Ocean and Polar Research

Korea Institute of Ocean Science & Technology (한국해양과학기술원)
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Comparison between in situ Survey and Satellite Imagery with Regard to Coastal Habitat Distribution Patterns in Weno, Micronesia

마이크로네시아 웨노섬 연안 서식지 분포의 현장조사와 위성영상 분석법 비교

  • 김태훈 (한국해양과학기술원 태평양해양연구센터) ;
  • 최영웅 (한국해양과학기술원 태평양해양연구센터) ;
  • 최종국 (한국해양과학기술원 해양위성센터) ;
  • 권문상 (한국해양과학기술원 해양정책연구소) ;
  • 박흥식 (한국해양과학기술원 태평양해양연구센터)
  • Received : 2013.09.16
  • Accepted : 2013.11.17
  • Published : 2013.12.30
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Abstract

The aim of this study is to suggest an optimal survey method for coastal habitat monitoring around Weno Island in Chuuk Atoll, Federated States of Micronesia (FSM). This study was carried out to compare and analyze differences between in situ survey (PHOTS) and high spatial satellite imagery (Worldview-2) with regard to the coastal habitat distribution patterns of Weno Island. The in situ field data showed the following coverage of habitat types: sand 42.4%, seagrass 26.1%, algae 14.9%, rubble 8.9%, hard coral 3.5%, soft coral 2.6%, dead coral 1.5%, others 0.1%. The satellite imagery showed the following coverage of habitat types: sand 26.5%, seagrass 23.3%, sand + seagrass 12.3%, coral 18.1%, rubble 19.0%, rock 0.8% (Accuracy 65.2%). According to the visual interpretation of the habitat map by in situ survey, seagrass, sand, coral and rubble distribution were misaligned compared with the satellite imagery. While, the satellite imagery appear to be a plausible results to identify habitat types, it could not classify habitat types under one pixel in images, which in turn overestimated coral and rubble coverage, underestimated algae and sand. The differences appear to arise primarily because of habitat classification scheme, sampling scale and remote sensing reflectance. The implication of these results is that satellite imagery analysis needs to incorporate in situ survey data to accurately identify habitat. We suggest that satellite imagery must correspond with in situ survey in habitat classification and sampling scale. Subsequently habitat sub-segmentation based on the in situ survey data should be applied to satellite imagery.

