A novel approach to leveraging social media for rapid flood mapping: a case study of the 2015 South Carolina floods

Cartography and Geographic Information Science

Volumn 45, Issue 2, 2018, Pages 97-110

  Li, Zhenlong ^a   Wang, Cuizhen ^a   Emrich, Christopher T ^b   Guo, Diansheng ^a  

^a UNIVERSITY OF SOUTH CAROLINA   (United States)

^b UNIVERSITY OF CENTRAL FLORIDA   (United States)

Author keywords

disaster management; flood mapping; geospatial statistics; Social media; Twitter

Indexed keywords

DECISION MAKING; DISASTER PREVENTION; DISASTERS; MAPPING; REMOTE SENSING; SOCIAL NETWORKING (ONLINE);

DISASTER MANAGEMENT; FLOOD MAPPING; GEO-SPATIAL; SOCIAL MEDIA; TWITTER;

FLOODS;

DECISION MAKING; DISASTER MANAGEMENT; FLOODING; GAUGE; GEOSTATISTICS; HAZARD ASSESSMENT; REAL TIME; REMOTE SENSING; SOCIAL MEDIA; SPATIOTEMPORAL ANALYSIS;

SOUTH CAROLINA; UNITED STATES;

EID: 85011931486     PISSN: 15230406     EISSN: 15450465     Source Type: Journal    
DOI: 10.1080/15230406.2016.1271356     Document Type: Article

References (32)

