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Object-based classifi cation of cloudy coastal areas using medium-resolution optical and SAR images for vulnerability assessment of marine disaster

  • Fengshuo Yang
  • Xiaomei Yang
  • Zhihua WangEmail author
  • Chen Lu
  • Zhi Li
  • Yueming Liu
Article
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Abstract

Effi cient and accurate access to coastal land cover information is of great signifi cance for marine disaster prevention and mitigation. Although the popular and common sensors of land resource satellites provide free and valuable images to map the land cover, coastal areas often encounter signifi cant cloud cover, especially in tropical areas, which makes the classifi cation in those areas non-ideal. To solve this problem, we proposed a framework of combining medium-resolution optical images and synthetic aperture radar (SAR) data with the recently popular object-based image analysis (OBIA) method and used the Landsat Operational Land Imager (OLI) and Phased Array type L-band Synthetic Aperture Radar (PALSAR) images acquired in Singapore in 2017 as a case study. We designed experiments to confi rm two critical factors of this framework: one is the segmentation scale that determines the average object size, and the other is the classifi cation feature. Accuracy assessments of the land cover indicated that the optimal segmentation scale was between 40 and 80, and the features of the combination of OLI and SAR resulted in higher accuracy than any individual features, especially in areas with cloud cover. Based on the land cover generated by this framework, we assessed the vulnerability of the marine disasters of Singapore in 2008 and 2017 and found that the high-vulnerability areas mainly located in the southeast and increased by 118.97 km 2 over the past decade. To clarify the disaster response plan for diff erent geographical environments, we classifi ed risk based on altitude and distance from shore. The newly increased high-vulnerability regions within 4 km off shore and below 30 m above sea level are at high risk; these regions may need to focus on strengthening disaster prevention construction. This study serves as a typical example of using remote sensing techniques for the vulnerability assessment of marine disasters, especially those in cloudy coastal areas.

Key word

coastal area marine disaster vulnerability assessment remote sensing land use/cover objectbased image analysis (OBIA) 

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Copyright information

© Chinese Society for Oceanology and Limnology, Science Press and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Fengshuo Yang
    • 1
    • 2
  • Xiaomei Yang
    • 1
    • 2
    • 4
  • Zhihua Wang
    • 1
    Email author
  • Chen Lu
    • 1
    • 2
  • Zhi Li
    • 2
    • 3
  • Yueming Liu
    • 1
    • 2
  1. 1.State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
  2. 2.University of Chinese Academy of SciencesBeijingChina
  3. 3.State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and GeographyChinese Academy of SciencesUrumqiChina
  4. 4.Jiangsu Centre for Collaborative Innovation in Geographical Information Resource Development and ApplicationNanjingChina

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