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Multi-Spectral Ship Detection Using Optical, Hyperspectral, and Microwave SAR Remote Sensing Data in Coastal Regions

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  • Kyung-Ae Park

    (Department of Earth Science Education/Research Institute of Oceanography, Seoul National University, Seoul 08826, Korea)

  • Jae-Jin Park

    (Department of Science Education, Seoul National University, Seoul 151-748, Korea)

  • Jae-Cheol Jang

    (Department of Science Education, Seoul National University, Seoul 151-748, Korea)

  • Ji-Hyun Lee

    (Department of Science Education, Seoul National University, Seoul 151-748, Korea)

  • Sangwoo Oh

    (Maritime Safety Research Division, Korea Research Institute of Ships and Ocean engineering, Daejeon 34103, Korea)

  • Moonjin Lee

    (Maritime Safety Research Division, Korea Research Institute of Ships and Ocean engineering, Daejeon 34103, Korea)

Abstract

The necessity of efficient monitoring of ships in coastal regions has been increasing over time. Multi-satellite observations make it possible to effectively monitor vessels. This study presents the results of ship detection methodology, applied to optical, hyperspectral, and microwave satellite images in the seas around the Korean Peninsula. Spectral matching algorithms are used to detect ships using hyperspectral images with hundreds of spectral channels and investigate the similarity between the spectra and in-situ measurements. In the case of SAR (Synthetic Aperture Radar) images, the Constant False Alarm Rate (CFAR) algorithm is used to discriminate the vessels from the backscattering coefficients of Sentinel-1B SAR and ALOS-2 PALSAR2 images. Validation results exhibited that the locations of the satellite-detected vessels showed good agreement with real-time location data within the Sentinel-1B coverage in the Korean coastal region. This study presented the probability of detection values of optical and SAR-based ship detection and discussed potential causes of the errors. This study also suggested a possibility for real-time operational use of vessel detection from multi-satellite images based on optical, hyperspectral, and SAR remote sensing, particularly in the inaccessible coastal regions off North Korea, for comprehensive coastal management and sustainability.

Suggested Citation

  • Kyung-Ae Park & Jae-Jin Park & Jae-Cheol Jang & Ji-Hyun Lee & Sangwoo Oh & Moonjin Lee, 2018. "Multi-Spectral Ship Detection Using Optical, Hyperspectral, and Microwave SAR Remote Sensing Data in Coastal Regions," Sustainability, MDPI, vol. 10(11), pages 1-23, November.
  • Handle: RePEc:gam:jsusta:v:10:y:2018:i:11:p:4064-:d:180925
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    References listed on IDEAS

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