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References

  1. Andrefouet S, Kramer P, Torres-Pulliza D, Joyce KE, Hochberg EJ, Garza-Pérez R, Mumby PJ, Riegl B, Yamano H, White WH, Zubia M, Brock JC, Phinn SR, Naseer A, Hatcher BG, Muller-Karger FE (2003) Multisite evaluation of IKONOS data for classification of tropical coral reef environments. Remote Sens Environ 88:128-143 https://doi.org/10.1016/j.rse.2003.04.005
  2. English S, Wilkinson CR, Baker C (1994) Survey Manual for Tropical Marine Resources. Australian Institute of Marine Science, Townsville, 390 p
  3. Green EP, Mumby PJ, Edwards AJ, Clark CD (2000) Remote sensing handbook for tropical coastal management. UNESCO, Paris, 316 p
  4. Hochberg EJ, Atkinson M (2003) Capabilities of remote sensors to classify coral, algae and sand as pure and mixed spectra. Remote Sens Environ 85:174-189 https://doi.org/10.1016/S0034-4257(02)00202-X
  5. Hochberg EJ (2011) Remote Sensing of Coral Reef Processes. In: Zvy D, Noga S (eds) Coral Reefs: An Ecosystem in Transition. Springer, pp 25-35
  6. Jonker M, Johns K, Osbourne K (2008) Surveys of benthic reef communities using underwater digital photography and counts of juvenile corals. Long-term Monitoring of the Great Barrier Reef. Australian Institute of Marine Science, Townsville, 75 p
  7. Joyce KE, Phinn SR, Roelfsema CM, Neil DT, Dennison WC (2004) Combining Landsat ETM+ and Reef Check classifications for mapping coral reefs: a critical assessment from the southern Great Barrier Reef, Australia. Coral Reefs 23:21-25 https://doi.org/10.1007/s00338-003-0357-7
  8. Knudby A, Roelfsema C, Lyons M, Phinn S, Jupiter S (2011) Mapping fish community variables by intergrating field and satellite data, object-based image analysis and modeling in a traditional Fijian fisheries management area. Remote Sens 3:460-483 https://doi.org/10.3390/rs3030460
  9. Kuster T, Jupp DLB (2006) On the possibility of mapping living corals to the species level based on their optical signatures. Estuar Coast Shelf Sci 69:607-614 https://doi.org/10.1016/j.ecss.2006.05.026
  10. Lam K, Shin PKS, Bradbeer R, Randall D, Ku KKK, Hodgson P, Cheung SG (2006) A comparison of video and point intercept transect methods for monitoring subtropical coral communities. J Exp Mar Biol Ecol 333:115-128 https://doi.org/10.1016/j.jembe.2005.12.009
  11. Lyons M, Phinn S, Roelfsema C (2011) Integrating Quickbird Multi-Spectral Satellite and Field Data: Mapping Bathymetry, Seagrass Cover, Seagrass Species and Change in Moreton Bay, Australia in 2004, 2007. Remote Sens 3:42-64 https://doi.org/10.3390/rs3010042
  12. Min JE, Ryu JH, Choi JK, Park HS (2010) Coral reef habitat monitoring using high-spatial satellite imagery: A case study from Chuuk lagoon in FSM. Ocean and Polar Res 32(1):53-61 https://doi.org/10.4217/OPR.2010.32.1.053
  13. Mumby PJ, Edwards AJ (2002) Mapping marine environments with IKONOS imagery: Enhanced spatial resolution can deliver greater thematic accuracy. Remote Sens Environ 82:248-257 https://doi.org/10.1016/S0034-4257(02)00041-X
  14. Mumby PJ, Green EP, Edwards AJ, Clark CD (1997) Coral reef habitat mapping: how much detail can remote sensing provide? Mar Biol 130:193-202 https://doi.org/10.1007/s002270050238
  15. Palandro DA, Andrefouet S, Hu C, Hallock P, Muller-Karger FE, Dustan P, Callahan MK, Kranenburg C, Beaver CR (2008) Quantification of two decades of shallow-water coral reef habitat decline in the Florida Keys National Marine Sanctuary using Landsat data (1984-2002). Remote Sens Environ 112:3388-3399 https://doi.org/10.1016/j.rse.2008.02.015
  16. Roelfsema C, Phinn S (2009) A Manual for Conducting Georeferenced Photo Transects Surveys to Assess the Benthos of Coral Reef and Seagrass Habitats. Centre for Remote Sensing & Spatial Information Science School of Geography, Planning & Environmental Management. University of Queensland, Australia
  17. Roelfsema C, Phinn S, Comley J (2007) Mapping benthic habitats on Fijian coral reefs: Evaluating combined field and remote sensing approaches. In: Proceedings of the Asian Conference on Remote Sensing. The 28th Asian Conference on Remote Sensing, Kuala Lumpur, Malaysia, pp 12-16
  18. Roelfsema C, Phinn S, Jupiter S, Comley J, Beger M, Paterson E (2010) The application of object based analysis of high spatial resolution imagery for mapping large coral reef systems in the West Pacific at geomorphic and benthic community spatial scales. In: Geosicience and Remote Sensing Symposium (IGARSS), Honolulu, Hawaii, USA, 25-30 July 2010
  19. Scopelitis J, Andrefouet S, Phinn S, Arroyo L, Dalleau M, Cros A, Chabanet P (2010) The next step in shallow coral reef monitoring: Combining remote sensing and in situ approaches. Mar Pollut Bull 60:1958-1968
  20. Scopelitis J, Andrefouet S, Phinn S, Chabanet P, Naim O, Tourrand C, Done T (2009) Changes of coral communities over 35 years: Integrating in situ and remote-sensing data on Saint-Leu Reef (la Reuniton, Indian Ocean). Estuar Coast Shelf Sci 84:342-352 https://doi.org/10.1016/j.ecss.2009.04.030
  21. Short FT, Short CA (1984) The Seagrass Filter: Purification of Estuarine and Coastal Water. In: Kennedy VS (ed) The Estuary as a Filter. Academic Press, Orlando, pp 395-413
  22. Smith VE, Togers RH, Reed LE (1975) Automated mapping and inventory of Great Barrier Reef zonation with Landsat data. In: Ocean 75 conference record. Institute of Electrical and Eletronics Engineers, Inc, New York, pp 775-780
  23. Stevenson JC (1988) Comparative ecology of submersed grass beds in freshwater, estuarine and marine environments. Limnol Oceanogr 33:867-893 https://doi.org/10.4319/lo.1988.33.4_part_2.0867
  24. Wilkinson C (2008) Status of Coral Reef of the World: 2008. Global Coral Reef Monitoring Network and Reef and Rainforest Research Centre, Townsville, Australia
  25. Yamano H, Tamura M (2004) Detection limits of coral reef bleaching by satellite remote sensing: simulation and data analysis. Remote Sens Environ 90:86-103 https://doi.org/10.1016/j.rse.2003.12.005

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