Using human mobility data to detect evacuation patterns in hurricane Ian

References

• Adeola, F. O. 2009. “Katrina Cataclysm: Does Duration of Residency and Prior Experience Affect Impacts, Evacuation, and Adaptation Behavior Among Survivors?” Environment and Behavior 41 (4): 459–489. https://doi.org/10.1177/0013916508316651.
   Web of Science ®Google Scholar
• Aktay, A., S. Bavadekar, G. Cossoul, J. Davis, D. Desfontaines, A. Fabrikant, E. Gabrilovich, K. Gadepalli, B. Gipson, and M. Guevara. 2020. Google COVID-19 Community Mobility Reports: Anonymization Process Description (Version 1.1). arXiv preprint arXiv:2004.04145.
   Google Scholar
• Alessandretti, L. 2022. “What Human Mobility Data Tell Us About COVID-19 Spread.” Nature Reviews Physics 4 (1): 12–13. https://doi.org/10.1038/s42254-021-00407-1.
   PubMedGoogle Scholar
• Apte, A. 2010. “Humanitarian Logistics: A New Field of Research and Action.” Foundations and trends® in Technology, Information and Operations Management 3 (1): 1–100. https://doi.org/10.1561/0200000014.
   Google Scholar
• Baker, E. J. 1979. “Predicting Response to Hurricane Warnings-Reanalysis of Data from 4 Studies.” Mass emergencies 4 (1): 9–24.
   Google Scholar
• Baker, E. J. 1991. “Hurricane Evacuation Behavior.” International Journal of Mass Emergencies & Disasters 9 (2): 287–310. https://doi.org/10.1177/028072709100900210.
   Google Scholar
• Baker, E. J. 1995. “Public Response to Hurricane Probability Forecasts.” The Professional Geographer 47 (2): 137–147. https://doi.org/10.1111/j.0033-0124.1995.00137.x.
   Web of Science ®Google Scholar
• Baker, E. J. 2009. “Acquiring Data on Travel Behaviour During Emergencies and Exceptional Events.”Transport Survey Methods: Keeping Up with a Changing World, edited by P. Bonnel, M. Lee-Gosselin, J. Zmud, and J.-L. Madre, 197–211. Leeds, UK: Emerald Group Publishing Limited.
   Google Scholar
• Beven, J. L., L. A. Avila, E. S. Blake, D. P. Brown, J. L. Franklin, R. D. Knabb, R. J. Pasch, J. R. Rhome, and S. R. Stewart. 2008. “Atlantic Hurricane Season of 2005.” Monthly Weather Review 136 (3): 1109–1173. https://doi.org/10.1175/2007MWR2074.1.
   Web of Science ®Google Scholar
• Biemer, P. P., and L. E. Lyberg. 2003. Introduction to Survey Quality. New York, USA: John Wiley & Sons.
   Google Scholar
• Brackenridge, S., L. K. Zottarelli, E. Rider, and B. Carlsen-Landy. 2012. “Dimensions of the Human–Animal Bond and Evacuation Decisions Among Pet Owners During Hurricane Ike.” Anthrozoös 25 (2): 229–238. https://doi.org/10.2752/175303712X13316289505503.
   Web of Science ®Google Scholar
• Brown, S., H. Parton, C. Driver, and C. Norman. 2016. “Evacuation During Hurricane Sandy: Data from a Rapid Community Assessment.” PLoS Currents 8. https://doi.org/10.1371/currents.dis.692664b92af52a3b506483b8550d6368.
   Google Scholar
• Chang, S., E. Pierson, P. W. Koh, J. Gerardin, B. Redbird, D. Grusky, and J. Leskovec. 2021. “Mobility Network Models of COVID-19 Explain Inequities and Inform Reopening.” Nature 589 (7840): 82–87. https://doi.org/10.1038/s41586-020-2923-3.
   PubMed Web of Science ®Google Scholar
• Chaniotakis, E., C. Antoniou, and F. C. Pereira. 2017. “Enhancing Resilience to Disasters Using Social Media.” 2017 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS), June 26–28, 2017, Naples, Italy.
