Data-driven approach to benthic cover type classification using bathymetric lidar waveform analysis

Remote Sensing

Volumn 7, Issue 10, 2015, Pages 13390-13409

  Kumpumäki, Teemu ^a   Ruusuvuori, Pekka ^a   Kangasniemi, Ville ^b   Lipping, Tarmo ^a  

^a TAMPERE UNIVERSITY OF TECHNOLOGY   (Finland)

^b Environmental Research and Assessment Enviro Case Ltd   (Finland)

Author keywords

Airborne laser bathymetry; Bathymetric LiDAR; Benthic cover type classification; Pulse waveform modeling; Self organizing map

Indexed keywords

CLUSTER ANALYSIS; CLUSTERING ALGORITHMS; CONFORMAL MAPPING; OPTICAL RADAR; REGRESSION ANALYSIS; SELF ORGANIZING MAPS; WATER QUALITY; WAVEFORM ANALYSIS;

AIRBORNE LASER BATHYMETRIES; BATHYMETRIC LIDARS; BENTHIC COVER; CLUSTERING METHODS; DATA-DRIVEN APPROACH; DATA-DRIVEN METHODS; PULSE WAVEFORMS; SONAR MEASUREMENTS;

BATHYMETRY;

EID: 84945963050     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs71013390     Document Type: Article

References (27)

1. EC. Directive 2008/56/EC of the European Parliament and of the Council: Establishing a framework for community action in the field of marine environmental policy. Off. J. Eur. Union 2008, 51, 19-40.
2. Zavalas, R.; Ierodiaconou, D.; Ryan, D.; Rattray, A.; Monk, J. Habitat classification of temperate marine macroalgal communities using bathymetric LiDAR. Remote Sens. 2014, 6, 2154-2175.
3. Costa, B.; Battista, T.; Pittman, S. Comparative evaluation of airborne LiDAR and ship-based multibeam SoNAR bathymetry and intensity for mapping coral reef ecosystems. Remote Sens. Environ. 2009, 113, 1082-1100.
4. Chust, G.; Grande, M.; Galparsoro, I.; Uriarte, A.; Borja, A. Capabilities of the bathymetric Hawk Eye LiDAR for coastal habitat mapping: A case study within a Basque estuary. Estuar., Coast. Shelf Sci. 2010, 89, 200-213.
5. Tulldahl, H.M.; Vahlberg, C.; Axelsson, A.; Karlsson, H.; Jonsson, P. Sea floor classification from airborne lidar data. Proc. SPIE 2007, 6750, 1-12.
6. Tulldahl, H.M.; Wikström, S. Classification of aquatic macrovegetation and substrates with airborne lidar. Remote Sens. Environ. 2012, 121, 347-357.
7. Collin, A.; Long, B.; Archambault, P. Benthic classifications using bathymetric LIDAR waveforms and integration of local spatial statistics and textural features. J. Coast. Res. 2011, 62, 86-98.
8. Collin, A.; Archambault, P.; Long, B. Predicting species diversity of benthic communities within turbid nearshore using full-waveform bathymetric LiDAR and machine learners. PloS one 2011, 6, e21265.
9. Wang, C.K.; Philpot, W.D. Using airborne bathymetric lidar to detect bottom type variation in shallow waters. Remote Sens. Environ. 2007, 106, 123-135.
10. Posiva Oy. Olkiluoto Biosphere Description 2012; Technical Report 2012-06; Posiva Oy: Eurajoki, Finland, 2013.
11. Rantataro, J. Akustis-seismiset tutkimukset Olkiluodon läheisellä merialueella vuonna 2000; Technical Report 2001-11; Posiva Oy: Eurajoki, Finland, 2001.
12. Rantataro, J.; Kaskela, A. Acoustic Seismic Studies in the Sea Area Close to Olkiluoto in 2008. Technical Report 2009-122; Posiva Oy: Eurajoki, Finland, 2009.
13. Ilmarinen, K.; Leinikki, J.; Oulasvirta, P. Seafloor Mapping at Olkiluoto Western Coast of Finland. Technical Report 2009-12; Posiva Oy: Eurajoki, Finland, 2009.
14. Lindfors, A.; Olli, H.; Joose, M. Vedenlaadun alueellinen jakauma Olkiluodon edustalla heinäkuussa 2008; Technical Report 2008-86; Posiva Oy: Eurajoki, Finland, 2008. (in Finnish)
15. Airborne Hydrography AB. Available online: http://www.airbornehydro.com (accessed on 3 September 2015).
16. Tulldahl, M.; Wikström, S. Initial Report on Statistical Separability of Vegetation and Bottom Types in Laser Data; Technical report; FOI, Swedish Defence Research Agency: Linköping, Sweden, 2010.
17. Jutzi, B.; Stilla, U. Range determination with waveform recording laser systems using a Wiener Filter. ISPRS J. Photogramm. Remote Sens. 2006, 61, 95_107.
18. Wiener, N. Extrapolation, Interpolation, and Smoothing of Stationary Time Series; Wiley: New York, NY, USA, 1949.
19. Abdallah, H.; Baghdadi, N.; Bailly, J.S.; Pastol, Y.; Fabre, F. Wa-LiD: A new LiDAR simulator for waters. IEEE Geosci. Remote Sens. Lett. 2012, 9, 744-748.
20. Le Digabel, S. Algorithm 909: NOMAD: Nonlinear optimization with the MADS algorithm. ACM Trans. Math. Software. 2011, 37, 1-15.
21. Abramson, M.A.; Audet, C.; J. E. Dennis, J.; Le Digabel, S. OrthoMADS: A deterministic MADS instance with orthogonal directions. SIAM J. Optim. 2009, 20, 948-966.
22. Kumpumäki, T.; Lipping, T. A new method for artefact-free estimation of surface slope from LiDAR data. EARSeL eProc. 2014, 13, 1-5.
23. Kohonen, T. Self-Organizing Maps, 3rd ed.; Springer: Berlin, Germany, 2001; p. 501.
24. Vesanto, J.; Alhoniemi, E. Clustering of the self-organizing map. IEEE Trans. Neural Networks 2000, 11, 586-600.
25. Vesanto, J.; Himberg, J.; Alhoniemi, E.; Parhankangas, J. SOM Toolbox for Matlab 5; Libella Oy: Espoo, Finland, 2000.
26. Vesanto, J.; Sulkava, M. Distance matrix based clustering of the Self-Organizing Map. In Proceedings of the 12th International Conference on Artificial Neural Networks, Madrid, Spain, 27-30 August, 2002; Volume 2415, pp. 951-956.
27. Mykkänen, J.; Kiirikki, M.; Lindfors, A. Resuspensio ja kiintoaineen kulkeutuminen Eurajoensalmessa; Technical Report 2012-78; Posiva Oy: Eurajoki, Finland, 2012.