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A Powerful Correspondence Selection Method for Point Cloud Registration Based on Machine Learning / Wuyong Tao in Photogrammetric Engineering & Remote Sensing, PERS, vol 89 n° 11 (November 2023)
[article]
Titre : A Powerful Correspondence Selection Method for Point Cloud Registration Based on Machine Learning Type de document : Article/Communication Auteurs : Wuyong Tao, Auteur ; Dong Xu, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : pp 703 - 712 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] appariement de points
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] semis de pointsRésumé : (auteur) Correspondence selection is an indispensable process in point cloud registration. The success of point cloud registration largely depends on a good correspondence selection method. For this purpose, a novel correspondence selection method is proposed in this paper. First, two geometric constraints, one of which is proposed in this paper, are used to compute the compatibility score between two correspondences. Then, the feature vectors of the correspondences are constructed according to the compatibility scores between the correspondence and others. A support vector machine classifier is trained to classify the correct and incorrect correspondences by using the feature vectors. The experimental results demonstrate that our method can choose the right correspondences well and get high precision and F-score performance. Also, our method has the best robustness to noise, pointdensity variation, and partial overlap compared to the other methods. Numéro de notice : A2023-237 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.23-00046R2 En ligne : https://doi.org/10.14358/PERS.23-00046R2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103597
in Photogrammetric Engineering & Remote Sensing, PERS > vol 89 n° 11 (November 2023) . - pp 703 - 712[article]Assuring the quality of VGI on land use and land cover: experiences and learnings from the LandSense project / Giles M. Foody in Geo-spatial Information Science, vol 26 n° inconnu ([01/08/2023])
[article]
Titre : Assuring the quality of VGI on land use and land cover: experiences and learnings from the LandSense project Type de document : Article/Communication Auteurs : Giles M. Foody, Auteur ; Gavin Long, Auteur ; Michael Schultz, Auteur ; Ana-Maria Olteanu-Raimond , Auteur Année de publication : 2023 Projets : Landsense / Raimond, Ana-Maria Article en page(s) : n° 2100285 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] assurance qualité
[Termes IGN] données localisées des bénévoles
[Termes IGN] occupation du sol
[Termes IGN] qualité des données
[Termes IGN] utilisation du solRésumé : (auteur) The potential of citizens as a source of geographical information has been recognized for many years. Such activity has grown recently due to the proliferation of inexpensive location aware devices and an ability to share data over the internet. Recently, a series of major projects, often cast as citizen observatories, have helped explore and develop this potential for a wide range of applications. Here, some of the experiences and learnings gained from part of one such project, which aimed to further the role of citizen science within Earth observation and help address environmental challenges, LandSense, are shared. The key focus is on quality assurance of citizen generated data on land use and land cover especially to support analyses of remotely sensed data and products. Particular focus is directed to quality assurance checks on photographic image quality, privacy, polygon overlap, positional accuracy and offset, contributor agreement, and categorical accuracy. The discussion aims to provide good practice advice to aid future studies and help fulfil the full potential of citizens as a source of volunteered geographical information (VGI). Numéro de notice : A2023-081 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10095020.2022.2100285 Date de publication en ligne : 21/07/2022 En ligne : https://doi.org/10.1080/10095020.2022.2100285 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101337
in Geo-spatial Information Science > vol 26 n° inconnu [01/08/2023] . - n° 2100285[article]Quality assessment of volunteered geographic information for outdoor activities: an analysis of OpenStreetMap data for names of peaks in Japan / Jun Yamashita in Geo-spatial Information Science, vol 26 n° inconnu ([01/08/2023])
[article]
Titre : Quality assessment of volunteered geographic information for outdoor activities: an analysis of OpenStreetMap data for names of peaks in Japan Type de document : Article/Communication Auteurs : Jun Yamashita, Auteur ; Toshikazu Seto, Auteur ; Nobusuke Iwasaki, Auteur ; Yuichiro Nishimura, Auteur Année de publication : 2023 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] données localisées des bénévoles
