Centre dedocumentation
scientifique

Architecture for semantic web service composition in spatial data infrastructures / Deniztan Ulutaş Karakol in Survey review, vol 54 n° 382 (January 2022)  

Public [article]  inSurvey review > vol 54 n° 382 (January 2022) . - pp 1 - 16 Titre : Architecture for semantic web service composition in spatial data infrastructures Type de document : Article/Communication Auteurs : Deniztan Ulutaş Karakol, Auteur ; Cetin Cömert, Auteur Année de publication : 2022 Article en page(s) : pp 1 - 16 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Infrastructure de données [Termes IGN] accès aux données localisées [Termes IGN] conception orientée utilisateur [Termes IGN] langage naturel (informatique) [Termes IGN] ontologie [Termes IGN] OWL [Termes IGN] web sémantique Résumé : (auteur) The importance of geospatial data has rendered it to be used in decision-making in both public and private sectors. The purpose of this study was to employ Semantic Web Technology (SWT) for the problems of Web Service Composition (WSC) in the context of Spatial Data Infrastructures (SDI). Some of these problems are identifying the workflow sequence and the user goal, discovering services according to service parameters, and matching these parameters. As a suggestion for the solution of all these problems a semi-automated WSC architecture was proposed in this study. In terms of architecture, users state their ‘goal’ with a natural language sentence. By semantically matching this sentence with a Spatial Services Ontology (SSO), the corresponding ‘abstract’ WSC was ‘located’ and the ‘concrete’ WSC was formed. Although there are still problems waiting to be solved due to the scope of the work, this study makes a valuable contribution to the area. Numéro de notice : A2022-110 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2020.1858255 Date de publication en ligne : 25/12/2020 En ligne : https://doi.org/10.1080/00396265.2020.1858255 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99627 [article]

Fully automated pose estimation of historical images in the context of 4D geographic information systems utilizing machine learning methods / Ferdinand Maiwald in ISPRS International journal of geo-information, vol 10 n° 11 (November 2021)  

Public [article]  inISPRS International journal of geo-information > vol 10 n° 11 (November 2021) . - n° 748 Titre : Fully automated pose estimation of historical images in the context of 4D geographic information systems utilizing machine learning methods Type de document : Article/Communication Auteurs : Ferdinand Maiwald, Auteur ; Christoph Lehmann, Auteur ; Taras Lazariv, Auteur Année de publication : 2021 Article en page(s) : n° 748 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] apprentissage automatique [Termes IGN] chaîne de traitement [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] corrélation à l'aide de traits caractéristiques [Termes IGN] échelle de temps [Termes IGN] estimation de pose [Termes IGN] image ancienne [Termes IGN] image terrestre [Termes IGN] métadonnées [Termes IGN] modélisation 4D [Termes IGN] patrimoine culturel [Termes IGN] recherche d'image basée sur le contenu [Termes IGN] récupération de données [Termes IGN] structure-from-motion [Termes IGN] système d'information géographique Résumé : (auteur) The idea of virtual time machines in digital environments like hand-held virtual reality or four-dimensional (4D) geographic information systems requires an accurate positioning and orientation of urban historical images. The browsing of large repositories to retrieve historical images and their subsequent precise pose estimation is still a manual and time-consuming process in the field of Cultural Heritage. This contribution presents an end-to-end pipeline from finding relevant images with utilization of content-based image retrieval to photogrammetric pose estimation of large historical terrestrial image datasets. Image retrieval as well as pose estimation are challenging tasks and are subjects of current research. Thereby, research has a strong focus on contemporary images but the methods are not considered for a use on historical image material. The first part of the pipeline comprises the precise selection of many relevant historical images based on a few example images (so called query images) by using content-based image retrieval. Therefore, two different retrieval approaches based on convolutional neural networks (CNN) are tested, evaluated, and compared with conventional metadata search in repositories. Results show that image retrieval approaches outperform the metadata search and are a valuable strategy for finding images of interest. The second part of the pipeline uses techniques of photogrammetry to derive the camera position and orientation of the historical images identified by the image retrieval. Multiple feature matching methods are used on four different datasets, the scene is reconstructed in the Structure-from-Motion software COLMAP, and all experiments are evaluated on a newly generated historical benchmark dataset. A large number of oriented images, as well as low error measures for most of the datasets, show that the workflow can be successfully applied. Finally, the combination of a CNN-based image retrieval and the feature matching methods SuperGlue and DISK show very promising results to realize a fully automated workflow. Such an automated workflow of selection and pose estimation of historical terrestrial images enables the creation of large-scale 4D models. Numéro de notice : A2021-827 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10110748 Date de publication en ligne : 04/11/2021 En ligne : https://doi.org/10.3390/ijgi10110748 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98964 [article]

