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SEH-SDB : a semantically enriched historical spatial database for documentation and preservation of monumental heritage based on CityGML / Reda Yaagoubi in Applied geomatics, vol 11 n° 1 (March 2019)
Titre : SEH-SDB : a semantically enriched historical spatial database for documentation and preservation of monumental heritage based on CityGML Type de document : Article/Communication Auteurs : Reda Yaagoubi, Auteur ; Abdulkader Al-Gilani, Auteur ; Ahmad Baik, Auteur ; Ebraheem Alhomodi, Auteur ; Yehia Miky, Auteur Année de publication : 2019 Article en page(s) : pp 53 - 68 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes d'information géographique
[Termes descripteurs IGN] base de données localisées
[Termes descripteurs IGN] CityGML
[Termes descripteurs IGN] Djeddah
[Termes descripteurs IGN] données lidar
[Termes descripteurs IGN] données localisées 3D
[Termes descripteurs IGN] enrichissement sémantique
[Termes descripteurs IGN] modélisation 3D du bâti BIM
[Termes descripteurs IGN] patrimoine immobilier
[Termes descripteurs IGN] préservation
[Termes descripteurs IGN] SIG 3DRésumé : (Auteur) Cultural heritage has a great and inestimable value for communities. Unfortunately, several historical monuments are under deteriorating conditions mainly due to the lack of knowledge about their historical importance. Hence, it is necessary to provide efficient solutions to preserve these monuments. An effective approach for the preservation of cultural heritage should address two main aspects: documentation and information. The first aspect is related to methods that are used to document and digitally archive historic buildings by using appropriate materials and techniques for acquiring 3D spatial data. The second aspect aims to inform the population and policy makers about the importance of the historical heritage in a simple, effective, and interactive manner. In this paper, we propose an original approach to design a semantically enriched historical spatial database (SEH-SDB) for documentation and information of monumental heritage. First of all, a LiDAR acquisition of the historical heritage should be undertaken to capture its current condition. Then, the SEH-SDB database will be designed according to four semantic packages related to historical buildings that are (1) Components package, (2) Material package, (3) Historical package, and (4) Social package. The component package is based on the CityGML standard, which ensures a high interoperability for 3D models. The material package represents the material used in the construction of the building (wood, stone …). The historical package informs about historical elements that characterize the building and its temporal evolution. The social package aims to inform about the main social activities that may take place in the historical building. Based on the SEH-SDB, a 3D historical GIS is developed to provide rich semantic information about historical sites. At the end of this paper, a case study of a historical monument named “Ribat Banajah” in Jeddah Historical City in Saudi Arabia is presented. A digital archiving of the current state of this building is performed by using terrestrial LiDAR in combination with other classical surveying techniques (traversing, leveling, and GPS). Then, a building information model of this building is created and exported to the 3D HGIS designed for the documentation of historical buildings. Numéro de notice : A2019-161 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s12518-018-0238-y date de publication en ligne : 28/08/2018 En ligne : https://doi.org/10.1007/s12518-018-0238-y Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92522
in Applied geomatics > vol 11 n° 1 (March 2019) . - pp 53 - 68[article]
Titre : Integration of lidar data and GIS data for point cloud semantic enrichment at the point level Type de document : Article/Communication Auteurs : Harith Aljumaily, Auteur ; Debra F. Laefer, Auteur ; Dolores Cuadra, Auteur Année de publication : 2019 Article en page(s) : pp 29 - 42 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes descripteurs IGN] analyse de groupement
[Termes descripteurs IGN] détection du bâti
[Termes descripteurs IGN] données lidar
[Termes descripteurs IGN] données localisées 3D
[Termes descripteurs IGN] Dublin (Irlande ; ville)
[Termes descripteurs IGN] enrichissement sémantique
[Termes descripteurs IGN] étiquetage sémantique
[Termes descripteurs IGN] extraction de la végétation
[Termes descripteurs IGN] extraction du réseau routier
[Termes descripteurs IGN] flore urbaine
[Termes descripteurs IGN] image multibande
[Termes descripteurs IGN] information sémantique
[Termes descripteurs IGN] interpolation linéaire
[Termes descripteurs IGN] OpenStreetMap
[Termes descripteurs IGN] réseau routier
[Termes descripteurs IGN] segmentation
[Termes descripteurs IGN] semis de points
[Termes descripteurs IGN] système de gestion de base de données
