Climatic Change

, Volume 116, Issue 3–4, pp 547–563 | Cite as

Assessing vulnerability due to sea-level rise in Maui, Hawaii using LiDAR remote sensing and GIS

  • Hannah M. Cooper
  • Qi Chen
  • Charles H. Fletcher
  • Matthew M. Barbee
Article

Abstract

Sea-level rise (SLR) threatens islands and coastal communities due to vulnerable infrastructure and populations concentrated in low-lying areas. LiDAR (Light Detection and Ranging) data were used to produce high-resolution DEMs (Digital Elevation Model) for Kahului and Lahaina, Maui, to assess the potential impacts of future SLR. Two existing LiDAR datasets from USACE (U.S. Army Corps of Engineers) and NOAA (National Oceanic and Atmospheric Administration) were compared and calibrated using the Kahului Harbor tide station. Using tidal benchmarks is a valuable approach for referencing LiDAR in areas lacking an established vertical datum, such as in Hawai‘i and other Pacific Islands. Exploratory analysis of the USACE LiDAR ground returns (point data classified as ground after the removal of vegetation and buildings) indicated that another round of filtering could reduce commission errors. Two SLR scenarios of 0.75 (best-case) to 1.9 m (worst-case) (Vermeer and Rahmstorf Proc Natl Acad Sci 106:21527–21532, 2009) were considered, and the DEMs were used to identify areas vulnerable to flooding. Our results indicate that if no adaptive strategies are taken, a loss ranging from $18.7 million under the best-case SLR scenario to $296 million under the worst-case SLR scenario for Hydrologically Connected (HC; marine inundation) and Hydrologically Disconnected (HD; drainage problems due to a higher water table) areas combined is possible for Kahului; a loss ranging from $57.5 million under the best-case SLR scenario to $394 million under the worst-case SLR scenario for HC and HD areas combined is possible for Lahaina towards the end of the century. This loss would be attributable to inundation between 0.55 km2 to 2.13 km2 of area for Kahului, and 0.04 km2 to 0.37 km2 of area for Lahaina.

Notes

Acknowledgments

We appreciate comments by three anonymous reviewers. Data were provided by the NOAA CSC, NGS, Hawai‘i Statewide GIS Program, and DigitalGlobe. This study was funded by a grant from the U.S. Department of Interior Pacific Islands Climate Change Cooperative.

