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Recognition of building group patterns using graph convolutional network / Rong Zhao in Cartography and Geographic Information Science, Vol 47 n° 5 (September 2020)  

Public [article]  inCartography and Geographic Information Science > Vol 47 n° 5 (September 2020) . - pp 400 - 417 Titre : Recognition of building group patterns using graph convolutional network Type de document : Article/Communication Auteurs : Rong Zhao, Auteur ; Tinghua Ai, Auteur ; Wenhao Yu, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 400 - 417 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes descripteurs IGN] classification par réseau neuronal convolutif [Termes descripteurs IGN] données topographiques [Termes descripteurs IGN] espace urbain [Termes descripteurs IGN] généralisation du bâti [Termes descripteurs IGN] graphe [Termes descripteurs IGN] modélisation du bâti [Termes descripteurs IGN] reconnaissance de formes Résumé : (auteur) Recognition of building group patterns is of great significance for understanding and modeling the urban space. However, many current methods cannot fully utilize spatial information and have trouble efficiently dealing with topographic data with high complexity. The design of intelligent computational models that can act directly on topographic data to extract spatial features is critical. To this end, we propose a novel deep neural network based on graph convolutions to automatically identify building group patterns with arbitrary forms. The method first models buildings by a general graph, and then the neural network simultaneously learns the structural information as well as vertex attributes to classify building objects. We apply this method to real building data, and the experimental results show that the proposed method can effectively capture spatial information to make more accurate predictions than traditional methods. Numéro de notice : A2020-510 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2020.1757512 date de publication en ligne : 12/06/2020 En ligne : https://doi.org/10.1080/15230406.2020.1757512 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95663 [article]

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Recognizing building groups for generalization : a comparative study / Min Deng in Cartography and Geographic Information Science, Vol 45 n° 3 (May 2018)  

Public [article]  inCartography and Geographic Information Science > Vol 45 n° 3 (May 2018) . - pp 187 - 204 Titre : Recognizing building groups for generalization : a comparative study Type de document : Article/Communication Auteurs : Min Deng, Auteur ; Jianbo Tang, Auteur ; Qiliang Liu, Auteur ; Fang Wu, Auteur Année de publication : 2018 Article en page(s) : pp 187 - 204 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] algorithme de généralisation [Termes descripteurs IGN] analyse comparative [Termes descripteurs IGN] Chine [Termes descripteurs IGN] contrainte géométrique [Termes descripteurs IGN] généralisation cartographique automatisée [Termes descripteurs IGN] généralisation du bâti [Vedettes matières IGN] Généralisation Résumé : (Auteur) Recognition of building groups is a critical step in building generalization. To find building groups, various approaches have been developed based on the principles of grouping (or the Gestalt laws of grouping), and the effectiveness of these approaches needs to be evaluated. This study presents a comparative analysis of nine typical such approaches, including three approaches that only consider proximity principle and six approaches that consider multiple grouping principles. Real-life dataset at 1:5000, 1:10,000, and 1:50,000 scales provided by National Geomatics Center of China is used to evaluate the performance of these approaches. Buildings at smaller scales are used to construct the benchmarks to test the grouping results at larger scales, and the adjusted Rand index is adopted to indicate the accuracy of the detected groups. Significant tests (Friedman test and Wilcoxon signed-rank test) are also performed to provide both the overall and pairwise comparisons of these approaches. The results show that (1) the average accuracy of most existing approaches is between 0.3 and 0.5, and the performances of these approaches are significantly different; (2) when only proximity is considered, the buffer analysis approach performs significantly better than other approaches; (3) when multiple grouping principles are considered, the local constraint-based approach usually performs better than other approaches; (4) existing approaches that consider similarity and/or continuity seldom improve the performance of building grouping. Numéro de notice : A2018-129 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2017.1302821 date de publication en ligne : 24/03/2017 En ligne : https://doi.org/10.1080/15230406.2017.1302821 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89657 [article]

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Progressive amalgamation of building clusters for map generalization based on scaling subgroups / Xianjin He in ISPRS International journal of geo-information, vol 7 n° 3 (March 2018)  

Public [article]  inISPRS International journal of geo-information > vol 7 n° 3 (March 2018) Titre : Progressive amalgamation of building clusters for map generalization based on scaling subgroups Type de document : Article/Communication Auteurs : Xianjin He, Auteur ; Xinchang Zhang, Auteur ; Jie Yang, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] approche hiérarchique [Termes descripteurs IGN] généralisation du bâti [Termes descripteurs IGN] regroupement de données [Termes descripteurs IGN] représentation multiple [Vedettes matières IGN] Généralisation Résumé : (Auteur) Map generalization utilizes transformation operations to derive smaller-scale maps from larger-scale maps, and is a key procedure for the modelling and understanding of geographic space. Studies to date have largely applied a fixed tolerance to aggregate clustered buildings into a single object, resulting in the loss of details that meet cartographic constraints and may be of importance for users. This study aims to develop a method that amalgamates clustered buildings gradually without significant modification of geometry, while preserving the map details as much as possible under cartographic constraints. The amalgamation process consists of three key steps. First, individual buildings are grouped into distinct clusters by using the graph-based spatial clustering application with random forest (GSCARF) method. Second, building clusters are decomposed into scaling subgroups according to homogeneity with regard to the mean distance of subgroups. Thus, hierarchies of building clusters can be derived based on scaling subgroups. Finally, an amalgamation operation is progressively performed from the bottom-level subgroups to the top-level subgroups using the maximum distance of each subgroup as the amalgamating tolerance instead of using a fixed tolerance. As a consequence of this step, generalized intermediate scaling results are available, which can form the multi-scale representation of buildings. The experimental results show that the proposed method can generate amalgams with correct details, statistical area balance and orthogonal shape while satisfying cartographic constraints (e.g., minimum distance and minimum area). Numéro de notice : A2018-102 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi7030116 En ligne : https://doi.org/10.3390/ijgi7030116 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89517 [article]

