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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

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.

Acknowledgement

Supported by : 한국해양과학기술원

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