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Interdependence of usage band, navigational purpose, scale range, compilation scale and radar range (according to IHO, 2004a and b).
Source publication
The scheme (or footprints) of NOAA Electronic Navigational Charts (ENCs) are based on traditional paper/raster charts from which they were derived. As a result, modernizing current ENC coverage to improve the way they are displayed in a digital environment, increase their level of detail, and incorporate additional survey data outside of the existi...
Contexts in source publication
Context 1
... official IHO recommendation for scale ranges and usage band was published in 2004, several years after some leading HOs had already decided on their own national usage bands and started to compile their ENCs accordingly (IHO, 2004a, b). Two IHO publications that were approved at that time (IHO S-65 and a SCAMIN paper) strongly recommend HOs assign each ENC to a navigational purpose based on the ENC's compilation scale ( Table 1). With that said, the inter-relationship and interaction between usage bands, SCAMIN, and compilation scale are particularly problematic and it is difficult to formulate voluntary guidelines that resolve all of the problems and that are acceptable to all HOs with differing views of these issues (Pharaoh, 2007). ...Context 2
... order for NOAA's charts to comply with international standards, NOAA adopted IHO recommended usage bands with two compilation scales in each usage band (Table 1). However, binary -dependent compilation scales were selected for NOAA's ENCs instead of the compilation scales that are dependent on radar ranges ( Table 3). ...Context 3
... reference fishnet's center of reference is at 0°N and 0°E for each of the usage bands, and it is possible to add more ENC cells to the chart suite by copying the footprint from the fishnet for any location on Earth. The geographic ENC size for each usage band was calculated based on data volume restriction of not being over 5 Mb ( Table 1). In the past, each ENC cell was maintained within its own individual database, which made re-scheming ENCs difficult, but now all NOAA ENCs are maintained within a single, seamless database called the Nautical Information System (NIS). ...Citations
... As new data reflecting changes in seafloor topography are collected, ENCs are updated to reflect this information. New ENCs can also be generated for uncharted regions or when data coverage areas change (Nyberg et al. 2020). Due to the volume of incoming data and resultant time and cost burden associated with managing entire suites of ENCs, automating components of the cartographic generalization process is crucial to maintaining ENC integrity and increasing throughput. ...
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.
... AOI extent, for both an ENC or VNM, should have maximal coverage of the area of interest at the appropriate scale for the purpose (e.g., a port for a berthing chart) (see [59]). Traditionally, nautical chart AOIs are determined by intended use and chart scale [60], but ENCs are recommended to follow a gridded canonical design (see, e.g., [61]). ...
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.
... Depth contours as linear features must not be encoded with a vertex density greater than 0.3 mm at compilation scale [6]. This restriction is further elaborated by United States' National Oceanic and Atmospheric Administration (NOAA) and a threshold of 0.4 mm is proposed [12]. ...
... Based on ENC validation checks [6], the coastline as a line feature must not be encoded at a point density higher than 0.3 mm at compilation scale. This restriction is further elaborated by NOAA and an upper limit of 0.4 mm is proposed [12]. Consequently, the deletion of vertices based on the vertex distance criteria is strongly recommended. ...
... This study addresses scales for harbour and approach nautical charts. The standard set of integer meter depth values for new gridded ENC depth contours [12] are based on depth intervals specified in the IHO S-101 Product Specification [26]. A group of contours (e.g., 2,3,4,5,6,7,8,10,15,20,30,50,100,150,200, 300, 400, and 500 m) is recommended for portrayal at the largest scale (in this case, 1:10 K) and a subset from this initial group is portrayed at smaller scales (see Figure 1). ...
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 mediumscale 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.
