Image-based continental shelf habitat mapping using novel automated data extraction techniques

Continental Shelf Research

Volumn 45, Issue , 2012, Pages 87-97

  Seiler, Jan ^a,b   Friedman, Ariell ^c   Steinberg, Daniel ^c   Barrett, Neville ^a,b   Williams, Alan ^b   Holbrook, Neil J ^a  

^a UNIVERSITY OF TASMANIA   (Australia)

^b CSIRO   (Australia)

^c UNIVERSITY OF SYDNEY   (Australia)

Author keywords

Habitat predictors; Habitat variability; Monitoring; Random forests; Sirius; Tasmania

Indexed keywords

ACCURACY ASSESSMENT; ALGORITHM; AUTOMATION; AUTONOMOUS UNDERWATER VEHICLE; COLOR; CONTINENTAL SHELF; COST-BENEFIT ANALYSIS; FISHING EFFORT; IMAGE CLASSIFICATION; PATCHINESS; SAMPLING; SEAFLOOR; SPATIAL DISTRIBUTION; TEXTURE;

AUSTRALIA; TASMANIA;

EID: 84865045311     PISSN: 02784343     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.csr.2012.06.003     Document Type: Article

References (25)

1. Allmon W.D., Jones D., Aiello R.L., Gowlett-Holmes K., Probert P.K. Observations on the biology of Maoricolpus roseus (Quoy and Gaimard), Prosobranchia: Turritellidae from New Zealand and Tasmania. The Veliger 1994, 37:267-279.
2. Barrett, N.S., Sanderson, J.C., Lawler, M.M., Halley, V., Jordan, A.R., 2001. Mapping of Inshore Marine Habitats in South-Eastern Tasmania for Marine Protected Area Planning and Marine Management. Technical Report. Tasmanian Aquaculture and Fisheries Institute, Hobart.
3. Breiman L. Random forests. Machine Learning 2001, 45:5-32.
4. Breiman, L., 2002. Manual on Setting Up, Using, and Understanding Random Forests. v3.1.
5. Fleiss J.L. Measuring nominal scale agreement among many raters. Psychological Bulletin 1971, 76:378-382.
6. Friedman A. Rugosity, Slope and Aspect Derived from Bathymetric Stereo Image 3D Reconstructions 2010, Ocean Engineering Society Poster Competition, Sydney.
7. Gwet K. Statistical Tables for Inter-Rater Agreement 2001, StatAxis, Gaithersburg.
8. Holmes K.W., Van Niel K.P., Radford B., Kendrick G.A., Grove S.L. Modelling distribution of marine benthos from hydroacoustics and underwater video. Continental Shelf Research 2008, 28:1800-1810.
9. Jensen J.R. Introductory digital image processing 2004, Pearson Prentice Hall, New Jersey, 544 p. third edition.
10. Landis J.R., Koch G.G. The measurement of observer agreement for categorical data. Biometrics 1977, 33:159-174.
11. Liaw A., Wiener M. Classification and Regression by randomForest. R News 2002, 2:18-22.
12. Lucieer V.L. Object-oriented classification of sidescan sonar data for mapping benthic marine habitats. International Journal of Remote Sensing 2008, 29:905-921.
13. Min R., Cheng H.D. Effective image retrieval using dominant color descriptor and fuzzy support vector machine. Pattern Recognition 2009, 42:147-157.
14. Nichol, S.L., Anderson, T.J., McArthur, M., Barrett, N., Heap, A.D., Siwabessy, P.J.W., Brooke, B., 2009. Southeast Tasmania Temperate Reef Survey. Post-Survey Report. June 13-26, 2008 and February 23-March 14, 2009. Geoscience Australia, Canberra, Australia.
15. Ojala T., Pietikäinen M., Mäenpää T. Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence 2002, 971-987.
16. Pal M., Mather P.M. An assessment of the effectiveness of decision tree methods for land cover classification. Remote Sensing of Environment 2003, 86:554-565.
17. Piepenburg D., Schmid M.K. A photographic survey of the epibenthic megafauna of the Arctic Laptev Sea shelf: distribution, abundance, and estimates of biomass and organic carbon demand. Marine Ecology Progress Series 1997, 147:63-75.
18. Purser A., Bergmann M., Lundälv T., Ontrup J., Nattkemper T.W. Use of machine-learning algorithms for the automated detection of cold-water coral habitats: a pilot study. Marine Ecology Progress Series 2009, 397:241-251.
19. R Development Core Team, 2008. R: A Language and Environment for Statistical Computing. http://www.r-project.org/.
20. Rattray A., Ierodiaconou D., Laurenson L., Burq S., Reston M. Hydro-acoustic remote sensing of benthic biological communities on the shallow South East Australian continental shelf. Estuarine, Coastal and Shelf Science 2009, 84:237-245.
21. Rhoads D.C., Germano J.D. Characterization of organism-sediment relations using sediment profile imaging: an efficient method of remote ecological monitoring of the seafloor (REMOTS™ System). Marine Ecology Progress Series 1982, 8:115-128.
22. Singh H., Can A., Eustice R., Lerner S., McPhee N., Pizarro O., Roman C. SeaBED AUV offers new platform for high-resolution imaging. EOS 2004, 85:294-295.
23. Singh H., Armstrong R., Gilbes F., Eustice R., Roman C., Pizarro O., Torres J. Imaging coral I: imaging coral habitats with the SeaBED AUV. Subsurface Sensing Technologies and Applications 2004, 5:25-42.
24. Williams, S.B., Pizarro, O., Mahon, I., Johnson-Roberson, M., 2008. Simultaneous localisation and mapping and dense stereoscopic seafloor reconstruction using an AUV. In: Proceedings of the International Symposium on Experimental Robotics, Athens.
25. Williams, S.B., Pizarro, O., Jakuba, M., Barrett, N.S., 2010. AUV benthic habitat mapping in South Eastern Tasmania. In: Proceedings of the 7th International Conference in Field and Service Robotics, Springer Berlin, pp. 275-284.