[Termes descripteurs IGN] zone urbaineRésumé : (auteur) Commercial aerial laser scanning is generally delivered with point-by-point metadata for object identification, but current vendor-generated classification approaches (which rely exclusively on that data) generate high misclassification rates in urban areas. To overcome this problem and provide a fully scalable solution that harnesses distributed computing capabilities, this paper introduces a novel system, employing a MapReduce framework and existing GIS-based data, to provide more detailed and accurate classification. The approach goes beyond traditional gross-level classification (roads, buildings, trees, noise) by enriching the point cloud metadata with detailed semantic information about the object type. The approach was evaluated using two datasets of differing point density, separated by eight years for the same study area in Dublin, Ireland. As evaluated against manually classified data, classification quality ranged from 76% to 91% depending upon category and only 8% remained unclassified, as opposed to the commercial vendor's classification quality which ranged from 43% to 78% with 82% left unclassified. Numéro de notice : A2019-027 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.85.1.29 date de publication en ligne : 01/01/2019 En ligne : https://doi.org/10.14358/PERS.85.1.29 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91964
in Photogrammetric Engineering & Remote Sensing, PERS > vol 85 n° 1 (January 2019) . - pp 29 - 42[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 105-2019011 SL Revue Centre de documentation Revues en salle Disponible
Titre : Land cover mapping at very high resolution with rotation equivariant CNNs : Towards small yet accurate models Type de document : Article/Communication Auteurs : Diego Marcos, Auteur ; Michele Volpi, Auteur ; Benjamin Kellenberger, Auteur ; Devis Tuia, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes descripteurs IGN] apprentissage profond
[Termes descripteurs IGN] Bade-Wurtemberg (Allemagne)
[Termes descripteurs IGN] carte d'occupation du sol
[Termes descripteurs IGN] enrichissement sémantique
[Termes descripteurs IGN] étiquette
[Termes descripteurs IGN] filtrage numérique d'image
[Termes descripteurs IGN] image à ultra haute résolution
[Termes descripteurs IGN] modèle numérique de surface
[Termes descripteurs IGN] orthoimage
[Termes descripteurs IGN] réseau neuronal convolutifRésumé : (Auteur) In remote sensing images, the absolute orientation of objects is arbitrary. Depending on an object’s orientation and on a sensor’s flight path, objects of the same semantic class can be observed in different orientations in the same image. Equivariance to rotation, in this context understood as responding with a rotated semantic label map when subject to a rotation of the input image, is therefore a very desirable feature, in particular for high capacity models, such as Convolutional Neural Networks (CNNs). If rotation equivariance is encoded in the network, the model is confronted with a simpler task and does not need to learn specific (and redundant) weights to address rotated versions of the same object class. In this work we propose a CNN architecture called Rotation Equivariant Vector Field Network (RotEqNet) to encode rotation equivariance in the network itself. By using rotating convolutions as building blocks and passing only the values corresponding to the maximally activating orientation throughout the network in the form of orientation encoding vector fields, RotEqNet treats rotated versions of the same object with the same filter bank and therefore achieves state-of-the-art performances even when using very small architectures trained from scratch. We test RotEqNet in two challenging sub-decimeter resolution semantic labeling problems, and show that we can perform better than a standard CNN while requiring one order of magnitude less parameters. Numéro de notice : A2018-491 Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.01.021 date de publication en ligne : 19/02/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.01.021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91227
in ISPRS Journal of photogrammetry and remote sensing > vol 145 - part A (November 2018)[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2018111 SL Revue Centre de documentation Revues en salle Disponible 081-2018113 DEP-EXM Revue MATIS Dépôt en unité Exclu du prêt 081-2018112 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt
Titre : OpenStreetMap data quality enrichment through awareness raising and collective action tools—experiences from a European project Type de document : Article/Communication Auteurs : Amin Mobasheri, Auteur ; Alexander Zipf, Auteur ; Louise Francis, Auteur Année de publication : 2018 Article en page(s) : pp 234 - 246 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes descripteurs IGN] accessibilité
[Termes descripteurs IGN] données localisées des bénévoles
[Termes descripteurs IGN] enrichissement sémantique
[Termes descripteurs IGN] étiquetage sémantique
