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VGI3D: an interactive and low-cost solution for 3D building modelling from street-level VGI images / Chaoquan Zhang in Journal of Geovisualization and Spatial Analysis, vol 5 n° 2 (December 2021)
[article]
Titre : VGI3D: an interactive and low-cost solution for 3D building modelling from street-level VGI images Type de document : Article/Communication Auteurs : Chaoquan Zhang, Auteur ; Hongchao Fan, Auteur ; Gefei Kong, Auteur Année de publication : 2021 Article en page(s) : n° 18 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] analyse de sensibilité
[Termes IGN] approche participative
[Termes IGN] base de données relationnelles
[Termes IGN] CityGML
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] données localisées des bénévoles
[Termes IGN] information sémantique
[Termes IGN] interactivité
[Termes IGN] modélisation 3D du bâti BIM
[Termes IGN] reconstruction 3D du bâtiRésumé : (auteur) Applications in smart cities are inseparable from the usage of three-dimensional (3D) building models. However, the cost of generating and constructing 3D building models with semantic information is high both in time and in labour. To solve this problem, we developed a web-based interactive system, VGI3D, with the ambition of becoming a VGI platform to collect 3D building models with semantic information by using the power of crowdsourcing. VGI3D is a platform-independent software program that is composed of a spatially relational database (PostgreSQL/PostGIS) for the storage and management of spatially geometrical data and other software modules, allowing users to import, analyse, reconstruct, visualise, modify and export 3D building models according to the OBJ/CityGML standard. In this paper, we present the VGI3D in detail, focusing on relevant technical implementations, and report the results of limited usability testing aimed at optimising the system and user experience. After limited expert and non-expert participants’ testing, we proved the usefulness of VGI3D and its promising value for the 3D modelling community. Numéro de notice : A2021-884 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s41651-021-00086-7 Date de publication en ligne : 23/09/2021 En ligne : https://doi.org/10.1007/s41651-021-00086-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99205
in Journal of Geovisualization and Spatial Analysis > vol 5 n° 2 (December 2021) . - n° 18[article]Analytics of location-based big data for smart cities: Opportunities, challenges, and future directions / Haosheng Huang in Computers, Environment and Urban Systems, vol 90 (November 2021)
[article]
Titre : Analytics of location-based big data for smart cities: Opportunities, challenges, and future directions Type de document : Article/Communication Auteurs : Haosheng Huang, Auteur ; Xiaobai Yao, Auteur ; Jukka Mathias Krisp, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 101712 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] données localisées des bénévoles
[Termes IGN] données massives
[Termes IGN] planification urbaine
[Termes IGN] service fondé sur la position
[Termes IGN] téléphonie mobile
[Termes IGN] ville durable
[Termes IGN] ville intelligenteRésumé : (auteur) The growing ubiquity of location/activity sensing technologies and location-based services (LBS) has led to a large volume and variety of location-based big data (LocBigData), such as location tracking or sensing data, social media data, and crowdsourced geographic information. The increasing availability of such LocBigData has created unprecedented opportunities for research on urban systems and human environments in general. In this article, we first review the common types of LocBigData: mobile phone network data, GPS data, Location-based social media data, LBS usage/log data, smart card travel data, beacon log data (WiFi or Bluetooth), and camera imagery data. Secondly, we describe the opportunities fueled by LocBigData for the realization of smart cities, mainly via answering questions ranging from “what happened” and “why did it happen” to “what's likely to happen in the future” and “what to do next”. Thirdly, pitfalls of dealing with LocBigData are summarized, such as high volume/velocity/variety; non-random sampling; messy and not clean data; and correlations rather than causal relationships. Finally, we review the state-of-the-art research trends in this field, and conclude the article with a list of open research challenges and a research agenda for LocBigData research to help achieve the vision of smart and sustainable cities. Numéro de notice : A2021-650 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article DOI : 10.1016/j.compenvurbsys.2021.101712 Date de publication en ligne : 08/09/2021 En ligne : https://doi.org/10.1016/j.compenvurbsys.2021.101712 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98368
in Computers, Environment and Urban Systems > vol 90 (November 2021) . - n° 101712[article]Point-of-interest (POI) data validation methods: An urban case study / Lih Wei Yeow in ISPRS International journal of geo-information, vol 10 n° 11 (November 2021)
[article]
Titre : Point-of-interest (POI) data validation methods: An urban case study Type de document : Article/Communication Auteurs : Lih Wei Yeow, Auteur ; Raymond Low, Auteur ; Yu Xiang Tan, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 735 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] analyse spatiale
[Termes IGN] données cartographiques
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] données localisées des bénévoles
[Termes IGN] erreur de positionnement
[Termes IGN] OpenStreetMap
[Termes IGN] point d'intérêt
[Termes IGN] qualité des données
[Termes IGN] Singapour
