Coral Reefs

, Volume 36, Issue 1, pp 269–275 | Cite as

Mapping coral reefs using consumer-grade drones and structure from motion photogrammetry techniques

  • Elisa CasellaEmail author
  • Antoine Collin
  • Daniel Harris
  • Sebastian Ferse
  • Sonia Bejarano
  • Valeriano Parravicini
  • James L. Hench
  • Alessio Rovere


We propose a novel technique to measure the small-scale three-dimensional features of a shallow-water coral reef using a small drone equipped with a consumer-grade camera, a handheld GPS and structure from motion (SfM) algorithms. We used a GoPro HERO4 with a modified lens mounted on a DJI Phantom 2 drone (maximum total take-off weight <2 kg) to perform a 10 min flight and collect 306 aerial images with an overlap equal or greater than 90%. We mapped an area of 8380 m2, obtaining as output an ortho-rectified aerial photomosaic and a bathymetric digital elevation model (DEM) with a resolution of 0.78 and 1.56 cm pixel−1, respectively. Through comparison with airborne LiDAR data for the same area, we verified that the location of the ortho-rectified aerial photomosaic is accurate within ~1.4 m. The bathymetric difference between our DEM and the LiDAR dataset is −0.016 ± 0.45 m (1σ). Our results show that it is possible, in conditions of calm waters, low winds and minimal sun glint, to deploy consumer-grade drones as a relatively low-cost and rapid survey technique to produce multispectral and bathymetric data on shallow-water coral reefs. We discuss the utility of such data to monitor temporal changes in topographic complexity of reefs and associated biological processes.


Drone mapping Coral reefs Bathymetry from drones Structure from motion underwater Bathymetry from photogrammetry 



This research was supported by the Institutional Strategy of the University of Bremen, funded by the German Excellence Initiative (ABPZuK-03/2014) and by ZMT, the Leibniz Center for Tropical Marine Ecology, Bremen. We acknowledge the Centre de Recherches Insulaires et Observatoire de l’Environnement (CRIOBE) for support during the field data collection. The airborne LiDAR measurements and analysis were supported by the US National Science Foundation grants OCE1435133 (Physical Oceanography) as well as OCE1236905 and OCE1637396 (Moorea Coral Reef LTER). We acknowledge useful assessments and corrections from two anonymous reviewers as well as the journal editor.

Supplementary material

338_2016_1522_MOESM1_ESM.docx (1.4 mb)
Supplementary material 1 (DOCX 1473 kb)