1. Ashktorab, Z., Brown, C., Nandi, M., & Culotta, A., (2014). Tweedr: Mining Twitter to inform disaster response. In S. R., Hiltz, M. S., Pfaff, L., Plotnick, & A. C., Robinson (Eds.). Proceedings of the 11th International ISCRAM Conference. University Park, PA: PSU.
2. Brennan, A., Carbone, G., Dow, K., Fly, L., Gao, P., Konrad, C., … Tufford, D., (2015). The South Carolina floods of October 2015. Retrieved June20, 2016, from http://www.cisa.sc.edu/PDFs/October%202015%20Flood%20Event%204%20Pager.pdf
3. Brivio, P. A., Colombo, R., Maggi, M., & Tomasoni, R., (2002). Integration of remote sensing data and GIS for accurate mapping of flooded areas. International Journal of Remote Sensing, 23(3), 429–441. doi:10.1080/01431160010014729
4. Cervone, G., Sava, E., Huang, Q., Schnebele, E., Harrison, J., & Waters, N., (2016). Using Twitter for tasking remote-sensing data collection and damage assessment: 2013 Boulder flood case study. International Journal of Remote Sensing, 37(1), 100–124. doi:10.1080/01431161.2015.1117684
5. de Albuquerque, J. P., Herfort, B., Brenning, A., & Zipf, A., (2015). A geographic approach for combining social media and authoritative data towards identifying useful information for disaster management. International Journal of Geographical Information Science, 29(4), 667–689. doi:10.1080/13658816.2014.996567
6. Feaster, T. D., Shelton, J. M., & Robbins, J. C., (2015). Preliminary peak stage and streamflow data at selected USGS streamgaging stations for the South Carolina flood of October 2015 (ver. 1.1, November 2015, U.S. Geological Survey Open-File Report 2015–1201). Reston, VA: USGS. 19 p. Retrieved November19, 2016, from http://pubs.usgs.gov/of/2015/1201/ofr20151201.pdf
7. Fohringer, J., Dransch, D., Kreibich, H., & Schröter, K., (2015). Social media as an information source for rapid flood inundation mapping. Natural Hazards and Earth System Sciences, 15(12), 2725–2738. doi:10.5194/nhess-15-2725-2015
8. Goodchild, M. F., (2007a). Citizens as voluntary sensors: Spatial data infrastructure in the world of web 2.0. International Journal of Spatial Data Infrastructures Research, 2, 24–32. http://ijsdir.jrc.ec.europa.eu/index.php/ijsdir/article/view/28
9. Goodchild, M. F., (2007b). Citizens as sensors: The world of volunteered geography. GeoJournal, 69(4), 211–221. doi:10.1007/s10708-007-9111-y
10. Goodchild, M. F., & Glennon, J. A., (2010). Crowdsourcing geographic information for disaster response: A research frontier. International Journal of Digital Earth, 3(3), 231–241. doi:10.1080/17538941003759255
11. Graham, M., Poorthuis, A., & Zook, M., (2012). Digital trails of the UK floods - how well do tweets match observations? [datablog]. The Guardian. Retrieved June20, 2016, from https://www.theguardian.com/news/datablog/2012/nov/28/data-shadows-twitter-uk-floods-mapped
12. Herfort, B., de Albuquerque, J. P., Schelhorn, S. J., & Zipf, A., (2014a). Exploring the geographical relations between social media and flood phenomena to improve situational awareness. In J., Huerta, S., Schade, & C., Granell (Eds.). Connecting a digital Europe through location and place (pp. 55–71). Cham, Switzerland: Springer International. doi: 10.1007/978-3-319-03611-3_4
13. Herfort, B., Schelhorn, S. J., de Albuquerque, J. P., & Zipf, A., (2014b). Does the spatiotemporal distribution of tweets match the spatiotemporal distribution of flood phenomena ? A study about the River Elbe Flood in June 2013. In S. R., Hiltz, M. S., Pfaff, L., Plotnick, & P. C., Shih (Eds.) Proceedings of the 11th International ISCRAM Conference (pp. 747–751). University Park, PA: PSU.
14. Hopfer, S, & MacEachren, A.M., (2007). Leveraging the potential of geospatial annotations for collaboration: A communication theory perspective. International Journal of Geographical Information Science, 21, 921–934. doi:10.1080/13658810701377780
15. Imran, M., Elbassuoni, S. M., Castillo, C., Diaz, F., Meier, P., & Müller, T., (2013). Extracting information nuggets from disaster-related messages in social media. In T., Comes, F., Fiedrich, S., Fortier, J., Geldermann and T., Müller, (Eds.), Proceedings of the 10th International ISCRAM Conference (pp. 791–800). Karlsruhe, Germany: KIT.
16. Kongthon, A., Haruechaiyasak, C., Pailai, J., & Kongyoung, S., (2012). The role of Twitter during a natural disaster: Case study of 2011 Thai flood. In D.F. Kocaoglu, T. R. Anderson, T. U. Daim, A. Jetter, C. M. Weber (Eds.), 2012 Proceedings of PICMET ’12: Technology Management for Emerging Technologies (pp. 2227–2232). Piscataway, NJ: IEEE.
17. Kryvasheyeu, Y., Chen, H., Obradovich, N., Moro, E., van Hentenryck, P., Fowler, J., & Cebrian, M., (2016). Rapid assessment of disaster damage using social media activity. Science Advances, 2(3), e1500779. doi:10.1126/sciadv.1500779
18. Li, L., Goodchild, M. F., & Xu, B., (2013). Spatial, temporal, and socioeconomic patterns in the use of Twitter and Flickr. Cartography and Geographic Information Science, 40(2), 61–77. doi:10.1080/15230406.2013.777139
19. McDougall, K., & Temple-Watts, P., (2012). The use of LIDAR and volunteered geographic information to map flood extents and inundation. In M. Shortis, & M. Madden (Eds.), ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 1(4), 251–256. doi:10.5194/isprsannals-I-4-251-2012
20. Musser, J. W., Watson, K. M., Painter, J. A., & Gotvald, A. J., (2016). Flood-inundation maps of selected areas affected by the flood of October 2015 in Central and Coastal South Carolina. (USGS Open file Report 2016-1019). Reston, VA: USGS. doi:10.3133/ofr20161019
21. Poser, K., & Dransch, D., (2010). Volunteered geographic information for disaster management with application to rapid flood damage estimation. Geomatica, 64(1), 89–98.
22. Sakaki, T., Toriumi, F., & Matsuo, Y., (2011). Tweet trend analysis in an emergency situation. In Proceedings of the Special Workshop on Internet and Disasters. New York: ACM. 10.1145/2079360.2079363
23. SCDNR (South Carolina Department of Natural Resources). (2016). LiDAR and related data products. Retrieved August14, 2016, from http://www.dnr.sc.gov/GIS/lidar.html
24. Schnebele, E., & Cervone, G., (2013). Improving remote sensing flood assessment using volunteered geographical data. Natural Hazards and Earth System Sciences, 13, 669–677. doi:10.5194/nhess-13-669-2013
25. Schnebele, E., Cervone, G., Kumar, S., & Waters, N., (2014). Real time estimation of the Calgary floods using limited remote sensing data. Water, 6(2), 381–398. doi:10.3390/w6020381
26. Schumann, G. J. P., Neal, J. C., Mason, D. C., & Bates, P. D., (2011). The accuracy of sequential aerial photography and SAR data for observing urban flood dynamics, a case study of the UK summer 2007 floods. Remote Sensing of Environment, 115(10), 2536–2546. doi:10.1016/j.rse.2011.04.039
27. Smith, L., Liang, Q., James, P., & Lin, W., (2015). Assessing the utility of social media as a data source for flood risk management using a real‐time modelling framework. Journal of Flood Risk Management. Advance online publication. doi:10.1111/jfr3.12154
28. Smith, L. C., (1997). Satellite remote sensing of river inundation area, stage, and discharge: A review. Hydrological Processes, 11(10), 1427–1439. doi:10.1002/(SICI)1099-1085(199708)11:10<1427::AID-HYP473>3.0.CO;2-S
29. Triglav-Čekada, M., & Radovan, D., (2013). Using volunteered geographical information to map the November 2012 floods in Slovenia. Natural Hazards and Earth System Sciences, 13(11), 2753–2762. doi:10.5194/nhess-13-2753-2013
30. USGS. (2016). Flood inundation mapping (FIM) program. Retrieved October3, 2016, from http://water.usgs.gov/osw/flood_inundation/
31. USGS (US Geological Survey). (2016). Current Water Data for the nation. Retrieved July31, 2016, from http://waterdata.usgs.gov/nwis/rt
32. Vieweg, S., Hughes, A. L., Starbird, K., Palen, L., & Aoki, P., (2010). Microblogging during two natural hazards events: what Twitter may contribute to situational awareness. In R., Grinter, T., Rodden, P., Aoki,E., Cutrell,R., Jeffries,& G., Olson, (Eds.), CHI ’10: Proceedings of the SIGCHI Conference on human factors in computing systems, (pp. 1079–1088). New York: ACM. doi:10.1145/1753326.1753486