Coral Reefs

, Volume 35, Issue 3, pp 889–894 | Cite as

End of the chain? Rugosity and fine-scale bathymetry from existing underwater digital imagery using structure-from-motion (SfM) technology

  • Curt D. Storlazzi
  • Peter Dartnell
  • Gerald A. Hatcher
  • Ann E. Gibbs


The rugosity or complexity of the seafloor has been shown to be an important ecological parameter for fish, algae, and corals. Historically, rugosity has been measured either using simple and subjective manual methods such as ‘chain-and-tape’ or complicated and expensive geophysical methods. Here, we demonstrate the application of structure-from-motion (SfM) photogrammetry to generate high-resolution, three-dimensional bathymetric models of a fringing reef from existing underwater video collected to characterize the seafloor. SfM techniques are capable of achieving spatial resolution that can be orders of magnitude greater than large-scale lidar and sonar mapping of coral reef ecosystems. The resulting data provide finer-scale measurements of bathymetry and rugosity that are more applicable to ecological studies of coral reefs than provided by the more expensive and time-consuming geophysical methods. Utilizing SfM techniques for characterizing the benthic habitat proved to be more effective and quantitatively powerful than conventional methods and thus might portend the end of the ‘chain-and-tape’ method for measuring benthic complexity.


Rugosity Bathymetry Imagery Structure-from-motion (SfM) 



This is a contribution of the US Geological Survey’s (USGS) Pacific Coral Reef Project and was supported by the USGS Coastal and Marine Geology Program. This work is dedicated to Paul Jokiel (UH-HIMB), who taught so much about coral reefs and their monitoring to so many. We would like to thank Dave Zawada (USGS) and three anonymous reviewers who contributed numerous excellent suggestions. Use of trademark names does not suggest USGS endorsement of products.


