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Urban impervious surface estimation from remote sensing and social data / Yan Yu in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 12 (December 2018)
[article]
Titre : Urban impervious surface estimation from remote sensing and social data Type de document : Article/Communication Auteurs : Yan Yu, Auteur ; Jun Li, Auteur ; Changyu Zhu, Auteur ; Antonio J. Plaza, Auteur Année de publication : 2018 Article en page(s) : pp 771 - 780 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] base de données routières
[Termes IGN] Canton (Kouangtoung)
[Termes IGN] contenu généré par les utilisateurs
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] données localisées des bénévoles
[Termes IGN] données vectorielles
[Termes IGN] Google Maps
[Termes IGN] image Landsat-8
[Termes IGN] image Landsat-OLI
[Termes IGN] OpenStreetMap
[Termes IGN] point d'intérêt
[Termes IGN] régression multiple
[Termes IGN] réseau routier
[Termes IGN] surface imperméable
[Termes IGN] zone urbaineRésumé : (auteur) We propose an inspiring approach for accurate impervious surface estimation based on the integration of remote sensing and social data. The proposed approach exploits the strengths of two kind of heterogeneous features, i.e., physical features and social features, where the former ones are derived by a morphological attribute profiles-guided spectral mixture analysis model using remote sensing imagery, and the latter ones are obtained from the normalized kernel density of point of interest and vector road datasets. These two features are then integrated using a multivariable linear regression model to estimate impervious surfaces. The proposed method has been tested in the main urban area of Guangzhou, China, in pixel level and parcel level, respectively. The obtained results, with the overall RMSE of 10.98% and 10.90% for pixel level and parcel level, respectively, demonstrate the good performance of integrating remote sensing imagery and social data for mapping of urban impervious surface. Numéro de notice : A2018-549 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.84.12.771 Date de publication en ligne : 01/12/2018 En ligne : https://doi.org/10.14358/PERS.84.12.771 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91622
in Photogrammetric Engineering & Remote Sensing, PERS > vol 84 n° 12 (December 2018) . - pp 771 - 780[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 105-2018121 RAB Revue Centre de documentation En réserve L003 Disponible An algorithm for on-the-fly K shortest paths finding in multi-storey buildings using a hierarchical topology model / Rosen Ivanov in International journal of geographical information science IJGIS, vol 32 n° 11-12 (November - December 2018)
[article]
Titre : An algorithm for on-the-fly K shortest paths finding in multi-storey buildings using a hierarchical topology model Type de document : Article/Communication Auteurs : Rosen Ivanov, Auteur Année de publication : 2018 Article en page(s) : pp 2362 - 2385 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement
[Termes IGN] bati
[Termes IGN] calcul d'itinéraire
[Termes IGN] cartographie à la volée
[Termes IGN] chemin le plus court, algorithme du
[Termes IGN] connexité (graphes)
[Termes IGN] connexité (topologie)
[Termes IGN] modèle topologique de données
[Termes IGN] modélisation 3D du bâti BIM
[Termes IGN] positionnement en intérieurRésumé : (Auteur) This article presents an approach to computing K shortest paths in large buildings with complex horizontal and vertical connectivity. The building topology is obtained from Building Information Model (BIM) and implemented using directed multigraphs. Hierarchical design allows the calculation of feasible paths without the need to load into memory the topology of the entire building. It is possible to expand the graph with new connectivity on-the-fly. The paths calculated may be composed of traversable building components that are located inside the buildings or those that are both inside and outside buildings. The performance (computational time and heap size used) is optimized by using the appropriate collections (maps, lists and sets). The proposed algorithm is evaluated in several use-case scenarios – complete graphs and real building environments. In all test scenarios, the proposed path finding algorithm is faster and uses less memory when compared to the fast version of the Yen’s KSP algorithm. The proposed approach can be successfully used as a first level of coarse-to-fine path finding algorithms. Numéro de notice : A2018-525 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1510126 Date de publication en ligne : 24/08/2018 En ligne : https://doi.org/10.1080/13658816.2018.1510126 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91352
in International journal of geographical information science IJGIS > vol 32 n° 11-12 (November - December 2018) . - pp 2362 - 2385[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2018061 RAB Revue Centre de documentation En réserve L003 Disponible Comparing historical and contemporary maps : a methodological framework for a cartographic map comparison applied to Swiss maps / Christin Loran in International journal of geographical information science IJGIS, vol 32 n° 11-12 (November - December 2018)
[article]
Titre : Comparing historical and contemporary maps : a methodological framework for a cartographic map comparison applied to Swiss maps Type de document : Article/Communication Auteurs : Christin Loran, Auteur ; Suzette Haegi, Auteur ; Christian Ginzler, Auteur Année de publication : 2018 Article en page(s) : pp 2123 - 2139 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse comparative
[Termes IGN] analyse diachronique
[Termes IGN] carte ancienne
[Termes IGN] carte topographique
[Termes IGN] distorsion d'image
[Termes IGN] forêt
[Termes IGN] généralisation cartographique
[Termes IGN] occupation du sol
[Termes IGN] Suisse
[Termes IGN] Zurich (Suisse)
