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Abstract
Cartographic sounding selection is a constraint-based bathymetric generalization process for identifying navigationally relevant soundings for nautical chart display. Electronic Navigational Charts (ENCs) are the premier maritime navigation medium and are produced according to international standards and distributed around the world. Cartographic generalization for ENCs is a major bottleneck in the chart creation and update process, where high volumes of data collected from constantly changing seafloor topographies require tedious examination. Moreover, these data are provided by multiple sources from various collection platforms at different levels of quality, further complicating the generalization process. Therefore, in this work, a comprehensive sounding selection algorithm is presented that focuses on safe navigation, leveraging both the Digital Surface Model (DSM) of multi-source bathymetry and the cartographic portrayal of the ENC. A taxonomy and hierarchy of soundings found on ENCs are defined and methods to identify these soundings are employed. Furthermore, the significant impact of depth contour generalization on sounding selection distribution is explored. Incorporating additional ENC bathymetric features (rocks, wrecks, and obstructions) affecting sounding distribution, calculating metrics from current chart products, and introducing procedures to correct cartographic constraint violations ensures a shoal-bias and mariner-readable output. This results in a selection that is near navigationally ready and complementary to the specific waterways of the area, contributing to the complete automation of the ENC creation and update process for safer maritime navigation.
Publication Date
5-11-2023
Journal Title
Geo-spatial Information Science
Rights
© 2023 Wuhan University.
Publisher
Taylor & Francis
Digital Object Identifier (DOI)
Document Type
Article
Recommended Citation
Dyer, N., Kastrisios, C., & De Floriani, L. (2023). Chart features, data quality, and scale in cartographic sounding selection from composite bathymetric data. Geo-Spatial Information Science, 27(5), 1542–1567. https://doi.org/10.1080/10095020.2023.2266222
Comments
This is an open access article published by Taylor & Francis in Geo-spatial Information Science in 2023, available online: https://dx.doi.org/10.1080/10095020.2023.2266222