Descripteur
Termes IGN > sciences humaines et sociales > sociologie > société de l'information > contenu généré par les utilisateurs
contenu généré par les utilisateursVoir aussi |
Documents disponibles dans cette catégorie (122)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
The geography of social media data in urban areas: Representativeness and complementarity / Alvaro Bernabeu-Bautista in ISPRS International journal of geo-information, vol 10 n° 11 (November 2021)
[article]
Titre : The geography of social media data in urban areas: Representativeness and complementarity Type de document : Article/Communication Auteurs : Alvaro Bernabeu-Bautista, Auteur ; Leticia Serrano-Estrada, Auteur ; V. Raul Perez-Sanchez, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 747 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] analyse socio-économique
[Termes IGN] analyse spatiale
[Termes IGN] données démographiques
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] données massives
[Termes IGN] données socio-économiques
[Termes IGN] géolocalisation
[Termes IGN] réseau social géodépendant
[Termes IGN] Valence (Espagne)
[Termes IGN] zone urbaineRésumé : (auteur) This research sheds light on the relationship between the presence of location-based social network (LBSN) data and other economic and demographic variables in the city of Valencia (Spain). For that purpose, a comparison is made between location patterns of geolocated data from various social networks (i.e., Google Places, Foursquare, Twitter, Airbnb and Idealista) and statistical information such as land value, average gross income, and population distribution by age range. The main findings show that there is no direct relationship between land value or age of registered population and the amount of social network data generated in a given area. However, a noteworthy coincidence was observed between Google Places data-clustering patterns, which represent the offer of economic activities, and the spatial concentration of the other LBSNs analyzed, suggesting that data from these sources are mostly generated in areas with a high density of economic activities. Numéro de notice : A2021-828 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10110747 Date de publication en ligne : 03/11/2021 En ligne : https://doi.org/10.3390/ijgi10110747 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98965
in ISPRS International journal of geo-information > vol 10 n° 11 (November 2021) . - n° 747[article]A topic model based framework for identifying the distribution of demand for relief supplies using social media data / Ting Zhang in International journal of geographical information science IJGIS, vol 35 n° 11 (November 2021)
[article]
Titre : A topic model based framework for identifying the distribution of demand for relief supplies using social media data Type de document : Article/Communication Auteurs : Ting Zhang, Auteur ; Shi Shen, Auteur ; Changxiu Cheng, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 2216 - 2237 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] allocation de Dirichlet latente
[Termes IGN] cartographie thématique
[Termes IGN] catastrophe naturelle
[Termes IGN] cyclone
[Termes IGN] distribution spatiale
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] Pacifique ouest
[Termes IGN] Philippines
[Termes IGN] répertoire toponymique
[Termes IGN] secours d'urgenceRésumé : (auteur) Natural disasters have caused substantial economic losses and numerous casualties. The demand analysis of relief supplies is the premise and basis for efficient relief operations after disasters. With the widespread use of social media, it has become a vital channel for people to report their demand for relief supplies and provides a way to obtain information on disaster areas. Therefore, we present a topic model-based framework and establish a demand dictionary and a gazetteer that aims to identify the spatial distribution of the demand for relief supplies by using social media data. Taking the 2013 Typhoon Haiyan (also called Yolanda) as a case study, we identify the potential topics of tweets with the biterm topic model, screen the tweets related to demands, and obtain the demand and location information from tweets to study the distribution of the relief supplies needs. The results show that, based on the demand dictionary, a gazetteer and the biterm topic model, the effective demand for relief supplies can be extracted from tweets. The proposed framework is feasible for the identification of accurate demand information and its distribution. Further, this framework can be applied to other types of disaster responses and can facilitate relief operations. Numéro de notice : A2021-757 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1869746 Date de publication en ligne : 07/01/2021 En ligne : https://doi.org/10.1080/13658816.2020.1869746 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98772
in International journal of geographical information science IJGIS > vol 35 n° 11 (November 2021) . - pp 2216 - 2237[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 079-2021111 SL Revue Centre de documentation Revues en salle Disponible 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
Réserver ce documentExemplaires(1)
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]Understanding the modifiable areal unit problem in dockless bike sharing usage and exploring the interactive effects of built environment factors / Feng Gao in International journal of geographical information science IJGIS, vol 35 n° 9 (September 2021)
[article]
Titre : Understanding the modifiable areal unit problem in dockless bike sharing usage and exploring the interactive effects of built environment factors Type de document : Article/Communication Auteurs : Feng Gao, Auteur ; Shaoying Li, Auteur ; Zhangzhi Tan, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1905 - 1925 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] aménagement du territoire
[Termes IGN] bicyclette
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] mobilité urbaine
[Termes IGN] origine - destination
[Termes IGN] planification urbaine
[Termes IGN] problème d'unité zonale modifiable
[Termes IGN] ShenzhenRésumé : (auteur) Understanding the influence mechanisms of dockless bike-sharing usage is essential for land use planning and bike scheduling strategy implementation. Although various studies have been carried out to explore the impact of built environment (BE) factors on bike-sharing usage, few studies have examined the modifiable areal unit problem (MAUP). Moreover, previous studies mainly focused on the separate effect of each factor but neglected the interactions between these factors. Taking Shenzhen, China as the case, this study fills these two gaps by employing the geographical detector method to examine the MAUP in dockless bike-sharing usage as well as the interactive effects of BE factors. The results revealed that the influences of most BE variables are sensitive to the spatial areal units, which have informed urban planners what built-environment factors should be paid more attention to at certain spatial scales. Additionally, through the comparisons between single effect and interactive effect, this study revealed some interesting findings that can provide scientific basis for temporal rebalance strategy for the innovative and high-density metropolis in China. Numéro de notice : A2021-593 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1863410 Date de publication en ligne : 05/01/2021 En ligne : https://doi.org/10.1080/13658816.2020.1863410 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98214
in International journal of geographical information science IJGIS > vol 35 n° 9 (September 2021) . - pp 1905 - 1925[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 079-2021091 SL Revue Centre de documentation Revues en salle Disponible Predicting user activity intensity using geographic interactions based on social media check-in data / Jing Li in ISPRS International journal of geo-information, vol 10 n° 8 (August 2021)PermalinkIdentifying home locations in human mobility data: an open-source R package for comparison and reproducibility / Qingqing Chen in International journal of geographical information science IJGIS, vol 35 n° 7 (July 2021)PermalinkConstructing and analyzing spatial-social networks from location-based social media data / Xuebin Wei in Cartography and Geographic Information Science, vol 48 n° 3 (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)PermalinkStop-and-move sequence expressions over semantic trajectories / Yenier Torres Izquierdo in International journal of geographical information science IJGIS, vol 35 n° 4 (April 2021)PermalinkUtilizing urban geospatial data to understand heritage attractiveness in Amsterdam / Sevim Sezi Karayazi in ISPRS International journal of geo-information, vol 10 n° 4 (April 2021)PermalinkLearning from GPS trajectories of floating car for CNN-based urban road extraction with high-resolution satellite imagery / Ju Zhang in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 3 (March 2021)PermalinkDetection of pictorial map objects with convolutional neural networks / Raimund Schnürer in Cartographic journal (the), vol 58 n° 1 (February 2021)PermalinkJoint promotion partner recommendation systems using data from location-based social networks / Yi-Chung Chen in ISPRS International journal of geo-information, vol 10 n° 2 (February 2021)PermalinkChinese 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