Depth Contours and Coastline Generalization for Harbour and Approach Nautical Charts
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Depth Contours and Coastline Generalization for Harbour and Approach Nautical Charts

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Details:

  • Journal Title:
    ISPRS International Journal of Geo-Information
  • Personal Author:
  • NOAA Program & Office:
  • Description:
    Generalization of nautical charts and electronic nautical charts (ENCs) is a critical process which aims at the safety of navigation and clear cartographic presentation. This paper elaborates on the problem of depth contours and coastline generalization—natural and artificial—for medium-scale charts (harbour and approach) taking into account International Hydrographic Organization (IHO) standards, hydrographic offices’ (HOs) best practices and cartographic literature. Additional factors considered are scale, depth, and seafloor characteristics. The proposed method for depth contour generalization utilizes contours created from high-resolution digital elevation models (DEMs) or those already portrayed on nautical charts. Moreover, it ensures consistency with generalized soundings. Regarding natural coastline generalization, the focus was on managing the resolution, while maintaining the shape, and on the islands. For the provision of a suitable generalization solution for the artificial shoreline, it was preprocessed in order to automatically recognize the shape of each structure as perceived by humans (e.g., a pier that looks like a T). The proposed generalization methodology is implemented with custom-developed routines utilizing standard geo-processing functions available in a geographic information system (GIS) environment and thus can be adopted by hydrographic agencies to support their ENC and nautical chart production. The methodology has been tested in the New York Lower Bay area in the U.S.A. Results have successfully delineated depth contours and coastline at scales 1:10 K, 1:20 K, 1:40 K and 1:80 K.
  • Keywords:
  • Source:
    ISPRS International Journal of Geo-Information, 10(4), 197
  • DOI:
  • ISSN:
    2220-9964
  • Publisher:
    MDPI AG
  • Document Type:
    Journal Article
  • Funding:
    Grant no. NA15NOS4000200
  • License:
  • Rights Information:
    CC BY
  • Compliance:
    Library
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  • File Type:

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