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Semantic integration of OpenStreetMap and CityGML with formal concept analysis / Somayeh Ahmadian in Transactions in GIS, vol 26 n° 8 (December 2022)  

Public [article]  inTransactions in GIS > vol 26 n° 8 (December 2022) . - pp 3349 - 3373 Titre : Semantic integration of OpenStreetMap and CityGML with formal concept analysis Type de document : Article/Communication Auteurs : Somayeh Ahmadian, Auteur ; Parham Pahlavani, Auteur Année de publication : 2022 Article en page(s) : pp 3349 - 3373 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] analyse de groupement [Termes IGN] bâtiment [Termes IGN] CityGML [Termes IGN] classification par nuées dynamiques [Termes IGN] données localisées des bénévoles [Termes IGN] information sémantique [Termes IGN] ontologie [Termes IGN] OpenStreetMap [Termes IGN] qualité des données [Termes IGN] réseau sémantique Résumé : (auteur) Volunteered geographic information (VGI) provides geometric and descriptive sources of geospatial data. VGI exchange, reuse, and integration are serious challenges due to the subjective contribution process, lack of organization, and redundancy. This study aims to enhance the quality of VGI semantic data by presenting a new approach to integrating and formalizing the VGI semantic knowledge using formal concept analysis. The proposed approach is assessed using the building tags in OpenStreetMap (OSM) and CityGML. The alignment process discovers the conceptual overlap between the categories of Amenity (Others), Office, and Man-Made in Map Features (OSM) and Business and Trade, Recreation, Sport, and Industry in AbstractBuilding (CityGML). The k-means clustering of the results illustrated that class, usage/function, address, wheelchair, and website/wikidata/wikipedia are significant attributes to describe building categories. Moreover, results showed that the analysis of frequent itemsets and cluster characteristics provides significant information about custom tags in OSM's editing tools. Numéro de notice : A2022-909 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1111/tgis.13006 Date de publication en ligne : 02/12/2022 En ligne : https://doi.org/10.1111/tgis.13006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102347 [article]

Generation of digital terrain model for forest areas using a new particle swarm optimization on LiDAR data / Behnaz Bigdeli in Survey review, vol 52 n° 371 (March 2020)  

Public [article]  inSurvey review > vol 52 n° 371 (March 2020) . - pp 115 - 125 Titre : Generation of digital terrain model for forest areas using a new particle swarm optimization on LiDAR data Type de document : Article/Communication Auteurs : Behnaz Bigdeli, Auteur ; Masoomeh Gomroki, Auteur ; Parham Pahlavani, Auteur Année de publication : 2020 Article en page(s) : pp 115 - 125 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] données lidar [Termes IGN] erreur moyenne quadratique [Termes IGN] filtrage de la végétation [Termes IGN] interpolation polynomiale [Termes IGN] Iran [Termes IGN] modèle numérique de terrain [Termes IGN] optimisation par essaim de particules [Termes IGN] semis de points [Termes IGN] surface forestière Résumé : (auteur) Since Light Detection and Ranging (LiDAR) data are capable of distinguishing vegetation from bare earth, these data are used nowadays to produce digital terrain models (DTMs) for forest regions. In this research, raw LiDAR data were filtered using hybrid and slope-based filtering methods and the filtered data were then interpolated using the new modified particle swarm optimisation (PSO) and accordingly the results were compared with those achieved by the other intelligent and conventional interpolation methods. The new modified PSO optimized the polynomial degree for interpolation and found suitable parameters for optimisation. Two data sets from two forest regions in some northern regions of Iran located in Golestan province were selected to compare these methods. Region 1 with dense vegetation and region 2 with grass vegetation. The results indicated that the hybrid filter performed lower RMSE than the slope-based filter. Finally, the DTM with lowest RMSE was obtained using the hybrid filter and the modified PSO interpolation method with RMSE of 6 mm for region 1 (Tavar-kuh) and 61 mm for region 2 (Shastkola River Basin). Numéro de notice : A2020-078 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2018.1530331 Date de publication en ligne : 10/10/2018 En ligne : https://doi.org/10.1080/00396265.2018.1530331 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94640 [article]