   Google Scholar
• Collins, J., R. Ersing, A. Polen, M. Saunders, and J. Senkbeil. 2018. “The Effects of Social Connections on Evacuation Decision Making During Hurricane Irma.” Weather, Climate, and Society 10 (3): 459–469. https://doi.org/10.1175/WCAS-D-17-0119.1.
   Web of Science ®Google Scholar
• Deng, H., D. P. Aldrich, M. M. Danziger, J. Gao, N. E. Phillips, S. P. Cornelius, and Q. R. Wang. 2021. “High-Resolution Human Mobility Data Reveal Race and Wealth Disparities in Disaster Evacuation Patterns.” Humanities and Social Sciences Communications 8 (1): 144. https://doi.org/10.1057/s41599-021-00824-8.
   Google Scholar
• de Palma, A., S. Vosough, and F. Liao. 2022. “An Overview of Effects of COVID-19 on Mobility and Lifestyle: 18 Months Since the Outbreak.” Transportation Research Part A: Policy and Practice 159:372–397. https://doi.org/10.1016/j.tra.2022.03.024.
   PubMed Web of Science ®Google Scholar
• Dixon, D. S., P. Mozumder, W. F. Vásquez, and H. Gladwin. 2017. “Heterogeneity within and Across Households in Hurricane Evacuation Response.” Networks and Spatial Economics 17 (2): 645–680. https://doi.org/10.1007/s11067-017-9339-0.
   Web of Science ®Google Scholar
• Dow, K., and S. L. Cutter. 2002. “Emerging Hurricane Evacuation Issues: Hurricane Floyd and South Carolina.” Natural Hazards Review 3 (1): 12–18. https://doi.org/10.1061/(ASCE)1527-6988.
   Google Scholar
• Elarde, J., J.-S. Kim, H. Kavak, A. Züfle, T. Anderson, and I. Benenson. 2021. “Change of Human Mobility During COVID-19: A United States Case Study.” PLoS One 16 (11): e0259031. https://doi.org/10.1371/journal.pone.0259031.
   PubMed Web of Science ®Google Scholar
• Ellis, L. A., C. Pomare, K. Churruca, A. Carrigan, I. Meulenbroeks, M. Saba, and J. Braithwaite. 2022. “Predictors of Response Rates of Safety Culture Questionnaires in Healthcare: A Systematic Review and Analysis.” BMJ Open 12 (9): e065320. https://doi.org/10.1136/bmjopen-2022-065320.
   PubMed Web of Science ®Google Scholar
• Elsner, J. B., X. Niu, and T. H. Jagger. 2004. “Detecting Shifts in Hurricane Rates Using a Markov Chain Monte Carlo Approach.” Journal of Climate 17 (13): 2652–2666. https://doi.org/10.1175/1520-0442(2004)017<2652:DSIHRU>2.0.CO;2.
   Web of Science ®Google Scholar
• Esmalian, A., N. Coleman, F. Yuan, X. Xiao, and A. Mostafavi. 2022. “Characterizing Equitable Access to Grocery Stores During Disasters Using Location-Based Data.” Scientific reports 12 (1): 20203. https://doi.org/10.1038/s41598-022-23532-y.
   PubMed Web of Science ®Google Scholar
• Esteban, M., V. P. Valenzuela, N. Y. Yun, T. Mikami, T. Shibayama, R. Matsumaru, H. Takagi, N. D. Thao, M. De Leon, and T. Oyama. 2015. “Typhoon Haiyan 2013 Evacuation Preparations and Awareness.” International Journal of Sustainable Future for Human Security 3 (1): 37–45. https://doi.org/10.24910/jsustain/3.1/3745.
   Google Scholar
• FDEM. (2022). Know Your Zone, Know Your Home. https://www.floridadisaster.org/.
   Google Scholar
• Gao, S., J. Rao, Y. Kang, Y. Liang, and J. Kruse. 2020. “Mapping County-Level Mobility Pattern Changes in the United States in Response to COVID-19.” SIGSpatial Special 12 (1): 16–26. https://doi.org/10.1145/3404820.3404824.