A typification method for linear pattern in urban building generalisation / Xianyong Gong in Geocarto international, vol 33 n° 2 (February 2018)  

Public [article]  inGeocarto international > vol 33 n° 2 (February 2018) . - pp 189 - 207 Titre : A typification method for linear pattern in urban building generalisation Type de document : Article/Communication Auteurs : Xianyong Gong, Auteur ; Fang Wu, Auteur Année de publication : 2018 Article en page(s) : pp 189 - 207 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] généralisation cartographique automatisée [Termes descripteurs IGN] généralisation du bâti [Termes descripteurs IGN] itération [Termes descripteurs IGN] modèle linéaire [Termes descripteurs IGN] reconnaissance de formes [Termes descripteurs IGN] triangulation de Delaunay [Termes descripteurs IGN] typification [Vedettes matières IGN] Généralisation Résumé : (Auteur) This paper presents a typification method for linear pattern in urban building generalization. The proposed method includes two processes. Firstly, structural knowledge in terms of linear pattern is detected using a two-step algorithm taking the advantages of Gestalt visual perception, computational geometry and graph theory. Spatial neighbourhood is captured using interpolated constrained Delaunay triangulation and the resulting proximity graph is pruned to be heterogeneous to get acceptable linear patterns with regard to Gestalt visual perception. Then, a typification strategy is proposed, in which typification is regarded as a progressive and iterative process consisting of elimination, exaggeration and displacement. The typification strategy iteratively executes eliminating the building with minimum overall effect, exaggerating remaining buildings considering key location and spatial characteristics and displacing them to preserve the linear pattern until elimination quantity is satisfied. Experiments show that this proposed strategy is effective and linear patterns are guaranteed with correctness and completeness. Numéro de notice : A2018-034 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2016.1240718 En ligne : https://doi.org/10.1080/10106049.2016.1240718 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89207 [article]

Progressive block graying and landmarks enhancing as intermediate representations between buildings and urban areas / Guillaume Touya (2017) 

Public contenu dans Proceedings of 20th ICA Workshop on Generalisation and Multiple Representation / International cartographic association = association cartographique internationale (2017)   Titre : Progressive block graying and landmarks enhancing as intermediate representations between buildings and urban areas Type de document : Article/Communication Auteurs : Guillaume Touya , Auteur ; Marion Dumont , Auteur Congrès : Congrès: ICC 2017 28th International Cartographic Conference ICA (2 - 7 juillet 2017; Washington DC, Etats-Unis) , Commanditaire Editeur : ICA Commission on Generalisation and Multiple Representation Année de publication : 2017 Importance : 10 p. Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] analyse multicritère [Termes descripteurs IGN] apprentissage automatique [Termes descripteurs IGN] base de données cartographiques [Termes descripteurs IGN] estompage automatique [Termes descripteurs IGN] généralisation du bâti [Termes descripteurs IGN] point de repère [Termes descripteurs IGN] relation spatiale [Termes descripteurs IGN] zone urbaine [Termes descripteurs IGN] zoom [Vedettes matières IGN] Généralisation Résumé : (Auteur) Geovisualization applications that allow the navigation between maps at different scales while zooming in and out often provide no smooth transition between the individual building level of abstraction and the representation of whole urban areas as polygons. In order to reduce the cognitive load of the user, we seek to add intermediate zoom levels with intermediate and progressive abstractions between buildings and urban areas. This paper proposes a method based on progressive block graying while enhancing building landmarks, to derive these intermediate representations from the individual buildings. Block graying is based on an automatic building classification, and a multiple criteria decision technique to infer inner city blocks. The landmarks identification relies on machine learning and several criteria based on geometry and spatial relations. The method is tested with real cartographic data between the 1:25k (with individual buildings) and the 1:100k scale (with urban areas): transitions with one, two, or three intermediate representations are derived and tested. Numéro de notice : C2017-007 Affiliation des auteurs : IGN (avant 2012) Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86201

Documents numériques

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Representation and discovery of building patterns: a three-level relational approach / Shihong Du in International journal of geographical information science IJGIS, vol 30 n° 5-6 (May - June 2016)  

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A vector field model to handle the displacement of multiple conflicts in building generalization / Tinghua Ai in International journal of geographical information science IJGIS, vol 29 n° 8 (August 2015)  

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Generalization of 3D buildings and LoD production [diaporama] / Shuang He (mai 2013) 

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A geometry and texture coupled flexible generalization of urban building models / M. Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 70 (June 2012)

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Multi-criteria diagnosis of control knowledge for cartographic generalisation / Patrick Taillandier in European journal of operational research, vol 217 n° 3 ([01/03/2012])  

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Utilising urban context recognition and machine learning to improve the generalisation of buildings / Stefan Steiniger in International journal of geographical information science IJGIS, vol 24 n°1-2 (january 2010)  

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A structure recognition technique in contextual generalisation of buildings and built-up areas / Melih Basaraner in Cartographic journal (the), vol 45 n° 4 (November 2008)

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A multi-parameter approach to automated building grouping and generalization / Hongxiang Yan in Geoinformatica, vol 12 n° 1 (March - May 2008)

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Automatic amalgation of buildings for producing Ordnance Survey 1: 50000 scale maps / Nicolas Regnauld in Cartographic journal (the), vol 44 n° 3 (August 2007)

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Mesh simplification for building typification / Dirk Burghardt in International journal of geographical information science IJGIS, vol 21 n° 3-4 (march - april 2007)

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