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Towards an automated chart-ready cartographic sounding selection

Authors:
Noel M. Dyer at National Oceanic and Atmospheric Administration
Noel M. Dyer
Christos Kastrisios at University of New Hampshire
Christos Kastrisios
Leila De Floriani
Leila De Floriani
Leila De Floriani
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Abstract and Figures

Cartographic sounding selection, the process of identifying navigationally relevant soundings for chart-display, is a time-consuming generalization process in the chart production workflow. Advances in bathymetric data collection and processing techniques are resulting in higher resolution data, which compounds the bottleneck of sounding selection. Thus, a comprehensive algorithm for generating a chart-ready set of soundings that adheres to cartographic constraints could vastly decrease the time from data collection to chart dissemination. Towards this goal, this work presents enhancements to our label-based hydrographic sounding selection (Dyer et al., 2022) and methods for identifying soundings for chart display. Enhancements to the hydrographic sounding selection algorithm include a method for cartographically generalizing Category Zone of Confidence (CATZOC) polygons (MQUALs), utilizing said generalized polygons for a constrained triangulation during validation, and an adjustment procedure to eliminate functionality (safety) constraint violations. This results in a hydrographic selection with zero functionality violations, albeit at the expense of legibility, where the introduced overlapping labels are handled later when deriving the chart-ready selection. The hydrographic sounding selection results serve as input to our cartographic sounding selection process that begins with defining the types of soundings found on nautical charts: least depth, critical, deep, supportive, and fill soundings. We present a method to extract these soundings based on analyzing the surface model of the hydrographic selection, the associated survey CATZOC value, and existing chart features.
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Towards an automated chart-ready cartographic sounding selection
Dyer, Noel1,2, Kastrisios, Christos3, De Floriani, Leila2
1 Office of Coast Survey, National Oceanic and Atmospheric Administration, USA
2 Department of Geographical Sciences, University of Maryland – College Park, USA
3 Center for Coastal & Ocean Mapping, University of New Hampshire, USA
Noel.Dyer@noaa.gov
Cartographic sounding selection, the process of identifying navigationally relevant soundings for
chart-display, is a time-consuming generalization process in the chart production workflow. Advances in
bathymetric data collection and processing techniques are resulting in higher resolution data, which
compounds the bottleneck of sounding selection. Thus, a comprehensive algorithm for generating a chart-
ready set of soundings that adheres to cartographic constraints could vastly decrease the time from data
collection to chart dissemination. Towards this goal, this work presents enhancements to our label-based
hydrographic sounding selection (Dyer et al., 2022) and methods for identifying soundings for chart display.
Enhancements to the hydrographic sounding selection algorithm include a method for
cartographically generalizing Category Zone of Confidence (CATZOC) polygons (MQUALs), utilizing said
generalized polygons for a constrained triangulation during validation, and an adjustment procedure to
eliminate functionality (safety) constraint violations. This results in a hydrographic selection with zero
functionality violations, albeit at the expense of legibility, where the introduced overlapping labels are
handled later when deriving the chart-ready selection.
The hydrographic sounding selection results serve as input to our cartographic sounding selection
process that begins with defining the types of soundings found on nautical charts: least depth, critical, deep,
supportive, and fill soundings. We present a method to extract these soundings based on analyzing the surface
model of the hydrographic selection, the associated survey CATZOC value, and existing chart features
(Figure).
Figure. Example of current workflow.
Reference
Dyer, N., Kastrisios, C., De Floriani, L. (2022). Label-based generalization of bathymetry data for
hydrographic sounding selection. Cartography and Geographic Information Science, 1–16.
https://doi.org/10.1080/15230406.2021.2014974
... Sounding selection, for example, is the identification of spot depths for a nautical chart. Only an algorithm cognizant of other charted bathymetric features (e.g., wrecks, rocks, obstructions, depth curves), as well as the final cartographic model, may yield acceptable outputs [15,32]. When the relevant chart features and/or the cartographic model (e.g., sounding label size and dimensions) are not considered by the automation algorithm, the adjustments that the cartographers must make may lead to a considerably different sounding selection, consequently, reducing their trust on the tool. ...
... With the aim to contribute to the efforts for expanding the holistic automated generalization approaches to the maritime domain, reduce the compilation time of fundamental chart features (land areas, depth areas and contours, soundings, buildings) and develop ENC-like products for applications beyond nautical charting, this work reviews available data sources and investigates the integration, testing, and improvement of existing generalization approaches. The work builds upon the professional experience of authors with nautical charting workflows and their research efforts to automate data collection [47] and individual data generalization tasks [15,32], to validate chart data requirements [6,35,[48][49][50][51][52], to model the nautical chart compilation workflow and generalize ENC Skin-of-the-Earth features with no topological errors [34], to shed light and gain knowledge on the capabilities of free and open software for use in ocean mapping workflows [53,54], to build innovative chart symbology [8,46,[55][56][57][58] and custom chart web services [45]. ...
... The method is product driven, and the only parameter required is the scale of the final product. The hydrographic sounding selection is combined with the bathymetry surrounding the study area and converted into a TIN surface model using a Delaunay triangulation of the points; maxima points correspond to the shallow soundings, minima to deep soundings, and saddles to supportive soundings [32] (Figure 3). The benefit of using the Hydrographic Sounding Selection for the surface critical points extraction (rather than working on the source bathymetric data) is that it sets the neighborhood distance based on product driven criteria (i.e., the scale of the chart) rather than an arbitrary user-defined search (neighborhood) distance. ...
Increasing Efficiency of Nautical Chart Production and Accessibility to Marine Environment Data through an Open-Science Compilation Workflow
Article
Full-text available
  • Mar 2023
  • ISPRS
Electronic Navigational Chart (ENC) data are essential for safe maritime navigation and have multiple other uses in a wide range of enterprises. Charts are relied upon to be as accurate and as up-to-date as possible by the vessels moving vast amounts of products to global ports each year. However, cartographic generalization processes for updating and creating ENCs are complex and time-consuming. Increasing the efficiency of the chart production workflow has been long sought by the nautical charting community. Toward this effort, approaches must consider intended scale, data quality, various chart features, and perform consistently in different scenarios. Additionally, supporting open-science initiatives through standardized open-source workflows will increase marine data accessibility for other disciplines. Therefore, this paper reviews, improves, and integrates available open-source software, and develops new custom generalization tools, for the semi-automated processing of land and hydrographic features per nautical charting specifications. The ro-bustness of this approach is demonstrated in two areas of very different geographic configurations and the effectiveness for use in nautical charting was confirmed by winning the first prize in an international competition. The presented rapid data processing combined with the ENC portrayal of results as a web-service provides new opportunities for applications such as the development of base-maps for marine spatial data infrastructures.
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