   Google Scholar
• Getis, A., and J. K. Ord. 1992. “The Analysis of Spatial Association by Use of Distance Statistics.” Geographical Analysis 24 (3): 189–206. https://doi.org/10.1111/j.1538-4632.1992.tb00261.x.
   Web of Science ®Google Scholar
• Halverson, J. B. 2018. “The Costliest Hurricane Season in U.S. History.” Weatherwise 71 (2): 20–27. https://doi.org/10.1080/00431672.2018.1416862.
   Google Scholar
• Harris, L. R., and G. T. Brown. 2010. “Mixing Interview and Questionnaire Methods: Practical Problems in Aligning Data.” Practical Assessment, Research & Evaluation 15 (1): 1.
   Google Scholar
• Heckard, D. 2022. Hurricane Ian’s Flooding Nightmare in Central Florida. https://www.news4jax.com/news/2022/10/07/hurricane-ians-flooding-nightmare-in-central-florida/.
   Google Scholar
• Her, P. H., S. Saeed, K. H. Tram, and S. R. Bhatnagar. 2022. “Novel Mobility Index Tracks COVID-19 Transmission Following Stay-At-Home Orders.” Scientific Reports 12 (1): 7654. https://doi.org/10.1038/s41598-022-10941-2.
   PubMed Web of Science ®Google Scholar
• Hong, L., and V. Frias-Martinez. 2020. “Modeling and Predicting Evacuation Flows During Hurricane Irma.” EPJ Data Science 9 (1): 29. https://doi.org/10.1140/epjds/s13688-020-00247-6.
   Web of Science ®Google Scholar
• Ilbeigi, M. 2019. “Statistical Process Control for Analyzing Resilience of Transportation Networks.” International Journal of Disaster Risk Reduction 33:155–161. https://doi.org/10.1016/j.ijdrr.2018.10.002.
   Web of Science ®Google Scholar
• Johnson, D. R., C. P. Scheitle, and E. H. Ecklund. 2021. “Beyond the In-Person Interview? How Interview Quality Varies Across In-Person, Telephone, and Skype Interviews.” Social Science Computer Review 39 (6): 1142–1158. https://doi.org/10.1177/0894439319893612.
   Web of Science ®Google Scholar
• Juhász, L., and H. H. Hochmair. 2020. “Studying Spatial and Temporal Visitation Patterns of Points of Interest Using SafeGraph Data in Florida.” GI_Forum 1:119–136. https://doi.org/10.1553/giscience2020_01_s119.
   Google Scholar
• Kang, Y., S. Gao, Y. Liang, M. Li, J. Rao, and J. Kruse. 2020. “Multiscale Dynamic Human Mobility Flow Dataset in the US During the COVID-19 Epidemic.” Scientific Data 7 (1): 390. https://doi.org/10.1038/s41597-020-00734-5.
   PubMed Web of Science ®Google Scholar
• Kang, J. E., M. K. Lindell, and C. S. Prater. 2007. “Hurricane Evacuation Expectations and Actual Behavior in Hurricane Lili 1.” Journal of Applied Social Psychology 37 (4): 887–903. https://doi.org/10.1111/j.1559-1816.2007.00191.x.
   Web of Science ®Google Scholar
• Karaye, I. M., N. Taylor, M. Perez-Patron, C. Thompson, and J. A. Horney. 2022. “Factors Associated with Hurricane Evacuation: A Statistical Meta-Analysis of Studies, 1999-2018.” Disaster Medicine and Public Health Preparedness 16 (3): 1064–1072. https://doi.org/10.1017/dmp.2021.24.
   PubMed Web of Science ®Google Scholar
• Kendall, L. 2014. “The Conduct of Qualitative Interviews: Research Questions, Methodological Issues, and Researching Online.” In Handbook of Research on New Literacies, edited by J. Coiro, M. Knobel, C. Lankshear, and D. J. Leu, 133–150. New York, USA: Routledge.