A web GIS-based integration of 3D digital models with linked open data for cultural heritage exploration / Ikrom Nishanbaev in ISPRS International journal of geo-information, vol 10 n° 10 (October 2021)  

Public [article]  inISPRS International journal of geo-information > vol 10 n° 10 (October 2021) . - n° 684 Titre : A web GIS-based integration of 3D digital models with linked open data for cultural heritage exploration Type de document : Article/Communication Auteurs : Ikrom Nishanbaev, Auteur ; Erik Champion, Auteur ; David A. McMeekin, Auteur Année de publication : 2021 Article en page(s) : n° 684 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] Australie [Termes IGN] carte interactive [Termes IGN] édition en libre accès [Termes IGN] hétérogénéité [Termes IGN] informatique en nuage [Termes IGN] interface de programmation [Termes IGN] interopérabilité [Termes IGN] métadonnées [Termes IGN] modélisation 3D [Termes IGN] patrimoine culturel [Termes IGN] QGIS [Termes IGN] SPARQL [Termes IGN] visualisation 3D [Termes IGN] Web des données [Termes IGN] WebSIG Résumé : (auteur) In recent years, considerable efforts have been made by cultural heritage institutions across the globe to digitise cultural heritage sites, artifacts, historical maps, etc. for digital preservation and online representation. On the other hand, ample research projects and studies have been published that demonstrate the great capabilities of web-geographic information systems (web-GIS) for the dissemination and online representation of cultural heritage data. However, cultural heritage data and the associated metadata produced by many cultural heritage institutions are heterogeneous. To make this heterogeneous data more interoperable and structured, an ever-growing number of cultural heritage institutions are adopting linked data principles. Although the cultural heritage domain has already started implementing linked open data concepts to the cultural heritage data, there are not many research articles that present an easy-to-implement, free, and open-source-based web-GIS architecture that integrates 3D digital cultural heritage models with cloud computing and linked open data. Furthermore, the integration of web-GIS technologies with 3D web-based visualisation and linked open data may offer new dimensions of interaction and exploration of digital cultural heritage. To demonstrate the high potential of integration of these technologies, this study presents a novel cloud architecture that attempts to enhance digital cultural heritage exploration by integrating 3D digital cultural heritage models with linked open data from DBpedia and GeoNames platforms using web-GIS technologies. More specifically, a digital interactive map, 3D digital cultural heritage models, and linked open data from DBpedia and GeoNames platforms were integrated into a cloud-based web-GIS architecture. Thus, the users of the architecture can easily interact with the digital map, visualise 3D digital cultural heritage models, and explore linked open data from GeoNames and DBpedia platforms, which offer additional information and context related to the selected cultural heritage site as well as external web resources. The architecture was validated by applying it to specific case studies of Australian cultural heritage and seeking expert feedback on the system, its benefits, and scope for improvement in the near future. Numéro de notice : A2021-802 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10100684 Date de publication en ligne : 11/10/2021 En ligne : https://doi.org/10.3390/ijgi10100684 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98854 [article]

Integration of heterogeneous terrain data into Discrete Global Grid Systems / Mingke Li in Cartography and Geographic Information Science, vol 48 n° 6 (October 2021)  

