A Comprehensive Multi-criteria Model for High Cartographic Quality Point-Feature Label Placement
Bibliographic Data
| ID | 14701367 |
|---|---|
| Authors | Maxim Rylov (Heidelberg University, corresponding author), Maxim A Rylov (GIScience Research Group / Institute of Geography / University of Heidelberg / Heidelberg / Germany), Andreas Reimer (Heidelberg University), Andreas W Reimer (GIScience Research Group / Institute of Geography / University of Heidelberg / Heidelberg / Germany) |
| Year | 2014 |
| Volume | 49 |
| Issue | 1 |
| Pages | 52-68 |
| Publication date | 2014-03-01 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Cartographica The International Journal for Geographic Information and Geovisualization (JOURNAL) |
| Journal identifiers | ISSN: 0317-7173 • E-ISSN: 1911-9925 |
| Publisher | University of Toronto Press Inc. (UTPress) (PUBLISHER) |
| DOI | 10.3138/carto.49.1.2137 |
| OpenAlex | W1992210522 |
| Language | EN |
| Citations received | 8 |
| References cited | 42 |
The lettering process, including assigning names to point features, is an essential part of map production. While there have been numerous and varied research efforts to automate point-feature label placement (PFLP), none of them seems to have taken into account the many well-established cartographic precepts for point-feature annotation used by human cartographers. As a result, current fully automated solutions are limited in their expressive power. The PFLP problem is still vital, therefore, and solving it is a compelling challenge. This article presents a comprehensive multi-criterion model that complies with almost all well-defined cartographic placement principles and requirements for PFLP, allowing for a significant increase in toponym density without affecting legibility. The proposed model, expressed as a quality-evaluation function, can be used by any mathematical optimization algorithm to resolve the automated label-placement problem. Through an application of the proposed model tested on volunteered geographic (VGI) data and the creation of sample parameter settings, the article illustrates that a high level of cartographic quality for PFLP can be achieved through the integrated approach, comparable to the lettering produced by an expert cartographer
Annotation · Data mining · Engineering drawing · Feature (linguistics · Information retrieval · Legibility · Lettering · Point (geometry · Process (computing · Programming language · Quality (philosophy · Computer Science · Data Management and Algorithms · Engineering · Geographic Information Systems Studies · Mathematics · Remote Sensing and LiDAR Applications · Artificial Intelligence
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Download the Complete Issue (25.6MB)
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| Citations per year | 0.73 |
|---|---|
| Citation span | 2015 - 2025 (11) |
| Highly cited | No |