   Google Scholar
• Klotzbach, P. J., S. G. Bowen, R. Pielke, and M. Bell. 2018. “Continental US Hurricane Landfall Frequency and Associated Damage: Observations and Future Risks.” Bulletin of the American Meteorological Society 99 (7): 1359–1376. https://doi.org/10.1175/BAMS-D-17-0184.1.
   Web of Science ®Google Scholar
• Knabb, R. D., J. R. Rhome, and D. P. Brown. 2005. Tropical Cyclone Report: Hurricane Katrina, 23–30 August 2005. National Hurricane Center.
   Google Scholar
• Knutson, T. R., J. L. McBride, J. Chan, K. Emanuel, G. Holland, C. Landsea, I. Held, J. P. Kossin, A. K. Srivastava, and M. Sugi. 2010. “Tropical Cyclones and Climate Change.” Nature Geoscience 3 (3): 157–163. https://doi.org/10.1038/ngeo779.
   Web of Science ®Google Scholar
• Kuchler, T., D. Russel, and J. Stroebel. 2020. “The Geographic Spread of COVID-19 Correlates with the Structure of Social Networks As Measured by Facebook.” (w26990): w26990. National Bureau of Economic Research. https://doi.org/10.3386/w26990
   Google Scholar
• Lambert, J. H., A. I. Parlak, Q. Zhou, J. S. Miller, M. D. Fontaine, T. M. Guterbock, J. L. Clements, and S. A. Thekdi. 2013. “Understanding and Managing Disaster Evacuation on a Transportation Network.” Accident Analysis & Prevention 50:645–658. https://doi.org/10.1016/j.aap.2012.06.015.
   PubMed Web of Science ®Google Scholar
• Lazo, J. K., A. Bostrom, R. E. Morss, J. L. Demuth, and H. Lazrus. 2015. “Factors Affecting Hurricane Evacuation Intentions.” Risk Analysis: An Official Publication of the Society for Risk Analysis 35 (10): 1837–1857. https://doi.org/10.1111/risa.12407.
   PubMed Web of Science ®Google Scholar
• Levin, R., D. L. Chao, E. A. Wenger, and J. L. Proctor. 2021. “Insights into Population Behavior During the COVID-19 Pandemic from Cell Phone Mobility Data and Manifold Learning.” Nature Computational Science 1 (9): 588–597. https://doi.org/10.1038/s43588-021-00125-9.
   PubMedGoogle Scholar
• Li, X., X. Huang, D. Li, and Y. Xu. 2022. “Aggravated Social Segregation During the COVID-19 Pandemic: Evidence from Crowdsourced Mobility Data in Twelve Most Populated U.S. Metropolitan Areas.” Sustainable Cities and Society 81:103869. https://doi.org/10.1016/j.scs.2022.103869.
   PubMed Web of Science ®Google Scholar
• Li, Z., X. Huang, X. Ye, and X. Li. 2020. “ODT Flow Explorer: Extract, Query, and Visualize Human Mobility.” ArXiv. https://doi.org/10.1371/journal.pone.0241957.
   Google Scholar
• Lindell Michael, K., J.-C. Lu, and S. Prater Carla. 2005. “Household Decision Making and Evacuation in Response to Hurricane Lili.” Natural Hazards Review 6 (4): 171–179. https://doi.org/10.1061/(ASCE)1527-6988(2005)6:4(171).
   Google Scholar
• Lin, B., L. Zou, H. Zhou, M. Yang, and B. Cai. 2023. “Sensing the Pulse of the Pandemic: Geovisualizing the Demographic Disparities of Public Sentiment Toward COVID-19 Through Social Media.” Cartography and Geographic Information Science 1–19. arXiv preprint arXiv:2304.06120. https://doi.org/10.1080/15230406.2024.2323489.
   Web of Science ®Google Scholar
• Lu, X., L. Bengtsson, and P. Holme. 2012. “Predictability of Population Displacement After the 2010 Haiti Earthquake.” Proceedings of the National Academy of Sciences 109 (29): 11576–11581. https://doi.org/10.1073/pnas.1203882109.
