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Termes IGN > géomatique > base de données localisées > modèle conceptuel de données localisées > modèle topologique de données
modèle topologique de donnéesSynonyme(s)modele topologiqueVoir aussi |
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A spatiotemporal structural graph for characterizing land cover changes / Bin Wu in International journal of geographical information science IJGIS, vol 35 n° 2 (February 2021)
[article]
Titre : A spatiotemporal structural graph for characterizing land cover changes Type de document : Article/Communication Auteurs : Bin Wu, Auteur ; Ballang Yu, Auteur ; Song Shu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 397 - 425 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse spatio-temporelle
[Termes IGN] changement d'occupation du sol
[Termes IGN] changement temporel
[Termes IGN] graphe
[Termes IGN] New York (Etats-Unis ; état)
[Termes IGN] objet géographique
[Termes IGN] voisinage (relation topologique)Résumé : (auteur) Characterizing landscape patterns and revealing their underlying processes are critical for studying climate change and environmental problems. Previous methods for mapping land cover changes largely focused on the classification of remote sensing images. Therefore, they could not provide information about the evolutionary process of land cover changes. In this paper, we developed a spatiotemporal structural graph (STSG) technique for a comprehensive analysis of land cover changes. First, a land cover neighborhood graph was generated for each snapshot to quantify the spatial relationship between adjacent land cover objects. Then, an object-based temporal tracking algorithm was designed to monitor the temporal changes between land cover objects over time. Finally, land cover evolutionary trajectories, pixel-level land cover change trajectories, and node-wise connectivity changes over time were characterized. We applied the proposed method to analyze land cover changes in Suffolk County, New York from 1996 to 2010. The results demonstrated that STSG can not only characterize and visualize detailed land cover changes spatially but also maintain the temporal sequence and relations of land cover objects in an integrated space-time environment. The proposed STSG provides a useful framework for analyzing land cover changes and can be adapted to characterize and quantify other spatiotemporal phenomena. Numéro de notice : A2021-041 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1778706 Date de publication en ligne : 16/06/2020 En ligne : https://doi.org/10.1080/13658816.2020.1778706 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96753
in International journal of geographical information science IJGIS > vol 35 n° 2 (February 2021) . - pp 397 - 425[article]Local fuzzy geographically weighted clustering: a new method for geodemographic segmentation / George Grekousis in International journal of geographical information science IJGIS, vol 35 n° 1 (January 2021)
[article]
Titre : Local fuzzy geographically weighted clustering: a new method for geodemographic segmentation Type de document : Article/Communication Auteurs : George Grekousis, Auteur Année de publication : 2021 Article en page(s) : pp 152 - 174 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de groupement
[Termes IGN] classification floue
[Termes IGN] données démographiques
[Termes IGN] New York (Etats-Unis ; ville)
[Termes IGN] optimisation par essaim de particules
[Termes IGN] pondération
[Termes IGN] régression géographiquement pondérée
[Termes IGN] santé
[Termes IGN] segmentation
[Termes IGN] voisinage (relation topologique)Résumé : (auteur) Fuzzy geographically weighted clustering has been proposed as an approach for improving fuzzy c-means algorithm when applied to geodemographic analysis. This clustering method allows a spatial entity to belong to more than one cluster with varying degrees, namely, membership values. Although fuzzy geographically weighted clustering attempts to create geographically aware clusters, it partially fails to trace spatial dependence and heterogeneity because, as a global metric, the membership values are calculated across the entire set of spatial entities. Here we introduce the first local version of fuzzy geographically weighted clustering, ‘local fuzzy geographically weighted clustering.’ In local fuzzy geographically weighted clustering, the membership values of a spatial entity are updated only according to the membership values of the spatial entities within its neighborhood and not across the entire set of entities, as originally proposed by the global metric. Additionally, we apply particle swarm optimization meta-heuristic to overcome the random initialization problem regarding the fuzzy c-means algorithm. To evaluate our method we compare local fuzzy geographically weighted clustering to global fuzzy geographically weighted clustering using a cancer incident benchmark dataset for Manhattan, New York. The results show that local fuzzy geographically weighted clustering outperforms the global version in all experimental settings. Numéro de notice : A2021-022 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1808221 Date de publication en ligne : 21/08/2020 En ligne : https://doi.org/10.1080/13658816.2020.1808221 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96525
in International journal of geographical information science IJGIS > vol 35 n° 1 (January 2021) . - pp 152 - 174[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2021011 SL Revue Centre de documentation Revues en salle Disponible Relation-constrained 3D reconstruction of buildings in metropolitan areas from photogrammetric point clouds / Yuan Li in Remote sensing, vol 13 n° 1 (January-1 2021)
[article]
Titre : Relation-constrained 3D reconstruction of buildings in metropolitan areas from photogrammetric point clouds Type de document : Article/Communication Auteurs : Yuan Li, Auteur ; Wu Bo, Auteur Année de publication : 2021 Article en page(s) : n° 13 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] CityGML
[Termes IGN] contrainte géométrique
[Termes IGN] détection de contours
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] géomètrie algorithmique
[Termes IGN] Ransac (algorithme)
[Termes IGN] reconstruction 3D du bâti
[Termes IGN] relation topologique
[Termes IGN] semis de points