[Termes descripteurs IGN] Europe (géographie politique)
[Termes descripteurs IGN] exhaustivité des données
[Termes descripteurs IGN] handicap
[Termes descripteurs IGN] OpenStreetMap
[Termes descripteurs IGN] qualité des données
[Termes descripteurs IGN] villeRésumé : (Auteur) Nowadays, several research projects show interest in employing volunteered geographic information (VGI) to improve their systems through using up-to-date and detailed data. The European project CAP4Access is one of the successful examples of such international-wide research projects that aims to improve the accessibility of people with restricted mobility using crowdsourced data. In this project, OpenStreetMap (OSM) is used to extend OpenRouteService, a well-known routing platform. However, a basic challenge that this project tackled was the incompleteness of OSM data with regards to certain information that is required for wheelchair accessibility (e.g. sidewalk information, kerb data, etc.). In this article, we present the results of initial assessment of sidewalk data in OSM at the beginning of the project as well as our approach in awareness raising and using tools for tagging accessibility data into OSM database for enriching the sidewalk data completeness. Several experiments have been carried out in different European cities, and discussion on the results of the experiments as well as the lessons learned are provided. The lessons learned provide recommendations that help in organizing better mapping party events in the future. We conclude by reporting on how and to what extent the OSM sidewalk data completeness in these study areas have benefited from the mapping parties by the end of the project. Numéro de notice : A2018-645 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10095020.2018.1493817 date de publication en ligne : 21/09/2018 En ligne : https://doi.org/10.1080/10095020.2018.1493817 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93315
in Geo-spatial Information Science > vol 21 n° 3 (October 2018) . - pp 234 - 246[article]
Titre : A framework for annotating OpenStreetMap objects using geo-tagged tweets Type de document : Article/Communication Auteurs : Xin Chen, Auteur ; Hoang Vo, Auteur ; Yu Wang, Auteur ; Fusheng Wang, Auteur Année de publication : 2018 Article en page(s) : pp 589 - 613 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes descripteurs IGN] corpus
[Termes descripteurs IGN] données issues des réseaux sociaux
[Termes descripteurs IGN] données localisées des bénévoles
[Termes descripteurs IGN] enrichissement sémantique
[Termes descripteurs IGN] géoétiquetage
[Termes descripteurs IGN] intégration de données
[Termes descripteurs IGN] objet géographique
[Termes descripteurs IGN] OpenStreetMap
[Termes descripteurs IGN] TwitterRésumé : (Auteur) Recent years have witnessed an explosion of geospatial data, especially in the form of Volunteered Geographic Information (VGI). As a prominent example, OpenStreetMap (OSM) creates a free editable map of the world from a large number of contributors. On the other hand, social media platforms such as Twitter or Instagram supply dynamic social feeds at population level. As much of such data is geo-tagged, there is a high potential on integrating social media with OSM to enrich OSM with semantic annotations, which will complement existing objective description oriented annotations to provide a broader range of annotations. In this paper, we propose a comprehensive framework on integrating social media data and VGI data to derive knowledge about geographical objects, specifically, top relevant annotations from tweets for objects in OSM. We first integrate geo-tagged tweets with OSM data with scalable spatial queries running on MapReduce. We propose a frequency based method for annotating boundary based geographic objects (a polygon), and a probability based method for annotating point based geographic objects (Latitude and Longitude), with consideration of noise. We evaluate our methods using a large geo-tagged tweets corpus and representative geographic objects from OSM, which demonstrates promising results through ground-truth comparison and case studies. We are able to produce up to 80% correct names for geographical objects and discover implicitly relevant information, such as popular exhibitions of a museum, the nicknames or visitors’ impression to a tourism attraction. Numéro de notice : A2018-369 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10707-018-0323-8 date de publication en ligne : 20/06/2018 En ligne : https://doi.org/10.1007/s10707-018-0323-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90760
in Geoinformatica [en ligne] > vol 22 n° 3 (July 2018) . - pp 589 - 613[article]PermalinkExtraction et Gestion des Connaissances, EGC 2008, 8es journées francophones, 29 janvier 2008, Sophia Antipolis, France / Marie-Aude Aufaure Portier (2008)
PermalinkPermalinkPermalinkEtude de l'unification sémantique de Géoroute sur la BDTopo ; thème réseau routier / Ahmed Berroukech (2001)
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