Public [article]  inCartography and Geographic Information Science > vol 48 n° 6 (October 2021) . - pp 546 - 564 Titre : Integration of heterogeneous terrain data into Discrete Global Grid Systems Type de document : Article/Communication Auteurs : Mingke Li, Auteur ; Heather McGrath, Auteur ; Emmanuel Stefanakis, Auteur Année de publication : 2021 Article en page(s) : pp 546 - 564 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] données de terrain [Termes IGN] données hétérogènes [Termes IGN] Infrastructure de données [Termes IGN] métadonnées [Termes IGN] modèle numérique de surface [Termes IGN] Ontario (Canada) [Termes IGN] système de grille globale discrète [Termes IGN] tessellation Résumé : (auteur) The Canadian Digital Elevation Model (CDEM) and the High-Resolution Digital Elevation Model (HRDEM) released by Natural Resources Canada are primary terrain data sources in Canada. Due to their different coverage, datums, resolutions, and accuracies, a standardized framework for national elevation data across various scales is required. This study provides new insights into the adoption of Discrete Global Grid Systems (DGGS) to facilitate the integration of multi-source terrain data at various granularities. In particular, the Icosahedral Snyder Equal Area Aperture 3 Hexagonal Grid (ISEA3H) was employed, and quantization, integration, and aggregation were conducted on this framework. To demonstrate the modeling process, an experiment was undertaken for two areas in Ontario, taking advantage of parallel computing which was beneficial from the discreteness of DGGS cells. The accuracy of the modeled elevations was estimated by referring to the ground-surveyed values and was included in the spatially referenced metadata as an indicator of data quality. This research can serve as a guide for future development of a national elevation service, providing consistent, multi-resolution elevations and avoiding complex, duplicated pre-processing at the user’s end. Future investigation into an operational integration platform to support real-world decision-making, as well as the DGGS-powered geospatial datacube, is recommended. Numéro de notice : A2021-748 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/15230406.2021.1966648 Date de publication en ligne : 02/09/2021 En ligne : https://doi.org/10.1080/15230406.2021.1966648 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98711 [article]

Réservation

Réserver ce document

Exemplaires (1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
032-2021061	SL	Revue	Centre de documentation	Revues en salle	Disponible

Implementing a mass valuation application on interoperable land valuation data model designed as an extension of the national GDI / Arif Cagdas Aydinoglu in Survey review, Vol 53 n° 379 (July 2021)  

Public [article]  inSurvey review > Vol 53 n° 379 (July 2021) . - pp 349 - 365 Titre : Implementing a mass valuation application on interoperable land valuation data model designed as an extension of the national GDI Type de document : Article/Communication Auteurs : Arif Cagdas Aydinoglu, Auteur ; Rabia Bovkir, Auteur ; Ismail Colkesen, Auteur Année de publication : 2021 Article en page(s) : pp 349 - 365 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Infrastructure de données [Termes IGN] apprentissage automatique [Termes IGN] base de données foncières [Termes IGN] classification par forêts aléatoires [Termes IGN] coefficient de corrélation [Termes IGN] implémentation (informatique) [Termes IGN] infrastructure nationale des données localisées [Termes IGN] interopérabilité [Termes IGN] Istanbul (Turquie) [Termes IGN] métadonnées [Termes IGN] système d'information géographique Résumé : (auteur) The main purpose of this study is to propose an interoperable land valuation data model for residential properties as an extension of the national geographic data infrastructure (GDI) and to make mass valuation process applicable with the use of machine learning approach. As an example, random forest (RF) ensemble algorithm was implemented in Pendik district of Istanbul to evaluate the prediction performance by using thematic datasets compatible with the data model. This study provides a methodology for various urban applications and robustness of the algorithm increases the prediction of the real estate values with the use of qualified datasets. Numéro de notice : A2021-523 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2020.1771967 Date de publication en ligne : 06/06/2020 En ligne : https://doi.org/10.1080/00396265.2020.1771967 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97960 [article]

Chinese tourists in Nordic countries: An analysis of spatio-temporal behavior using geo-located travel blog data / Yunhao Zheng in Computers, Environment and Urban Systems, vol 85 (January 2021)  

Permalink

Spatial dataset search: Building a dedicated knowledge graph / Mehdi Zhral (2021)  

Permalink

Streets of London: Using Flickr and OpenStreetMap to build an interactive image of the city / Azam Raha Bahrehdar in Computers, Environment and Urban Systems, vol 84 (November 2020)  

Permalink

GNSS scale determination using calibrated receiver and Galileo satellite antenna patterns / Arturo Villiger in Journal of geodesy, vol 94 n° 9 (September 2020)  

Permalink

Data scale as cartography: a semi-automatic approach for thematic web map creation / Auriol Degbelo in Cartography and Geographic Information Science, vol 47 n° 2 (February 2020)  

Permalink

Artificial intelligence applications to smart city and smart enterprise / Donato Impedovo (2020)  

Permalink

Big data computing for geospatial applications / Zhenlong Li (2020)  

Permalink

Collaborative user oriented metadata production on EuroSDR Geometadatalabs platform [paper and diaporama] / Bénédicte Bucher (2020)    

Permalink

Comparing supervised learning algorithms for Spatial Nominal Entity recognition / Amine Medad (2020)  

Permalink

Distributed and parallel architectures for spatial data / Alberto Belussi (2020)  

Permalink