[Termes IGN] ville intelligenteRésumé : (auteur) The complexity and variety of buildings and the defects of point cloud data are the main challenges faced by 3D urban reconstruction from point clouds, especially in metropolitan areas. In this paper, we developed a method that embeds multiple relations into a procedural modelling process for the automatic 3D reconstruction of buildings from photogrammetric point clouds. First, a hybrid tree of constructive solid geometry and boundary representation (CSG-BRep) was built to decompose the building bounding space into multiple polyhedral cells based on geometric-relation constraints. The cells that approximate the shapes of buildings were then selected based on topological-relation constraints and geometric building models were generated using a reconstructing CSG-BRep tree. Finally, different parts of buildings were retrieved from the CSG-BRep trees, and specific surface types were recognized to convert the building models into the City Geography Markup Language (CityGML) format. The point clouds of 105 buildings in a metropolitan area in Hong Kong were used to evaluate the performance of the proposed method. Compared with two existing methods, the proposed method performed the best in terms of robustness, regularity, and topological correctness. The CityGML building models enriched with semantic information were also compared with the manually digitized ground truth, and the high level of consistency between the results suggested that the produced models will be useful in smart city applications. Numéro de notice : A2021-078 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs13010129 Date de publication en ligne : 01/01/2021 En ligne : https://doi.org/10.3390/rs13010129 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96820
in Remote sensing > vol 13 n° 1 (January-1 2021) . - n° 13[article]Semi-supervised PolSAR image classification based on improved tri-training with a minimum spanning tree / Shuang Wang in IEEE Transactions on geoscience and remote sensing, Vol 58 n° 12 (December 2020)
[article]
Titre : Semi-supervised PolSAR image classification based on improved tri-training with a minimum spanning tree Type de document : Article/Communication Auteurs : Shuang Wang, Auteur ; Yanhe Guo, Auteur ; Wenqiang Hua, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 8583 - 8597 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] arbre aléatoire minimum
[Termes IGN] classification semi-dirigée
[Termes IGN] données d'entrainement (apprentissage automatique)
[Termes IGN] image radar moirée
[Termes IGN] polarimétrie radar
[Termes IGN] segmentation sémantique
[Termes IGN] voisinage (relation topologique)Résumé : (auteur) In this article, the terrain classifications of polarimetric synthetic aperture radar (PolSAR) images are studied. A novel semi-supervised method based on improved Tri-training combined with a neighborhood minimum spanning tree (NMST) is proposed. Several strategies are included in the method: 1) a high-dimensional vector of polarimetric features that are obtained from the coherency matrix and diverse target decompositions is constructed; 2) this vector is divided into three subvectors and each subvector consists of one-third of the polarimetric features, randomly selected. The three subvectors are used to separately train the three different base classifiers in the Tri-training algorithm to increase the diversity of classification; and 3) a help-training sample selection with the improved NMST that uses both the coherency matrix and the spatial information is adopted to select highly reliable unlabeled samples to increase the training sets. Thus, the proposed method can effectively take advantage of unlabeled samples to improve the classification. Experimental results show that with a small number of labeled samples, the proposed method achieves a much better performance than existing classification methods. Numéro de notice : A2020-743 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.2988982 Date de publication en ligne : 14/05/2020 En ligne : https://doi.org/10.1109/TGRS.2020.2988982 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96374
in IEEE Transactions on geoscience and remote sensing > Vol 58 n° 12 (December 2020) . - pp 8583 - 8597[article]A comparison of neighbourhood relations based on ordinary Delaunay diagrams and area Delaunay diagrams: an application to define the neighbourhood relations of buildings / Hiroyuki Usui in International journal of geographical information science IJGIS, vol 34 n° 11 (November 2020)
[article]
Titre : A comparison of neighbourhood relations based on ordinary Delaunay diagrams and area Delaunay diagrams: an application to define the neighbourhood relations of buildings Type de document : Article/Communication Auteurs : Hiroyuki Usui, Auteur ; Akihiro Teraki, Auteur ; Kei-ichi Okunuki, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 2177 - 2203 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] adjacence
[Termes IGN] analyse de groupement
[Termes IGN] ArcGIS
[Termes IGN] bâtiment
[Termes IGN] chevauchement
[Termes IGN] diagramme de Voronoï
[Termes IGN] Tokyo (Japon)
[Termes IGN] triangulation de Delaunay
[Termes IGN] voisinage (relation topologique)Résumé : (auteur) The aim of this article is to describe a convenient but robust method for defining neighbourhood relations among buildings based on ordinary Delaunay diagrams (ODDs) and area Delaunay diagrams (ADDs). ODDs and ADDs are defined as a set of edges connecting the generators of adjacent ordinary Voronoi cells (points representing centroids of building polygons) and a set of edges connecting two centroids of building polygons, which are the generators of adjacent area Voronoi cells, respectively. Although ADDs are more robust than ODDs, computation time of ODDs is shorter than that of ADDs (the order of their computation time complexity is O(nlogn)). If ODDs can approximate ADDs with a certain degree of accuracy, the former can be used as an alternative. Therefore, we computed the ratio of the number of ADD edges to that of ODD edges overlapping ADDs at building and regional scales. The results indicate that: (1) for approximately 60% of all buildings, ODDs can exactly overlap ADDs with extra ODD edges; (2) at a regional scale, ODDs can overlap approximately 90% of ADDs with 10% extra ODD edges; and (3) focusing on judging errors, although ADDs are more accurate than ODDs, the difference is only approximately 1%. Numéro de notice : A2020-616 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1748191 Date de publication en ligne : 15/04/2020 En ligne : https://doi.org/10.1080/13658816.2020.1748191 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95991
in International journal of geographical information science IJGIS > vol 34 n° 11 (November 2020) . - pp 2177 - 2203[article]Réservation
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