[Termes IGN] Japon
[Termes IGN] montagne
[Termes IGN] OpenStreetMap
[Termes IGN] oronymie
[Termes IGN] qualité des donnéesRésumé : (auteur) Geographical studies of outdoor activities have increased in recent years with the rise in popularity of these activities worldwide, including in Japan. Volunteered geographic information (VGI) is a key tool for organizing outdoor activities as it offers a means to determine the locational information and names of places. To evaluate the quality of VGI, geospatial data generated by land survey agencies and other VGI are often utilized as reference data. However, since these reference data may not be available, other methods are necessary to assure the quality of VGI. In this study, we examined five trust indicators based on the inherent characteristics of VGI through an empirical case study. We used mountain names extracted from OpenStreetMap in Japan as data because there were almost no other VGI in the vicinity. As a result, we isolated three trust indicators, namely versions, users, and tag corrections, to examine the thematic accuracy of VGI because these were the only statistically significant indicators. However, we found that the prediction rate of thematic accuracy was very low. To improve thematic accuracy, this study recommends using the most accurate versions, applying correctly given tags, and considering the motivations and characteristics of the VGI contributors. Numéro de notice : A2022-611 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10095020.2022.2085188 Date de publication en ligne : 01/07/2022 En ligne : https://doi.org/10.1080/10095020.2022.2085188 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101365
in Geo-spatial Information Science > vol 26 n° inconnu [01/08/2023][article]Automatic generation of outline-based representations of landmark buildings with distinctive shapes / Peng Ti in International journal of geographical information science IJGIS, vol 37 n° 4 (April 2023)
[article]
Titre : Automatic generation of outline-based representations of landmark buildings with distinctive shapes Type de document : Article/Communication Auteurs : Peng Ti, Auteur ; Tao Xiong, Auteur ; Yuhong Qiu, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : pp 864 - 884 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Bâti-3D
[Termes IGN] cartographie
[Termes IGN] contour
[Termes IGN] détection du bâti
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] raisonnement spatial
[Termes IGN] reconnaissance de formes
[Termes IGN] segmentation d'image
[Termes IGN] sémiologie graphique
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) Landmark buildings are salient features for spatial cognition on maps. Distinctive outlines are the major visual characteristics that separate landmark buildings from their surrounding environments. The automatic symbolization of landmark outlines facilitates recognition and map production. As users often recognize landmarks by the outlines of their façades from a street view, this study proposes an automatic method for automatically generating representations of the outlines of landmark buildings in four steps: (1) extract outlines from street-view photographs using GrabCut method, (2) vectorize the extracted building outlines, (3) simplify outline shapes, and (4) symbolize the simplified building outlines in three dimensions (3D). We used the proposed method to generate test data with symbolized outlines for eight buildings in a real-world environment for a wayfinding experiment in which the subjects used the building representations to identify landmark buildings and evaluated their perception of the generated maps. The subjects successfully recognized these buildings based on the symbolized outlines on a map, expressed satisfaction with the manually generated 3D symbols, and reported the same or similar ease of building recognition using 2D or 3D symbolized outlines. Numéro de notice : A2023-207 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2022.2143503 Date de publication en ligne : 11/11/2022 En ligne : https://doi.org/10.1080/13658816.2022.2143503 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103109
in International journal of geographical information science IJGIS > vol 37 n° 4 (April 2023) . - pp 864 - 884[article]Methods for matching English language addresses / Keshav Ramani in Transactions in GIS, vol 27 n° 2 (april 2023)
[article]