  1. Brown EK, Cox EF, Tissot B, Jokiel PL, Rodgers KS, Smith WR, Coles SL (2004) Development of benthic sampling methods for the Coral Reef Assessment and Monitoring Program (CRAMP) in Hawai‘i. Pac Sci 7:145–158CrossRefGoogle Scholar
  2. Burns JHR, Delparte D, Gates RD, Takabayashi M (2015) Integrating structure-from-motion photogrammetry with geospatial software as a novel technique for quantifying 3D ecological characteristics of coral reefs. PeerJ 3:e1077CrossRefPubMedPubMedCentralGoogle Scholar
  3. Dartnell P, Gardner JV (2004) Predicting sea floor facies from multibeam bathymetry and backscatter data. Photogramm Eng Remote Sensing 70:1081–1091CrossRefGoogle Scholar
  4. Figueria W, Ferrari R, Weatherby E, Porter A, Hawes S, Byrne M (2015) Accuracy and precision of habitat structural complexity metrics derived from underwater photogrammetry. Remote Sens 7:16883–16900CrossRefGoogle Scholar
  5. Fisher WS, Davis WP, Quarles RL, Patrick J, Campbell JG, Harris PS, Hemmer BL, Parsons M (2007) Characterizing coral condition using estimates of three-dimensional colony surface area. Environ Monit Assess 125:347–360CrossRefPubMedGoogle Scholar
  6. Friedman A, Pizarro O, Williams SB, Johnson-Roberson M (2012) Multi-scale measures of rugosity, slope and aspect from benthic stereo image reconstructions. PLoS One 7:e50440CrossRefPubMedPubMedCentralGoogle Scholar
  7. Graham NAJ, Nash KL (2012) The importance of structural complexity in coral reef ecosystems. Coral Reefs 32:315–326CrossRefGoogle Scholar
  8. He H, Ferrari R, McKinnon D, Roff GA, Smith R, Mumby PJ, Upcroft B (2012) Measuring reef complexity and rugosity from monocular video bathymetric reconstruction. Proc 12th Int Coral Reef Symp, James Cook University, Cairns, AustraliaGoogle Scholar
  9. Hill J, Wilkinson C (2004) Methods for ecological monitoring of coral reefs, Version 1. A resource for managers, Australian Institute of Marine Science, Townsville, AustraliaGoogle Scholar
  10. Javernick L, Brasington J, Caruso B (2014) Modeling the topography of shallow braided rivers using structure-from-motion photogrammetry. Geomorphology (Amst) 213:166–218CrossRefGoogle Scholar
  11. Kocak DM, Caimi FM, Das PS, Karson JA (1999) A 3-D laser line scanner for outcrop scale studies of seafloor features. OCEANS ‘99 MTS/IEEE 3:1105–1114Google Scholar
  12. Kohler KE, Gill SM (2006) Coral Point Count with Excel extensions (CPCe): a Visual Basic program for the determination of coral and substrate coverage using random point count methodology. Comput Geosci 32:1259–1269CrossRefGoogle Scholar
  13. LaRocque PE, Banic JR, Cunningham AG (2004) Design description and field testing of the SHOALS-1000T airborne bathymeter. Proceedings SPIE vol. 5412, laser radar technology and applications IX 162. doi: 10.1117/12.564924
  14. Leon JX, Roelfsema CM, Saunders MI, Phinn SR (2015) Measuring coral reef terrain roughness using structure-from-motion close-range photogrammetry. Geomorphology (Amst) 242:21–28CrossRefGoogle Scholar
  15. Lowe RJ, Falter JL (2015) Ocean forcing of coral reefs. Annu Rev Mar Sci 7:43–66CrossRefGoogle Scholar
  16. McCormick MI (1994) Comparison of field methods for measuring surface topography and their associations with a tropical reef fish assemblage. Mar Ecol Prog Ser 112:87–96CrossRefGoogle Scholar
  17. Pollefeys M, Koch R, VanGool L (1999) Self-calibration and metric reconstruction in spite of varying and unknown intrinsic camera parameters. Int J Comput Vis 32:7–25CrossRefGoogle Scholar
  18. Risk MJ (1972) Fish diversity on a coral reef in the Virgin Islands. Atoll Res Bull 193:1–6CrossRefGoogle Scholar
  19. Siccardi A, Bozzano R, Bono R (1997) Seabed vegetation analysis by a 2 MHz sonar. OCEANS ‘97 MTS/IEEE 1:344–350Google Scholar
  20. Storlazzi CD, Fregoso TA, Golden NE, Finlayson DP (2011) Sediment dynamics and the burial and exhumation of bedrock reefs along an emergent coastline as elucidated by repetitive sonar surveys: Northern Monterey Bay, CA. Mar Geol 289:46–59CrossRefGoogle Scholar
  21. Tomasi C, Kanade T (1992) Shape and motion from image streams under orthography: a factorization method. Int J Comput Vis 9:137–154CrossRefGoogle Scholar
  22. Westoby MJ, Brasington J, Glasser NF, Hambrey MJ, Reynolds JM (2012) ‘Structure-from-motion’ photogrammetry: a low-cost, effective tool for geoscience applications. Geomorphology (Amst) 179:300–314CrossRefGoogle Scholar
  23. Wright DJ, Pendleton M, Boulware J, Walbridge S, Gerlt B, Eslinger D, Sampson D, Huntley E (2012) ArcGIS benthic terrain modeler (BTM), v. 3.0, Environmental Systems Research Institute, NOAA Coastal Services Center, Massachusetts Office of Coastal Zone Management.
  24. Zawada DG, Piniak GA, Hearn CJ (2010) Topographic complexity and roughness of a tropical benthic seascape. Geophys Res Lett 37:L14604CrossRefGoogle Scholar

Copyright information

© US Government 2016

Authors and Affiliations

  • Curt D. Storlazzi
    • 1
  • Peter Dartnell
    • 1
  • Gerald A. Hatcher
    • 1
  • Ann E. Gibbs
    • 1
  1. 1.US Geological SurveyPacific Coastal and Marine Science CenterSanta CruzUSA

Personalised recommendations