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Aggregation of LoD 1 building models as an optimization problem / R. Guercke in ISPRS Journal of photogrammetry and remote sensing, vol 66 n° 2 (March - April 2011)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 66 n° 2 (March - April 2011) . - pp 209 - 222 Titre : Aggregation of LoD 1 building models as an optimization problem Type de document : Article/Communication Auteurs : R. Guercke, Auteur ; T. Götzelmann, Auteur ; Claus Brenner, Auteur ; Monika Sester, Auteur Année de publication : 2011 Article en page(s) : pp 209 - 222 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] agrégation de détails [Termes IGN] généralisation automatique de données [Termes IGN] hauteur du bâti [Termes IGN] méthode heuristique [Termes IGN] modèle 3D de l'espace urbain [Termes IGN] optimisation (mathématiques) [Termes IGN] reconstruction 3D du bâti Résumé : (Auteur) 3D city models offered by digital map providers typically consist of several thousands or even millions of individual buildings. Those buildings are usually generated in an automated fashion from high resolution cadastral and remote sensing data and can be very detailed. However, not in every application such a high degree of detail is desirable. One way to remove complexity is to aggregate individual buildings, simplify the ground plan and assign an appropriate average building height. This task is computationally complex because it includes the combinatorial optimization problem of determining which subset of the original set of buildings should best be aggregated to meet the demands of an application. In this article, we introduce approaches to express different aspects of the aggregation of LoD 1 building models in the form of Mixed Integer Programming (MIP) problems. The advantage of this approach is that for linear (and some quadratic) MIP problems, sophisticated software exists to find exact solutions (global optima) with reasonable effort. We also propose two different heuristic approaches based on the region growing strategy and evaluate their potential for optimization by comparing their performance to a MIP-based approach. Numéro de notice : A2011-074 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2010.10.006 En ligne : https://doi.org/10.1016/j.isprsjprs.2010.10.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30855 [article]

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