   PubMed Web of Science ®Google Scholar
• Lusk, C., G. L. Delclos, K. Burau, D. D. Drawhorn, and L. A. Aday. 2007. “Mail versus Internet Surveys: Determinants of Method of Response Preferences Among Health Professionals.” Evaluation & the Health Professions 30 (2): 186–201. https://doi.org/10.1177/0163278707300634.
   PubMed Web of Science ®Google Scholar
• Martín, Y., S. L. Cutter, and Z. Li. 2020. “Bridging Twitter and Survey Data for Evacuation Assessment of Hurricane Matthew and Hurricane Irma.” Natural Hazards Review 21 (2). https://doi.org/10.1061/(asce)nh.1527-6996.0000354.
   PubMed Web of Science ®Google Scholar
• Martín, Y., Z. Li, S. L. Cutter, and S. Ukkusuri. 2017. “Leveraging Twitter to Gauge Evacuation Compliance: Spatiotemporal Analysis of Hurricane Matthew.” PLoS One 12 (7): e0181701. https://doi.org/10.1371/journal.pone.0181701.
   PubMed Web of Science ®Google Scholar
• McClure, L. A., M. L. Boninger, M. L. Oyster, M. J. Roach, J. Nagy, and G. Nemunaitis. 2011. “Emergency Evacuation Readiness of Full-Time Wheelchair Users with Spinal Cord Injury.” Archives of Physical Medicine and Rehabilitation 92 (3): 491–498. https://doi.org/10.1016/j.apmr.2010.08.030.
   PubMed Web of Science ®Google Scholar
• Mesa-Arango, R., S. Hasan, S. V. Ukkusuri, and P. Murray-Tuite. 2013. “Household-Level Model for Hurricane Evacuation Destination Type Choice Using Hurricane Ivan Data.” Natural Hazards Review 14 (1): 11–20. https://doi.org/10.1061/(ASCE)NH.1527-6996.0000083.
   Web of Science ®Google Scholar
• Metaxa-Kakavouli, D., P. Maas, and D. P. Aldrich. 2018. “How Social Ties Influence Hurricane Evacuation Behavior.” Proceedings of the ACM on Human-Computer Interaction 2 (CSCW): 1–16. Article 122. https://doi.org/10.1145/3274391.
   Google Scholar
• Morss, R. E., J. L. Demuth, J. K. Lazo, K. Dickinson, H. Lazrus, and B. H. Morrow. 2016. “Understanding Public Hurricane Evacuation Decisions and Responses to Forecast and Warning Messages.” Weather and Forecasting 31 (2): 395–417. https://doi.org/10.1175/WAF-D-15-0066.1.
   Web of Science ®Google Scholar
• NEWS, C. 2022. Floridians Scramble to Evacuate as Hurricane Ian Strengthens—But Some Refuse to Leave. https://www.cbsnews.com/news/hurricane-ian-category-4-evacuations-tampa/.
   Google Scholar
• NHC. 2022. IAN Graphics Archive: 5-Day Forecast Track and Watch/Warning Graphic. https://www.nhc.noaa.gov/archive/2022/IANgraphics.php?product=5dayconenoline.
   Google Scholar
• NOAA. 2005. U.S. Mainland Hurricane Strikes by State, 1851–2004. https://www.nhc.noaa.gov/paststate.shtml.
   Google Scholar
• NOAA. (2022. NOAA National Centers for Environmental Information, Monthly National Climate Report for September 2022. https://www.ncei.noaa.gov/access/monitoring/monthly-report/national/202209/supplemental/page-5.
   Google Scholar
• NOAA. 2023a. Continental United States Hurricane Impacts/Landfalls (1851-2022). https://www.aoml.noaa.gov/hrd/hurdat/AllU.S.Hurricanes.html.
   Google Scholar
• NOAA. 2023b. NOAA National Centers for Environmental Information (NCEI) U.S. Billion-Dollar Weather and Climate Disasters. https://www.ncei.noaa.gov/access/billions/.