Titre : Methods for matching English language addresses Type de document : Article/Communication Auteurs : Keshav Ramani, Auteur ; Daniel Borrajo, Auteur Année de publication : 2023 Article en page(s) : pp 347 - 363 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] anglais (langue)
[Termes IGN] appariement d'adresses
[Termes IGN] apprentissage profond
[Termes IGN] base de données d'adresses
[Termes IGN] conversion de donnéesRésumé : (auteur) Addresses occupy a niche location within the landscape of textual data, due to the positional importance carried by every word, and the geographic scope it refers to. The task of matching addresses happens every day and is present in various fields such as mail redirection, entity resolution, etc. Our work defines, and formalizes a framework to generate matching and mismatching pairs of addresses in the English language, and use it to evaluate various methods to automatically perform address matching. These methods vary widely from distance-based approaches to deep learning models. By studying the Precision, Recall, and Accuracy metrics of these approaches, we obtain an understanding of the best suited method for this setting of the address matching task. Numéro de notice : A2023-195 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1111/tgis.13027 Date de publication en ligne : 17/03/2023 En ligne : https://doi.org/10.1111/tgis.13027 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103080
in Transactions in GIS > vol 27 n° 2 (april 2023) . - pp 347 - 363[article]Towards global scale segmentation with OpenStreetMap and remote sensing / Munazza Usmani in ISPRS Open Journal of Photogrammetry and Remote Sensing, vol 8 (April 2023)PermalinkDeriving map images of generalised mountain roads with generative adversarial networks / Azelle Courtial in International journal of geographical information science IJGIS, vol 37 n° 3 (March 2023)PermalinkGeneration of concise 3D building model from dense meshes by extracting and completing planar primitives / Xinyi Liu in Photogrammetric record, vol 38 n° 181 (March 2023)PermalinkA graph-based approach for representing addresses in geocoding / Chen Zhang in Computers, Environment and Urban Systems, vol 100 (March 2023)PermalinkMapping population distribution from open address data: application to mainland Portugal / Nelson Mileu in Journal of maps, vol 18 n° 3 (March 2023)PermalinkSALT: A multifeature ensemble learning framework for mapping urban functional zones from VGI data and VHR images / Hao Wu in Computers, Environment and Urban Systems, vol 100 (March 2023)PermalinkSiamese KPConv: 3D multiple change detection from raw point clouds using deep learning / Iris de Gelis in ISPRS Journal of photogrammetry and remote sensing, vol 197 (March 2023)PermalinkA spatiotemporal data model and an index structure for computational time geography / Bi Yu Chen in International journal of geographical information science IJGIS, vol 37 n° 3 (March 2023)PermalinkWho owns the map? Data sovereignty and government spatial data collection, use, and dissemination / Peter A. Johnson in Transactions in GIS, vol 27 n° 1 (February 2023)PermalinkAnalysing urban growth using machine learning and open data: An artificial neural network modelled case study of five Greek cities / Pavlos Tsagkis in Sustainable Cities and Society, vol 89 (February 2023)PermalinkComparative analysis of different CNN models for building segmentation from satellite and UAV images / Batuhan Sariturk in Photogrammetric Engineering & Remote Sensing, PERS, vol 89 n° 2 (February 2023)PermalinkIdentification of enclaves and exclaves by computation based on point-set topology / Xiaonan Wang in International journal of geographical information science IJGIS, vol 37 n° 2 (February 2023)PermalinkIs 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)PermalinkLarge-scale burn severity mapping in multispectral imagery using deep semantic segmentation models / Xikun Hu in ISPRS Journal of photogrammetry and remote sensing, vol 196 (February 2023)PermalinkMulti-agent reinforcement learning to unify order-matching and vehicle-repositioning in ride-hailing services / Mingyue Xu in International journal of geographical information science IJGIS, vol 37 n° 2 (February 2023)PermalinkWhere am I now? modelling disorientation in pan-scalar maps / Guillaume Touya in ISPRS International journal of geo-information, vol 12 n° 2 (February 2023)PermalinkAnalysis of cycling network evolution in OpenStreetMap through a data quality prism / Raphaël Bres (2023)PermalinkPermalinkCorrelation of road network structure and urban mobility intensity: An exploratory study using geo-tagged tweets / Li Geng in ISPRS International journal of geo-information, vol 12 n° 1 (January 2023)PermalinkPermalinkGeographically masking