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Area aggregation in map generalisation by mixed-integer programming / Jan‐Henrik Haunert in International journal of geographical information science IJGIS, vol 24 n°11-12 (december 2010)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 24 n°11-12 (december 2010) . - pp 1871 - 1897 Titre : Area aggregation in map generalisation by mixed-integer programming Type de document : Article/Communication Auteurs : Jan‐Henrik Haunert, Auteur ; A. Wolff, Auteur Année de publication : 2010 Article en page(s) : pp 1871 - 1897 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] agrégation de données [Termes IGN] analyse combinatoire (maths) [Termes IGN] base de données ATKIS [Termes IGN] base de données topographiques [Termes IGN] distance [Termes IGN] généralisation cartographique automatisée [Termes IGN] graphe [Termes IGN] jeu de données localisées [Termes IGN] méthode heuristique [Termes IGN] optimisation (mathématiques) [Termes IGN] programmation par contraintes [Termes IGN] rédaction cartographique [Termes IGN] sémiologie graphique [Vedettes matières IGN] Généralisation Résumé : (Auteur) Topographic databases normally contain areas of different land cover classes, commonly defining a planar partition, that is, gaps and overlaps are not allowed. When reducing the scale of such a database, some areas become too small for representation and need to be aggregated. This unintentionally but unavoidably results in changes of classes. In this article we present an optimisation method for the aggregation problem. This method aims to minimise changes of classes and to create compact shapes, subject to hard constraints ensuring aggregates of sufficient size for the target scale. To quantify class changes we apply a semantic distance measure. We give a graph theoretical problem formulation and prove that the problem is NP-hard, meaning that we cannot hope to find an efficient algorithm. Instead, we present a solution by mixed-integer programming that can be used to optimally solve small instances with existing optimisation software. In order to process large datasets, we introduce specialised heuristics that allow certain variables to be eliminated in advance and a problem instance to be decomposed into independent sub-instances. We tested our method for a dataset of the official German topographic database ATKIS with input scale 1:50,000 and output scale 1:250,000. For small instances, we compare results of this approach with optimal solutions that were obtained without heuristics. We compare results for large instances with those of an existing iterative algorithm and an alternative optimisation approach by simulated annealing. These tests allow us to conclude that, with the defined heuristics, our optimisation method yields high-quality results for large datasets in modest time. Numéro de notice : A2010-554 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658810903401008 En ligne : https://doi.org/10.1080/13658810903401008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30746 [article]

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Towards an evaluation of quality for names placement methods / S. Van Dijk in International journal of geographical information science IJGIS, vol 16 n° 7 (october 2002)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 16 n° 7 (october 2002) . - pp 641 - 661 Titre : Towards an evaluation of quality for names placement methods Type de document : Article/Communication Auteurs : S. Van Dijk, Auteur ; Marc Van Kreveld, Auteur ; Tycho Wiljan Strijk, Auteur ; A. Wolff, Auteur Année de publication : 2002 Article en page(s) : pp 641 - 661 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie numérique [Termes IGN] contrôle qualité [Termes IGN] indicateur de qualité [Termes IGN] placement automatique des écritures Résumé : (Auteur) The cartographic labelling problem is the problem of placing text on a map. This includes the positioning of the labels, and determining the shape in the case of line and area feature labels. There are many rules and customs that describe aspects of good label placement, like readability and clear association. This paper gives a classification of most label placement rules, and formalizes them into a function that can serve as a quality measure for label placement. If such a function is implemented, it allows comparison of the output of different label placement programs. We give a simple and a more refined example of the quality function. Numéro de notice : A2002-210 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658810210138742 En ligne : https://doi.org/10.1080/13658810210138742 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22125 [article]

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