   Google Scholar
• Pan, A. 2020. “Study on the Decision-Making Behavior of Evacuation for Coastal Residents Under Typhoon Storm Surge Disaster.” International Journal of Disaster Risk Reduction 45:101522. https://doi.org/10.1016/j.ijdrr.2020.101522.
   Web of Science ®Google Scholar
• Roy, K. C., and S. Hasan. 2021. “Modeling the Dynamics of Hurricane Evacuation Decisions from Twitter Data: An Input Output Hidden Markov Modeling Approach.” Transportation Research Part C: Emerging Technologies 123:102976. https://doi.org/10.1016/j.trc.2021.102976.
   Web of Science ®Google Scholar
• SafeGraph. 2020. SafeGraph COVID-19 Data Consortium. https://www.safegraph.com/covid-19-data-consortium.
   Google Scholar
• SafeGraph. 2023. Knowledge Sharing, Industry Trends, and Everything You Need to Know About Places Data. https://www.safegraph.com/blog.
   Google Scholar
• Smith, A. B. 2024. “2023 US Billion-dollar weather and climate disasters in historical context.” 104th AMS Annual Meeting, January 28–February 1, 2024, Baltimore, MD, USA. New York, NY, USA: American Meteorological Society.
   Google Scholar
• Stein, R., B. Buzcu‐Guven, L. Dueñdueñas‐Osorio, D. Subramanian, and D. Kahle. 2013. “How Risk Perceptions Influence Evacuations from Hurricanes and Compliance with Government Directives.” Policy Studies Journal 41 (2): 319–342. https://doi.org/10.1111/psj.12019.
   Web of Science ®Google Scholar
• Stein, R. M., L. Dueñdueñas‐Osorio, and D. Subramanian. 2010. “Who Evacuates When Hurricanes Approach? The Role of Risk, Information, and Location.” Social science quarterly 91 (3): 816–834. https://doi.org/10.1111/j.1540-6237.2010.00721.x.
   PubMed Web of Science ®Google Scholar
• Stieglitz, S., M. Mirbabaie, B. Ross, and C. Neuberger. 2018. “Social Media Analytics – Challenges in Topic Discovery, Data Collection, and Data Preparation.” International Journal of Information Management 39:156–168. https://doi.org/10.1016/j.ijinfomgt.2017.12.002.
   Web of Science ®Google Scholar
• Tanim, S. H., B. M. Wiernik, S. Reader, and Y. Hu. 2022. “Predictors of Hurricane Evacuation Decisions: A Meta-Analysis.” Journal of Environmental Psychology 79:101742. https://doi.org/10.1016/j.jenvp.2021.101742.
   Web of Science ®Google Scholar
• U.S. Census Bureau. 2023a. State Population Totals and Components of Change: 2020-2022. https://www.census.gov/data/tables/time-series/demo/popest/2020s-state-total.html.
   Google Scholar
• U.S. Census Bureau. 2023b. ZIP Code Tabulation Areas (ZCTAs). https://www.census.gov/programs-surveys/geography/guidance/geo-areas/zctas.html.
   Google Scholar
• Vassolo, M. 2022. Miami-Dade Escapes Hurricane Ian with Minor Damages. https://www.axios.com/local/miami/2022/09/29/power-outage-miami-hurricane-ian.
   Google Scholar
• Wang, Q., J. E. Taylor, and L. A. Braunstein. 2016. “Patterns and Limitations of Urban Human Mobility Resilience Under the Influence of Multiple Types of Natural Disaster.” PLoS One 11 (1): e0147299. https://doi.org/10.1371/journal.pone.0147299.
   PubMed Web of Science ®Google Scholar
• Warren, M. S., and S. W. Skillman. 2020. “Mobility Changes in Response to COVID-19.” arXiv preprint arXiv:2003.14228.
   Google Scholar
• Weller, S. C., R. Baer, and J. Prochaska. 2016. “Should I Stay or Should I Go? Response to the Hurricane Ike Evacuation Order on the Texas Gulf Coast.” Natural Hazards Review 17 (3): 04016003. https://doi.org/10.1061/(ASCE)NH.1527-6996.0000217.