addresses to study COVID-19 clusters / Walid Houfaf-Khoufaf in Cartography and Geographic Information Science, vol inconnu (2023)PermalinkGeoMultiTaskNet: remote sensing unsupervised domain adaptation using geographical coordinates / Valerio Marsocci (2023)PermalinkGeospatial-based machine learning techniques for land use and land cover mapping using a high-resolution unmanned aerial vehicle image / Taposh Mollick in Remote Sensing Applications: Society and Environment, RSASE, vol 29 (January 2023)PermalinkA hexagon-based method for polygon generalization using morphological operators / Lu Wang in International journal of geographical information science IJGIS, vol 37 n° 1 (January 2023)PermalinkHGAT-VCA: Integrating high-order graph attention network with vector cellular automata for urban growth simulation / Xuefeng Guan in Computers, Environment and Urban Systems, vol 99 (January 2023)PermalinkA hierarchical multiview registration framework of TLS point clouds based on loop constraint / Hao Wu in ISPRS Journal of photogrammetry and remote sensing, vol 195 (January 2023)PermalinkIncorporating ideas of structure and meaning in interactive multi scale mapping environments / Guillaume Touya in International journal of cartography, vol inconnu (2023)PermalinkLandscape metrics regularly outperform other traditionally-used ancillary datasets in dasymetric mapping of population / Heng Wan in Computers, Environment and Urban Systems, vol 99 (January 2023)PermalinkLinear building pattern recognition in topographical maps combining convex polygon decomposition / Zhiwei Wei in Geocarto international, vol 38 n° inconnu ([01/01/2023])PermalinkMachine learning remote sensing using the random forest classifier to detect the building damage caused by the Anak Krakatau Volcano tsunami / Riantini Virtriana in Geomatics, Natural Hazards and Risk, vol 14 n° 1 (2023)PermalinkMeasuring metro accessibility: An exploratory study of Wuhan based on multi-source urban data / Tao Wu in ISPRS International journal of geo-information, vol 12 n° 1 (January 2023)PermalinkA method for remote sensing image classification by combining Pixel Neighbourhood Similarity and optimal feature combination / Kaili Zhang in Geocarto international, vol 38 n° 1 ([01/01/2023])PermalinkMitigating the risk of wind damage at the forest landscape level by using stand neighbourhood and terrain elevation information in forest planning / Roope Ruotsalainen in Forestry, an international journal of forest research, vol 96 n° 1 (January 2023)PermalinkModern vectorization and alignment of historical maps: An application to Paris Atlas (1789-1950) / Yizi Chen (2023)PermalinkPermalinkSemi-automated Pipeline to Produce Customizable Tactile Maps of Street Intersections for People with Visual Impairments / Yuhao Jiang (2023)PermalinkThe cellular automata approach in dynamic modelling of land use change detection and future simulations based on remote sensing data in Lahore Pakistan / Muhammad Nasar Ahmad in Photogrammetric Engineering & Remote Sensing, PERS, vol 89 n° 1 (January 2023)PermalinkUsing Google Earth Engine to classify unique forest and agroforest classes using a mix of Sentinel 2a spectral data and topographical features: a Sri Lanka case study / W.D.K.V. Nandasena in Geocarto international, vol 38 n° inconnu ([01/01/2023])PermalinkAutomatic registration method of multi-source point clouds based on building facades matching in urban scenes / Yumin Tan in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 12 (December 2022)PermalinkAutomatic registration of point cloud and panoramic images in urban scenes based on pole matching / Yuan Wang in International journal of applied Earth observation and geoinformation, vol 115 (December 2022)PermalinkCoastal land use and shoreline evolution along the Nador lagoon Coast in Morocco / Khalid El Khalidi in Geocarto international, vol 37 n° 25 ([01/12/2022])PermalinkHyperspectral imagery and urban areas: results of the HYEP project / Christiane Weber in Revue Française de Photogrammétrie et de Télédétection, n° 224 (2022)PermalinkIntegration of geospatial technologies with multiple regression model for urban land use land cover change analysis and its impact on land surface temperature in Jimma City, southwestern Ethiopia / Mitiku Badasa Moisa in Applied geomatics, vol 14 n° 4 (December 2022)PermalinkLinkClimate: An interoperable knowledge graph platform for climate data / Jiantao Wu in Computers & geosciences, vol 169 (December 2022)PermalinkMapping impervious surfaces with a hierarchical spectral mixture analysis incorporating endmember spatial distribution / Zhenfeng Shao in Geo-spatial Information Science, vol 25 n° 4 (December 2022)Permalink