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Is the radial distance really a distance? An analysis of its properties and interest for the matching of polygon features / Yann Méneroux in International journal of geographical information science IJGIS, vol 37 n° 2 (February 2023)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 37 n° 2 (February 2023) . - 38 p. Titre : Is the radial distance really a distance? An analysis of its properties and interest for the matching of polygon features Type de document : Article/Communication Auteurs : Yann Méneroux , Auteur ; Ibrahim Maidaneh Abdi, Auteur ; Arnaud Le Guilcher , Auteur ; Ana-Maria Olteanu-Raimond , Auteur Année de publication : 2023 Projets : 3-projet - voir note / Article en page(s) : 38 p. Note générale : bibliographie This work was supported by the French National Mapping Agency: Institut National de l’Information Géographique et Forestière (IGN) and by the University of Djibouti Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] abaque [Termes IGN] algorithme de Douglas-Peucker [Termes IGN] appariement de formes [Termes IGN] bâtiment [Termes IGN] BD Topo [Termes IGN] distance [Termes IGN] généralisation [Termes IGN] géométrie analytique [Termes IGN] modèle analytique [Termes IGN] polygone [Termes IGN] propagation d'erreur [Termes IGN] transformation rapide de Fourier Résumé : (auteur) In this paper, we examine the properties of the radial distance which has been used as a tool to compare the shape of simple surfacic objects. We give a rigorous definition of the radial distance and derive its theoretical properties, and in particular under which conditions it satisfies the distance properties. We show how the computation of the radial distance can be implemented in practice and made faster by the use of an analytical formula and a Fast Fourier Transform. Finally, we conduct experiments to measure how the radial distance is impacted by perturbation and generalization and we give abacuses and thresholds to deduce when buildings are likely to be homologous or non-homologous given their radial distance. Numéro de notice : A2023-074 Affiliation des auteurs : UGE-LASTIG (2020- ) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2022.2123487 Date de publication en ligne : 23/09/2022 En ligne : https://doi.org/10.1080/13658816.2022.2123487 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101671 [article]

A regression model of spatial accuracy prediction for Openstreetmap buildings / Ibrahim Maidaneh Abdi in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, V-4 (August 2020)  

Public [article]  inISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > V-4 (August 2020) . - pp 39 - 47 Titre : A regression model of spatial accuracy prediction for Openstreetmap buildings Type de document : Article/Communication Auteurs : Ibrahim Maidaneh Abdi, Auteur ; Arnaud Le Guilcher , Auteur ; Ana-Maria Olteanu-Raimond , Auteur Année de publication : 2020 Projets : 1-Pas de projet / Conférence : ISPRS 2020, Commission 4, virtual Congress, Imaging today foreseeing tomorrow 31/08/2020 02/09/2020 Nice (en ligne) France Annals Commission 4 Article en page(s) : pp 39 - 47 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] apprentissage automatique [Termes IGN] bati [Termes IGN] modèle de régression [Termes IGN] OpenStreetMap [Termes IGN] précision géométrique (imagerie) [Termes IGN] qualité des données Résumé : (auteur) Data quality assessment of OpenStreetMap (OSM) data can be carried out by comparing them with a reference spatial data (e.g authoritative data). However, in case of a lack of reference data, the spatial accuracy is unknown. The aim of this work is therefore to propose a framework to infer relative spatial accuracy of OSM data by using machine learning methods. Our approach is based on the hypothesis that there is a relationship between extrinsic and intrinsic quality measures. Thus, starting from a multi-criteria data matching, the process seeks to establish a statistical relationship between measures of extrinsic quality of OSM (i.e. obtained by comparison with reference spatial data) and the measures of intrinsic quality of OSM (i.e. OSM features themselves) in order to estimate extrinsic quality on an unevaluated OSM dataset. The approach was applied on OSM buildings. On our dataset, the resulting regression model predicts the values on the extrinsic quality indicators with 30% less variance than an uninformed predictor. Numéro de notice : A2020-506 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-V-4-2020-39-2020 Date de publication en ligne : 03/08/2020 En ligne : https://doi.org/10.5194/isprs-annals-V-4-2020-39-2020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95647 [article]