   Web of Science ®Google Scholar
• Western, B., A. Braga, D. Hureau, and C. Sirois. 2016. “Study Retention As Bias Reduction in a Hard-To-Reach Population.” Proceedings of the National Academy of Sciences 113 (20): 5477–5485. https://doi.org/10.1073/pnas.1604138113.
   PubMed Web of Science ®Google Scholar
• Whitehead, J. C., B. Edwards, M. Van Willigen, J. R. Maiolo, K. Wilson, and K. T. Smith. 2000. “Heading for Higher Ground: Factors Affecting Real and Hypothetical Hurricane Evacuation Behavior.” Global Environmental Change Part B: Environmental Hazards 2 (4): 133–142. https://doi.org/10.1016/S1464-2867(01)00013-4.
   Google Scholar
• Wright, K. B. 2017. “Researching Internet-Based Populations: Advantages and Disadvantages of Online Survey Research, Online Questionnaire Authoring Software Packages, and Web Survey Services.” Journal of Computer-Mediated Communication 10 (3). https://doi.org/10.1111/j.1083-6101.2005.tb00259.x.
   Google Scholar
• Wu, H.-C., M. K. Lindell, and C. S. Prater. 2012. “Logistics of Hurricane Evacuation in Hurricanes Katrina and Rita.” Transportation Research Part F: Traffic Psychology and Behaviour 15 (4): 445–461. https://doi.org/10.1016/j.trf.2012.03.005.
   Web of Science ®Google Scholar
• Yabe, T., S. V. Ukkusuri, C. Rao, and P. S. 2019. “Mobile Phone Data Reveals the Importance of Pre-Disaster Inter-City Social Ties for Recovery After Hurricane Maria.” Applied Network Science 4 (1): 98. https://doi.org/10.1007/s41109-019-0221-5.
   Google Scholar
• Younes, H., A. Darzi, and L. Zhang. 2021. “How Effective Are Evacuation Orders? An Analysis of Decision Making Among Vulnerable Populations in Florida During Hurricane Irma.” Travel Behaviour and Society 25:144–152. https://doi.org/10.1016/j.tbs.2021.07.006.
   Web of Science ®Google Scholar
• Yuan, F., A. Esmalian, B. Oztekin, and A. Mostafavi. 2022. “Unveiling Spatial Patterns of Disaster Impacts and Recovery Using Credit Card Transaction Fluctuations.” Environment and Planning B: Urban Analytics and City Science 49 (9): 2378–2391. https://doi.org/10.1177/23998083221090246.
   Google Scholar
• Yu, M., C. Yang, and Y. Li. 2018. “Big data in natural disaster management: a review.” Geosciences 8 (5): 165. https://doi.org/10.3390/geosciences8050165.
   Web of Science ®Google Scholar
• Zang, E., J. West, N. Kim, and C. Pao. 2021. “US Regional Differences in Physical Distancing: Evaluating Racial and Socioeconomic Divides During the COVID-19 Pandemic.” PLoS One 16 (11): e0259665. https://doi.org/10.1371/journal.pone.0259665.
   PubMed Web of Science ®Google Scholar
• Zhang, Y., C. S. Prater, and M. K. Lindell. 2004. “Risk Area Accuracy and Evacuation from Hurricane Bret.” Natural Hazards Review 5 (3): 115–120. https://doi.org/10.1061/(ASCE)1527-6988(2004)5:3(115).
   Google Scholar
• Zhu, Y.-J., Y. Hu, and J. M. Collins. 2020. “Estimating Road Network Accessibility During a Hurricane Evacuation: A Case Study of Hurricane Irma in Florida.” Transportation Research Part D: Transport & Environment 83:102334. https://doi.org/10.1016/j.trd.2020.102334.
   Web of Science ®Google Scholar
• Zou, L., N. S. N. Lam, H. Cai, and Y. Qiang. 2018. “Mining Twitter Data for Improved Understanding of Disaster Resilience.” Annals of the American Association of Geographers 108 (5): 1422–1441. https://doi.org/10.1080/24694452.2017.1421897.
   Web of Science ®Google Scholar