References

  1. ASPRS (2004) ASPRS guidelines vertical accuracy reporting for LiDAR data, vol.1.0. http://www.asprs.org/a/society/committees/standards/standards_comm.html. Accessed 22 August 2011
  2. CCSP (2009) Synthesis and assessment product 4.1: coastal sensitivity to sea-level rise: a focus on the Mid-Atlantic region. U.S. Climate Change Program, Washington, DCGoogle Scholar
  3. Chen Q (2007) Airborne LiDAR data processing and information extraction. Photogramm Eng Rem Sens 73:109–112Google Scholar
  4. Chen Q, Gong P, Baldocchi DD, Xie G (2007) Filtering airborne laser scanning data with morphological methods. Photogramm Eng Rem Sens 73:171–181Google Scholar
  5. FGDC (1998) Geospatial positioning accuracy standards, Part 3. National Standard for Spatial Data Accuracy. FGDC-STD-007.3-1998. http://www.fgdc.gov/standards/projects/FGDC-standards-projects/accuracy/part3/index_html. Accessed 22 August 2011
  6. Fletcher CH (2009) Sea level by the end of the 21st century: a review. Shore & Beach 77:4–12Google Scholar
  7. Fletcher C, Boyd R, Grober-Dunsmore R, Neal WJ, Tice V (2010) Living on the shores of Hawai‘i. University of Hawai‘i Press, HonoluluGoogle Scholar
  8. Genz AS, Fletcher CH, Dunn RA, Frazer LN, Rooney JJ (2007) The predictive accuracy of shoreline change rate methods and alongshore beach variation on Maui, Hawaii. J Coast Res 23:87–105. doi: 10.2112/05-0521.1 CrossRefGoogle Scholar
  9. Gesch DB (2009) Analysis of LiDAR elevation data for improved identification and delineation of lands vulnerable to sea-level rise. J Coast Res 53:49–58. doi: 10.2112/S153-006.1 CrossRefGoogle Scholar
  10. GOF (2011) The Global Oceans Forum report of activities 2010. www.globaloceans.org. Accessed 22 august 2011
  11. Henman J, Poulter B (2008) Inundation of freshwater peatlands by sea level rise: Uncertainty and potential carbon cycle feedbacks. J Geophys Res 113:G01011. doi: 10.1029/2006JG000395 CrossRefGoogle Scholar
  12. IPCC (2007) Climate change 2007, the physical science basis. Cambridge University Press, CambridgeGoogle Scholar
  13. Liu XY (2011) Accuracy assessment of LiDAR elevation data using survey marks. Surv Rev 43:80–93. doi: 10.1179/003962611X12894696204704 CrossRefGoogle Scholar
  14. Marcy D, Brooks W, Draganov K, Hadley B, Haynes C, Herold N, McCombs J, Pendleton M, Ryan S, Schmid K, Sutherland M, Waters K (2011) New mapping tool and techniques for visualizing sea level rise and coastal flooding impacts. In: Wallendorf LA, Jones C, Ewing L, Battalio B (eds) Proceedings of the 2011 Solutions to Coastal Disasters Conference, Anchorage, Alaska, June 26 to June 29, 2011., pp 474–90, Reston, VA: American Society of Civil Engineers. http://csc.noaa.gov/digitalcoast/tools/slrviewer/support.html#cite1. Accessed 17, March 2012Google Scholar
  15. McLeod E, Poulter B, Hinkel J, Reyes E, Salm R (2010) Sea level-rise impact models and environmental conservation: a review of models and their applications. Ocean Coast Manage 53:507–517. doi: 10.1016/j.ocecoaman.2010.06.009 CrossRefGoogle Scholar
  16. Maune DF (2007) DEM User Requirements. In: Maune DF (ed) Digital elevation model technologies and applications: the DEM users manual, 2nd edn. American Society for Photogrammatry and Remote Sensing, Bethesda, pp 449–473Google Scholar
  17. Nicholls RJ (2011) Planning for the impacts of sea level rise. Oceanography 24:144–157. doi: 10.5670/oceanog.2011.34 CrossRefGoogle Scholar
  18. NOAA (2001) Tidal datums and their applications. NOAA special publication NOS CO-OPS 1. NOAA National Ocean Service, Silver SpringGoogle Scholar
  19. NOAA (2008) Topographic and bathymetric data considerations: datums, datum conversion techniques, and data integration. Technical Report NOAA/CSC/20718-PUB. National Oceanic and Atmospheric Administration, Charleston, SCGoogle Scholar
  20. NOAA (2009) Sea level variations of the United States 1854–2006. Technical Report NOS CO- OPS 053. NOAA National Ocean Service, Silver SpringGoogle Scholar
  21. NOAA (2010) Technical considerations for use of geospatial data in sea level change mapping and assessment. NOAA NOS Technical Report. NOAA National Ocean Service, Silver SpringGoogle Scholar
  22. NOAA (2011) Digital Coast, NOAA Coastal Services Center. http://csc.noaa.gov/digitalcoast/tools/slrviewer/support.html#cite1. Accessed 17, March 2012
  23. Poulter B, Halpin PN (2008) Raster modeling of coastal flooding from sea-level rise. Int J Geogr Inf Sci 22:167–182. doi: 10.1080/13658810701371858 CrossRefGoogle Scholar
  24. Rotzoll K, El-Kadi AL (2008) Estimating hydraulic properties of coastal aquifers using wave setup. J Hydrol 353:201–213. doi: 10.1016/j.jhydrol.2008.02.005 CrossRefGoogle Scholar
  25. Rotzoll K, El-Kadi AL, Gingerich SB (2008) Analysis of an unconfined aquifer subject to asynchronous dual-tide propagation. Ground Water 46:239–250. doi: 10.1111/j.1745-6584.2007.00412.x CrossRefGoogle Scholar
  26. US Census Bureau (2011) The 2011 statistical abstract of the United States. US Census Bureau. Washington, DC. http://www.census.gov/compendia/statab/. Accessed 22 August 2011
  27. Vermeer M, Rahmstorf S (2009) Global sea level linked to global temperature. Proc Natl Acad Sci 106:21527–21532. doi: 10.1073/pnas/.0907769106 CrossRefGoogle Scholar
  28. Wu SY, Yarnal B, Fisher A (2002) Vulnerability of coastal communities to sea-level rise: a case study of Cape May County, New Jersey, USA. Clim Res 22:255–270CrossRefGoogle Scholar
  29. Zhang K (2011) Analysis of non-linear inundation from sea-level rise using LiDAR data: a case study for South Florida. Clim Change 106:537–565. doi: 10.1007/s10584-010-9987-2 CrossRefGoogle Scholar
  30. Zhang K, Dittmar J, Ross M, Bergh C (2011) Assessment of sea level rise impacts on human population and real property in the Florida Keys. Clim Change 107:129–146. doi: 10.1007/s10584-011-0080-2 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  • Hannah M. Cooper
    • 1
    • 2
  • Qi Chen
    • 1
  • Charles H. Fletcher
    • 2
  • Matthew M. Barbee
    • 2
  1. 1.Department of GeographyUniversity of Hawai‘iHonoluluUSA
  2. 2.Department of Geology and Geophysics, School of Ocean and Earth Science and TechnologyUniversity of Hawai‘iHonoluluUSA

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