  1. Alvarez-Filip L, Gill JA, Dulvy NK, Perry AL, Watkinson AR, Côté IM (2011) Drivers of region wide declines in architectural complexity on Caribbean reefs. Coral Reefs 30:1051–1060CrossRefGoogle Scholar
  2. Bejarano S, Mumby PJ, Sotheran I (2011) Predicting structural complexity of reefs and fish abundance using acoustic remote sensing (RoxAnn). Mar Biol 158:489–504CrossRefGoogle Scholar
  3. Bryson M, Duce S, Harris D, Webster JM, Thompson A, Vila-Concejo A, Williams SB (2016) Geomorphic changes of a coral shingle cay measured using kite aerial photography. Geomorphology 270:1–8CrossRefGoogle Scholar
  4. Casella E, Rovere A, Pedroncini A, Stark CP, Casella M, Ferrari M, Firpo M (2016) Drones as tools for monitoring beach topography changes in the Ligurian Sea (NW Mediterranean). Geo-Mar Lett 36:151–163CrossRefGoogle Scholar
  5. Casella E, Rovere A, Pedroncini A, Mucerino L, Casella M, Cusati AL, Vacchi M, Ferrari M, Firpo M (2014) Study of wave runup using numerical models and low-altitude aerial photogrammetry: a tool for coastal management. Estuar Coast Shelf Sci 149:160–167CrossRefGoogle Scholar
  6. Chirayath V, Earle S (2016) Drones that see through waves—preliminary results from airborne fluid lensing for centimetre-scale aquatic conservation. Aquat Conserv 26:237–250CrossRefGoogle Scholar
  7. Collin A, Archambault P, Planes S (2014) Revealing the regime of shallow coral reefs at patch scale by continuous spatial modeling. Front Mar Sci 1:65CrossRefGoogle Scholar
  8. Costa BM, Battista TA, Pittman SJ (2009) Comparative evaluation of airborne LiDAR and ship-based multibeam SoNAR bathymetry and intensity for mapping coral reef ecosystems. Remote Sens Environ 113:1082–1100CrossRefGoogle Scholar
  9. Duffy JP, Anderson K (2016) A 21st-century renaissance of kites as platforms for proximal sensing. Prog Phys Geogr 40:352–361CrossRefGoogle Scholar
  10. Ferrario F, Beck MW, Storlazzi CD, Micheli F, Shepard CC, Airoldi L (2014) The effectiveness of coral reefs for coastal hazard risk reduction and adaptation. Nat Commun 5:3794CrossRefPubMedPubMedCentralGoogle Scholar
  11. Flynn KF, Chapra SC (2014) Remote sensing of submerged aquatic vegetation in a shallow non-turbid river using an unmanned aerial vehicle. Remote Sens 6:12815–12836CrossRefGoogle Scholar
  12. Graham NA (2014) Habitat complexity: coral structural loss leads to fisheries declines. Curr Biol 24:R359–R361CrossRefPubMedGoogle Scholar
  13. Graham NAJ, Nash KL (2013) The importance of structural complexity in coral reef ecosystems. Coral Reefs 32:315–326CrossRefGoogle Scholar
  14. Graham NA, Jennings S, MacNeil MA, Mouillot D, Wilson SK (2015) Predicting climate-driven regime shifts versus rebound potential in coral reefs. Nature 518:94–97CrossRefPubMedGoogle Scholar
  15. Hedley J, Roelfsema C, Chollett I, Harborne A, Heron S, Weeks S, Skirving W, Strong A, Eakin C, Christensen T, Ticzon V, Bejarano S, Mumby P (2016) Remote sensing of coral reefs for monitoring and management: a review. Remote Sens 8:118CrossRefGoogle Scholar
  16. Lesser MP, Mobley CD (2007) Bathymetry, water optical properties, and benthic classification of coral reefs using hyperspectral remote sensing imagery. Coral Reefs 26:819–829CrossRefGoogle Scholar
  17. Lugo-Fernández A, Roberts HH, Suhayda JN (1998) Wave transformations across a Caribbean fringing-barrier coral reef. Cont Shelf Res 18:1099–1124CrossRefGoogle Scholar
  18. Madin EM, Madin JS, Booth DJ (2011) Landscape of fear visible from space. Sci Rep 1:14CrossRefPubMedPubMedCentralGoogle Scholar
  19. Mumby PJ (2016) Stratifying herbivore fisheries by habitat to avoid ecosystem overfishing of coral reefs. Fish Fish 17:266–278CrossRefGoogle Scholar
  20. Mumby PJ, Green EP, Edwards AJ, Clark CD (1997) Coral reef habitat mapping: how much detail can remote sensing provide? Mar Biol 130:193–202CrossRefGoogle Scholar
  21. Normile D (2016) El Niño’s warmth devastating reefs worldwide. Science 352:15–16CrossRefPubMedGoogle Scholar
  22. Richter C, Wunsch M (1999) Cavity-dwelling suspension feeders in coral reefs—a new link in reef trophodynamics. Mar Ecol Prog Ser 188:105–116CrossRefGoogle Scholar
  23. Rogers A, Blanchard JL, Mumby PJ (2014) Vulnerability of coral reef fisheries to a loss of structural complexity. Curr Biol 24:1000–1005CrossRefPubMedGoogle Scholar
  24. Sheppard C, Dixon DJ, Gourlay M, Sheppard A, Payet R (2005) Coral mortality increases wave energy reaching shores protected by reef flats: examples from the Seychelles. Estuar Coast Shelf Sci 64:223–234CrossRefGoogle Scholar
  25. Szmant AM (1997) Nutrient effects on coral reefs: a hypothesis on the importance of topographic and trophic complexity to reef nutrient dynamics. Proc 8th Int Coral Reef Symp 2:1527–1532Google Scholar
  26. Witze A (2016) Marine ecologists take to the skies to study coral reefs. Nature 534:13–14CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.ZMT, Leibniz Center for Tropical Marine EcologyBremenGermany
  2. 2.EPHE—Ecole Pratique des Hautes EtudesDinardFrance
  3. 3.MARUMUniversity of BremenBremenGermany
  4. 4.Nicholas School of the EnvironmentDuke UniversityBeaufortUSA
  5. 5.Lamont Doherty Earth ObservatoryColumbia UniversityNew YorkUSA
  6. 6.Ecole Pratique des Hautes Etudes, ParisSciences et Lettres Research University, Université de PerpignanPerpignanFrance
  7. 7.Laboratoire d’ExcellenceCORAILPerpignanFrance

Personalised recommendations