","DOI":"10.1016\/j.apgeog.2017.09.004","volume":"88","author":"S Oliveira","year":"2017","unstructured":"Oliveira, S., Z\u00eazere, J.L., Queir\u00f3s, M., Pereira, J.M.: Assessing the social context of wildfire-affected areas. The case of mainland Portugal. Appl. Geogr. 88, 104\u2013117 (2017)","journal-title":"Appl. Geogr."},{"key":"23_CR22","unstructured":"Pastor-Escuredo, D., Torres, Y., Martinez, M., Zufiria, P.J.: Floods impact dynamics quantified from big data sources. arXiv preprint arXiv:1804.09129 (2018)"},{"issue":"3","key":"23_CR23","doi-asserted-by":"crossref","first-page":"148","DOI":"10.4103\/picr.PICR_87_17","volume":"8","author":"P Ranganathan","year":"2017","unstructured":"Ranganathan, P., Pramesh, C., Aggarwal, R.: Common pitfalls in statistical analysis: logistic regression. Perspect. Clin. Res. 8(3), 148 (2017)","journal-title":"Perspect. Clin. Res."},{"issue":"1","key":"23_CR24","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1007\/s11069-017-2755-0","volume":"87","author":"JF Rosser","year":"2017","unstructured":"Rosser, J.F., Leibovici, D.G., Jackson, M.J.: Rapid flood inundation mapping using social media, remote sensing and topographic data. Nat. Hazards 87(1), 103\u2013120 (2017). https:\/\/doi.org\/10.1007\/s11069-017-2755-0","journal-title":"Nat. Hazards"},{"key":"23_CR25","unstructured":"Schlein, L.: UN: most deaths from natural disasters occur in poor countries (2016). https:\/\/www.voanews.com\/a\/un-says-most-deaths-from-natural-disasters-occur-in-poor-countries\/3548871.html"},{"key":"23_CR26","doi-asserted-by":"crossref","unstructured":"Wilson, R., et al.: Rapid and near real-time assessments of population displacement using mobile phone data following disasters: the 2015 Nepal eEarthquake. PLoS Curr. 8 (2016)","DOI":"10.1371\/currents.dis.d073fbece328e4c39087bc086d694b5c"},{"issue":"2","key":"23_CR27","doi-asserted-by":"publisher","first-page":"287","DOI":"10.20965\/jdr.2017.p0287","volume":"12","author":"T Yabe","year":"2017","unstructured":"Yabe, T., Sekimoto, Y., Sudo, A., Tsubouchi, K.: Predicting delay of commuting activities following frequently occurring disasters using location data from smartphones. J. Disaster Res. 12(2), 287\u2013295 (2017)","journal-title":"J. Disaster Res."},{"issue":"5","key":"23_CR28","doi-asserted-by":"publisher","first-page":"165","DOI":"10.3390\/geosciences8050165","volume":"8","author":"M Yu","year":"2018","unstructured":"Yu, M., Yang, C., Li, Y.: Big data in natural disaster management: a review. Geosciences 8(5), 165 (2018)","journal-title":"Geosciences"},{"key":"23_CR29","doi-asserted-by":"publisher","first-page":"758","DOI":"10.1016\/j.ijdrr.2018.02.003","volume":"28","author":"F Yuan","year":"2018","unstructured":"Yuan, F., Liu, R.: Feasibility study of using crowdsourcing to identify critical affected areas for rapid damage assessment: Hurricane Matthew case study. Int. J. Disaster Risk Reduction 28, 758\u2013767 (2018)","journal-title":"Int. J. Disaster Risk Reduction"}],"container-title":["Communications in Computer and Information Science","Information Management and Big Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-46140-9_23","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,4]],"date-time":"2024-08-04T11:55:32Z","timestamp":1722772532000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-46140-9_23"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030461393","9783030461409"],"references-count":29,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-46140-9_23","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"23 April 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SIMBig","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Annual International Symposium on Information Management and Big Data","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Lima","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Peru","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 August 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 August 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"simbig2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/simbig.org\/SIMBig2019\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"104","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"15","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"16","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"14% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}