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Extracting urban functional regions from points of interest and human activities on location-based social networks / Song Gao in Transactions in GIS, vol 21 n° 3 (June 2017)
[article]
Titre : Extracting urban functional regions from points of interest and human activities on location-based social networks Type de document : Article/Communication Auteurs : Song Gao, Auteur ; Krzysztof Janowicz, Auteur ; Helen Couclelis, Auteur Année de publication : 2017 Article en page(s) : pp 446 - 467 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] classification par nuées dynamiques
[Termes IGN] connaissance thématique
[Termes IGN] Etats-Unis
[Termes IGN] point d'intérêt
[Termes IGN] problème de Dirichlet
[Termes IGN] réseau social géodépendant
[Termes IGN] trace GPS
[Termes IGN] triangulation de Delaunay
[Termes IGN] zone urbaineRésumé : (Auteur) Data about points of interest (POI) have been widely used in studying urban land use types and for sensing human behavior. However, it is difficult to quantify the correct mix or the spatial relations among different POI types indicative of specific urban functions. In this research, we develop a statistical framework to help discover semantically meaningful topics and functional regions based on the co-occurrence patterns of POI types. The framework applies the latent Dirichlet allocation (LDA) topic modeling technique and incorporates user check-in activities on location-based social networks. Using a large corpus of about 100,000 Foursquare venues and user check-in behavior in the 10 most populated urban areas of the US, we demonstrate the effectiveness of our proposed methodology by identifying distinctive types of latent topics and, further, by extracting urban functional regions using K-means clustering and Delaunay triangulation spatial constraints clustering. We show that a region can support multiple functions but with different probabilities, while the same type of functional region can span multiple geographically non-adjacent locations. Since each region can be modeled as a vector consisting of multinomial topic distributions, similar regions with regard to their thematic topic signatures can be identified. Compared with remote sensing images which mainly uncover the physical landscape of urban environments, our popularity-based POI topic modeling approach can be seen as a complementary social sensing view on urban space based on human activities. Numéro de notice : A2017-623 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12289 En ligne : http://dx.doi.org/10.1111/tgis.12289 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86938
in Transactions in GIS > vol 21 n° 3 (June 2017) . - pp 446 - 467[article]Information extraction and visualization from twitter considering spatial structure / Hideyuki Fujita in Cartographica, vol 52 n° 2 (Summer 2017)
[article]
Titre : Information extraction and visualization from twitter considering spatial structure Type de document : Article/Communication Auteurs : Hideyuki Fujita, Auteur Année de publication : 2017 Article en page(s) : pp 178 - 193 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] données issues des réseaux sociaux
[Termes IGN] extraction de données
[Termes IGN] géobalise
[Termes IGN] point d'intérêt
[Termes IGN] structure spatiale
[Termes IGN] Twitter
[Termes IGN] utilisateur
[Vedettes matières IGN] GéovisualisationRésumé : (Auteur) Mobile social media represented by Twitter are expected to be a suitable source of data for analyzing human behaviour and statuses of locations. It seems that we can provide location-based information simply by spatially filtering archived data. However, there are several problems in terms of practical use. This research considers in particular problems that concern the relationship between data meaning and their spatial structures. With regard to Twitter, in general, the location from which a tweet is posted is attached to a geotagged tweet. For example, the location coordinates attached to the geotagged tweet “Heavy rain in Miura Peninsula” by NHK (Japan's public broadcaster) are not those of the Miura Peninsula, but of Shibuya in Tokyo (where NHK is located). Therefore, the tweet is not found by a spatial search around the Miura Peninsula or even Kanagawa Prefecture (where the Miura Peninsula is located). To resolve such problems, we propose a framework that distinguishes locations of interest and locations of activity. We propose a method for automatically classifying such locations and develop a data collection, classification, and visualization system based on this method. Numéro de notice : A2017-375 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.3138/cart.52.2.3875 En ligne : https://doi.org/10.3138/cart.52.2.3875 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85800
in Cartographica > vol 52 n° 2 (Summer 2017) . - pp 178 - 193[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 031-2017021 SL Revue Centre de documentation Revues en salle Disponible Demand and supply of cultural ecosystem services: Use of geotagged photos to map the aesthetic value of landscapes in Hokkaido / Nobuhiko Yoshimura in Ecosystem Services, vol 24 (April 2017)
[article]
Titre : Demand and supply of cultural ecosystem services: Use of geotagged photos to map the aesthetic value of landscapes in Hokkaido Type de document : Article/Communication Auteurs : Nobuhiko Yoshimura, Auteur ; Tsutom Hiura, Auteur Année de publication : 2017 Article en page(s) : pp 68 - 78 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] contenu généré par les utilisateurs
[Termes IGN] géobalise
[Termes IGN] GeoWeb
[Termes IGN] Hokkaido (Japon)
[Termes IGN] image Flickr
[Termes IGN] parc naturel
[Termes IGN] réseau social
[Termes IGN] réseautage social
[Termes IGN] service écosystémiqueRésumé : (auteur) We proposed a mapping method for landscape aesthetic demand and potential supply area based on viewsheds, which is a direct method that provides robust results. Moreover, we mapped the aesthetic value of Hokkaido as a case study in Asia.