[Vedettes matières IGN] GénéralisationRésumé : (Auteur) Topographic maps are powerful tools for the purpose of identifying land use and cover change (LUCC) as they are among the most reliable representations of past landscapes for the time prior to the existence of aerial photography. In light of the increased availability of historical maps, we argue that there is a need for a standardized process to assess map comparability in a systematic way in order to avoid, or at least minimize, the detection of spurious landscape changes due to incompatible map series. A full understanding of map quality, background and error distributions is fundamental to attain reliable LUCC results. The conceptual framework presented in this study considers the context, distortion and cartographic generalization of topographic maps. Furthermore, it includes an approach to homogenize the level of generalization of landscape elements (e.g. forests) from maps with different scales. To demonstrate its application, we assessed the comparability of seven topographic maps from Canton Zurich covering a time span of 336 years (1664–2000). Overall, for the maps of Canton Zurich, a wall-to-wall comparison of forest cover based on the topographic maps presented here can be problematic for the oldest map from 1664. Based on the results, a wall-to-wall comparison with the later maps is not recommended, due to its substantial distortion. Yet, after re-generalization of natural landscape elements, such as forests, a comparison based on landscape indices is possible, even for the oldest map. Furthermore, our results demonstrate that maps from the mid-19th century onward possess an acceptable level of accuracy. This framework can be applied to a wide range of maps at regional, national, or global levels, providing the opportunity to look at land cover history over multiple centuries. Numéro de notice : A2018-521 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1482553 Date de publication en ligne : 14/06/2018 En ligne : https://doi.org/10.1080/13658816.2018.1482553 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91346
in International journal of geographical information science IJGIS > vol 32 n° 11-12 (November - December 2018) . - pp 2123 - 2139[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2018061 RAB Revue Centre de documentation En réserve L003 Disponible On the spatial distribution of buildings for map generalization / Zhiwei Wei in Cartography and Geographic Information Science, Vol 45 n° 6 (November 2018)
[article]
Titre : On the spatial distribution of buildings for map generalization Type de document : Article/Communication Auteurs : Zhiwei Wei, Auteur ; Qingsheng Guo, Auteur ; Lin Wang, Auteur ; Fen Yan, Auteur Année de publication : 2018 Article en page(s) : pp 539 - 555 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse de groupement
[Termes IGN] analyse en composantes principales
[Termes IGN] arbre aléatoire minimum
[Termes IGN] bati
[Termes IGN] distribution spatiale
[Termes IGN] données localisées des bénévoles
[Termes IGN] généralisation cartographique automatisée
[Termes IGN] OpenStreetMap
[Vedettes matières IGN] GénéralisationRésumé : (Auteur) Information on spatial distribution of buildings must be explored as part of the process of map generalization. A new approach is proposed in this article, which combines building classification and clustering to enable the detection of class differences within a pattern, as well as patterns within a class. To do this, an analysis of existing parameters describing building characteristics is performed via principal component analysis (PCA), and four major parameters (i.e. convex hull area, IPQ compactness, number of edges, and smallest minimum bounding rectangle orientation) are selected for further classification based on similarities between building characteristics. A building clustering method based on minimum spanning tree (MST) considering rivers and roads is then applied. Theory and experiments show that use of a relative neighbor graph (RNG) is more effective in detecting linear building patterns than either a nearest neighbor graph (NNG), an MST, or a Gabriel graph (GssG). Building classification and clustering are therefore conducted separately using experimental data extracted from OpenStreetMap (OSM), and linear patterns are then recognized within resultant clusters. Experimental results show that the approach proposed in this article is both reasonable and efficient for mining information on the spatial distribution of buildings for map generalization. Numéro de notice : A2018-480 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2018.1433068 Date de publication en ligne : 15/02/2018 En ligne : https://doi.org/10.1080/15230406.2018.1433068 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91258
in Cartography and Geographic Information Science > Vol 45 n° 6 (November 2018) . - pp 539 - 555[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 032-2018061 RAB Revue Centre de documentation En réserve L003 Disponible Automated extraction of 3D vector topographic feature line from terrain point cloud / Wei Zhou in Geocarto international, vol 33 n° 10 (October 2018)
[article]
Titre : Automated extraction of 3D vector topographic feature line from terrain point cloud Type de document : Article/Communication Auteurs : Wei Zhou, Auteur ; Rencan Peng, Auteur ; Jian Dong, Auteur ; Tao Wang, Auteur Année de publication : 2018 Article en page(s) : pp 1036 - 1047 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] arbre aléatoire minimum
[Termes IGN] détection d'objet
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] ligne caractéristique
[Termes IGN] lissage de données
[Termes IGN] modèle numérique de terrain
[Termes IGN] objet géographique linéaire
[Termes IGN] repère de Laplace
[Termes IGN] segmentation en régions
[Termes IGN] semis de pointsRésumé : (auteur) This paper presents an automated topographic feature lines detection method that directly extracts 3D vector topographic feature lines from terrain point cloud. First, signed surface variation (SSV) is introduced to extract the potential feature points. Secondly, the potential feature points are segmented to different clusters by combining region growing segmentation and conditional Euclidean clustering. In order to extract feature points, the potential feature points in each cluster are iteratively thinned using a HC-Laplacian smoothing method with SSV weighted taken into account. Besides, SSV-based and elevation-based simple rules are added for accelerating this thinning process. Finally, the feature lines are obtained by constructing the minimum spanning tree of the extracted feature points. By comparing with manually digitized reference lines, the correctness and the completeness of extracted results are about 80% or even higher, which are much higher than those extracted by D8 algorithm. Numéro de notice : A2019-046 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2017.1325521 Date de publication en ligne : 18/05/2017 En ligne : https://doi.org/10.1080/10106049.2017.1325521 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92064
in Geocarto international > vol 33 n° 10 (October 2018) . - pp 1036 - 1047[article]Réservation
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