Automated islands generalization techniques for nautical charts

Land is one of the most prominent geo-features in marine navigation for passage planning and execution. Land generalization for nautical charting, and particularly that of smaller landmasses (islands), is a task performed manually by cartographers based on available specifications and their own experience. Existing methods for automated island selection utilize the Voronoi diagram or weighted buffers to calculate island density and remove islands in dense regions. Their main deficiency is that they do not consider other related chart features, while they may also incorrectly represent the density and distribution of islands and the detection of isolated ones in the process. As such, islands that pose navigational significance and would be retained by a professional cartographer may be removed by the algorithm and vice versa. These drawbacks restrict their use as they present difficulties in achieving the product requirements. This paper presents an island generalization method that combines the benefits of Voronoi and buffer approaches, while it incorporates relevant other chart feature classes to respect topology relations and, with island shape recognition, to categorize islands on a hierarchy level for making generalization decisions. This innovative approach enhances the effectiveness and accurate presentation of islands on nautical charts through automated generalization.

Authors

Institutions

Publication Details

Journal
Geo-spatial Information Science
Published
2025-10-29
DOI
https://doi.org/10.1080/10095020.2025.2568115
Primary Topic
Historical Geography and Cartography
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Automated islands generalization techniques for nautical charts

Christos Kastrisios, Brian R. Calder, Christie Ence, Tamer Nada et al.
Geo-spatial Information Science
Historical Geography and Cartography
article

Automated islands generalization techniques for nautical charts

Christos Kastrisios, Brian R. Calder, Christie Ence, Tamer Nada, Amber Bethell, Craig Greene
article en

Abstract

Land is one of the most prominent geo-features in marine navigation for passage planning and execution. Land generalization for nautical charting, and particularly that of smaller landmasses (islands), is a task performed manually by cartographers based on available specifications and their own experience. Existing methods for automated island selection utilize the Voronoi diagram or weighted buffers to calculate island density and remove islands in dense regions. Their main deficiency is that they do not consider other related chart features, while they may also incorrectly represent the density and distribution of islands and the detection of isolated ones in the process. As such, islands that pose navigational significance and would be retained by a professional cartographer may be removed by the algorithm and vice versa. These drawbacks restrict their use as they present difficulties in achieving the product requirements. This paper presents an island generalization method that combines the benefits of Voronoi and buffer approaches, while it incorporates relevant other chart feature classes to respect topology relations and, with island shape recognition, to categorize islands on a hierarchy level for making generalization decisions. This innovative approach enhances the effectiveness and accurate presentation of islands on nautical charts through automated generalization.

Geo-spatial Information Science
Environmental Systems Research Institute (United States) (US), University of New Hampshire (US), University of New Hampshire at Manchester (US), Ethnographic Museum (HU), NOAA Office of Coast Survey, NOAA National Geodetic Survey (US)
Openalex Percentile: Top 63%
Historical Geography and Cartography
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.