[Termes IGN] validation des donnéesRésumé : (auteur) Point-of-interest (POI) data from map sources are increasingly used in a wide range of applications, including real estate, land use, and transport planning. However, uncertainties in data quality arise from the fact that some of this data are crowdsourced and proprietary validation workflows lack transparency. Comparing data quality between POI sources without standardized validation metrics is a challenge. This study reviews and implements the available POI validation methods, working towards identifying a set of metrics that is applicable across datasets. Twenty-three validation methods were found and categorized. Most methods evaluated positional accuracy, while logical consistency and usability were the least represented. A subset of nine methods was implemented to assess four real-world POI datasets extracted for a highly urbanized neighborhood in Singapore. The datasets were found to have poor completeness with errors of commission and omission, although spatial errors were reasonably low ( Numéro de notice : A2021-830 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10110735 Date de publication en ligne : 29/10/2021 En ligne : https://doi.org/10.3390/ijgi10110735 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98968
in ISPRS International journal of geo-information > vol 10 n° 11 (November 2021) . - n° 735[article]Urban land-use analysis using proximate sensing imagery: a survey / Zhinan Qiao in International journal of geographical information science IJGIS, vol 35 n° 11 (November 2021)
[article]
Titre : Urban land-use analysis using proximate sensing imagery: a survey Type de document : Article/Communication Auteurs : Zhinan Qiao, Auteur ; Xiaohui Yuan, Auteur Année de publication : 2021 Article en page(s) : pp 2129 - 2148 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] détection d'objet
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] données localisées des bénévoles
[Termes IGN] image Streetview
[Termes IGN] utilisation du sol
[Termes IGN] zone urbaineRésumé : (auteur) Urban regions are complicated functional systems that are closely associated with and reshaped by human activities. The propagation of online geographic information-sharing platforms and mobile devices equipped with the Global Positioning System (GPS) greatly proliferates proximate sensing images taken near or on the ground at a close distance to urban targets. Studies leveraging proximate sensing images have demonstrated great potential to address the need for local data in the urban land-use analysis. This paper reviews and summarizes the state-of-the-art methods and publicly available data sets from proximate sensing to support land-use analysis. We identify several research problems in the perspective of examples to support the training of models and means of integrating diverse data sets. Our discussions highlight the challenges, strategies, and opportunities faced by the existing methods using proximate sensing images in urban land-use studies. Numéro de notice : A2021-759 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.1919682 Date de publication en ligne : 03/05/2021 En ligne : https://doi.org/10.1080/13658816.2021.1919682 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98788
in International journal of geographical information science IJGIS > vol 35 n° 11 (November 2021) . - pp 2129 - 2148[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2021111 SL Revue Centre de documentation Revues en salle Disponible Disaster Image Classification by Fusing Multimodal Social Media Data / Zhiqiang Zou in ISPRS International journal of geo-information, vol 10 n° 10 (October 2021)
[article]
Titre : Disaster Image Classification by Fusing Multimodal Social Media Data Type de document : Article/Communication Auteurs : Zhiqiang Zou, Auteur ; Hongyu Gan, Auteur ; Qunying Huang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 636 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] analyse visuelle
[Termes IGN] apprentissage profond
[Termes IGN] catastrophe naturelle
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] corpus
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] données localisées des bénévoles
[Termes IGN] données massives
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] fusion de données multisource
[Termes IGN] qualité des données
[Termes IGN] traitement de donnéesNuméro de notice : A2021-803 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10100636 Date de publication en ligne : 24/09/2021 En ligne : https://doi.org/10.3390/ijgi10100636 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98856
in ISPRS International journal of geo-information > vol 10 n° 10 (October 2021) . - n° 636[article]Impact of travel time uncertainties on modeling of spatial accessibility: a comparison of street data sources / Yan Lin in Cartography and Geographic Information Science, vol 48 n° 6 (October 2021)PermalinkBenford’s law and geographical information – the example of OpenStreetMap / Franz-Benjamin Mocnik in International journal of geographical information science IJGIS, vol 35 n° 9 (September 2021)PermalinkThe willingness of volonteers to report changes on topographic maps / Mihaela Triglav Cekada in Geodetski vestnik, vol 65 n° 3 (September - November 2021)PermalinkTowards generating network of bikeways from Mapillary data / Xuan Ding in Computers, Environment and Urban Systems, vol 88 (July 2021)PermalinkA framework for classification of volunteered geographic data based on user’s need / Nazila Mohammadi in Geocarto international, vol 36 n° 11 ([15/06/2021])PermalinkTowards detecting, characterizing, and rating of road class errors in crowd-sourced road network databases / Johanna Guth in Journal of Spatial Information Science (JoSIS), n° 22 (2021)PermalinkCrowdsourcing of popular toponyms: How to collect and preserve toponyms in spoken use / Daniel Vrbik in ISPRS International journal of geo-information, vol 10 n° 5 (May 2021)PermalinkQuality assessment of heterogeneous training data sets for classification of urban area with Landsat imagery / Neema Nicodemus Lyimo in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 5 (May 2021)PermalinkUnderstanding collective human movement dynamics during large-scale events using big geosocial data analytics / Junchuan Fan in Computers, Environment and Urban Systems, vol 87 (May 2021)Permalink1996–2017 GPS position time series, velocities and quality measures for the CORS Network / Jarir Saleh in Journal of applied geodesy, vol 15 n° 2 (April 2021)Permalink