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Articles

ReBankment: displacing embankment lines from roads and rivers with a least squares adjustment

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Pages 37-53 | Received 06 Jul 2021, Accepted 23 Aug 2021, Published online: 18 Oct 2021
 

ABSTRACT

While the recent progress on automated generalisation helped National Mapping Agencies to derive topographic maps more and more quickly, there are still practical cartographic issues that require attention. For instance, embankments are represented with line symbols showing the slope of the embankment. This paper proposes an automated algorithm called ReBankment that displaces the embankment lines from the roads and rivers that overlap the embankment symbol. ReBankment is based on a triangulation to identify neighbourhoods, and on a least squares adjustment to displace and distort the embankment line while preserving its shape. This paper also proposes how to handle complex cases and scaling issues. ReBankment is tested on real data from a 1:25k scale topographic map.

RÉSUMÉ

Même si les progrès récents sur l'automatisation de la généralisation cartographique aident les -agences de cartographie nationales à produire leurs cartes topographiques à différentes échelles de plus en plus rapidement, il existe encore des opérations de généralisation que nous ne savons pas automatiser correctement. Par exemple, les talus sont fréquemment représentés par un symbole linéaire avec des barbules représentant le sens de la pente du talus. Ce type de symbole prend de la place et nécessite d'être éloigné des symboles de routes notamment. Cet article propose un algorithme, appelé ReBankment, qui permet de déplacer automatiquement les lignes de talus. L'algorithme utilise une triangulation pour identifier les voisinages entre objets de la carte, puis une optimisation par moindres carrés de la position des points de la ligne de talus, ce qui permet un déplacement sans modifier la forme initiale de la ligne. L'article propose également des moyens pour traiter les cas complexes et les jeux de données massifs. L'algorithme est testé sur des données réelles de l'IGN France pour la généralisation de la carte au 1/25000.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 https://numpy.org/

2 https://pypi.org/project/Shapely/

Additional information

Notes on contributors

Guillaume Touya

Guillaume Touya is the head of the Scales research team, at IGN France (the French mapping agency) and Univ Gustave Eiffel. He holds a PhD and habilitation in GI science from Paris-Est University. His research interests focus on automated cartography, map generalization and volunteered geographic information. He is particularly interested in research approaches to multi-scale cartography that mix automated cartography, spatial cognition and human-computer interaction issues. He is the principal investigator of the recent LostInZoom project, funded by the Europe Research Council (ERC). He is the chair of the ICA (International Cartographic Association) commission on map generalization and multiple representation.

Imran Lokhat

Imran Lokhat was geographical information science developer at IGN France, the French national mapping agency from 2015 to 2021. He developed, with researchers from IGN, several research platforms and prototypes, in particular the CartAGen open source generalisation platform

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