The Aichi Biodiversity Target refers to the importance of ecosystem service (ES) mapping methodologies. However, ES mapping in policy and practice has rarely been reported. Robust, reliable indicators are required. Recently, studies estimating aesthetic value have used geotagged photos on social networking services instead of survey results of user preferences. The methods used in these studies were cost effective and provided spatially explicit results. However, these methods used the photography positions. Using the photographed sites is a more direct method to estimate the aesthetic demand.
Therefore, we used geotagged photos on Flickr and viewsheds from each photography position to identify the photographed sites. The demand area was estimated using the viewshed. The potential supply area was estimated using MaxEnt. The demand and potential supply areas were concentrated in natural parks. Comparing the demand and potential supply areas indicates areas with potential supply despite their low demand in forest, farmland, and natural parks. This method will contribute to CES research and decision-making.Numéro de notice : A2017-051 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.ecoser.2017.02.009 En ligne : https://doi.org/10.1016/j.ecoser.2017.02.009 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84231
in Ecosystem Services > vol 24 (April 2017) . - pp 68 - 78[article]Improving large area population mapping using geotweet densities / Nirav N. Patel in Transactions in GIS, vol 21 n° 2 (April 2017)
[article]
Titre : Improving large area population mapping using geotweet densities Type de document : Article/Communication Auteurs : Nirav N. Patel, Auteur ; Forrest R. Stevens, Auteur ; Zhuojie Huang, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 317 – 331 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] cartographie dynamique
[Termes IGN] cartographie statistique
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] densité de population
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] Indonésie
[Termes IGN] recensement
[Termes IGN] répartition géographique
[Termes IGN] Twitter
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) Many different methods are used to disaggregate census data and predict population densities to construct finer scale, gridded population data sets. These methods often involve a range of high resolution geospatial covariate datasets on aspects such as urban areas, infrastructure, land cover and topography; such covariates, however, are not directly indicative of the presence of people. Here we tested the potential of geo-located tweets from the social media application, Twitter, as a covariate in the production of population maps. The density of geo-located tweets in 1x1 km grid cells over a 2-month period across Indonesia, a country with one of the highest Twitter usage rates in the world, was input as a covariate into a previously published random forests-based census disaggregation method. Comparison of internal measures of accuracy and external assessments between models built with and without the geotweets showed that increases in population mapping accuracy could be obtained using the geotweet densities as a covariate layer. The work highlights the potential for such social media-derived data in improving our understanding of population distributions and offers promise for more dynamic mapping with such data being continually produced and freely available. Numéro de notice : A2017-166 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/SOCIETE NUMERIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12214 En ligne : http://dx.doi.org/10.1111/tgis.12214 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84700
in Transactions in GIS > vol 21 n° 2 (April 2017) . - pp 317 – 331[article]Building social networks in volunteered geographic information communities: What contributor behaviours reveal about crowdsourced data quality / Quy Thy Truong (2017)
contenu dans Proceedings of workshops and posters at the 13th international conference on spatial information theory (COSIT 2017) / Paolo Fogliaroni (2017)
Titre : Building social networks in volunteered geographic information communities: What contributor behaviours reveal about crowdsourced data quality Type de document : Article/Communication Auteurs : Quy Thy Truong , Auteur ; Guillaume Touya , Auteur ; Cyril de Runz, Auteur Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 2017 Collection : Lecture notes in Geoinformation and Cartography, ISSN 1863-2246 Conférence : COSIT 2017, 13th international conference on spatial information theory 04/09/2017 08/09/2017 L'Aquila Italie Proceedings Springer Importance : pp 125 - 131 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] données localisées des bénévoles
[Termes IGN] OpenStreetMap
[Termes IGN] qualité des données
[Termes IGN] réseau socialRésumé : (auteur) Modelling social interactions in volunteered geographic information projects requires defining what binds contributors together. In order to be as realistic as possible, instead of choosing one social aspect to study, we choose to build a multi-layered social network that contains several types of interaction between VGI contributors. The analysis of such a multigraph should allow the detection of communities and the definition of typical profiles of contributors. A use case on OpenStreetMap illustrates what inferences can be made about contributions based on their authors. Numéro de notice : C2017-017 Affiliation des auteurs : LASTIG COGIT+Ext (2012-2019) Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1007/978-3-319-63946-8_25 Date de publication en ligne : 30/09/2017 En ligne : https://doi.org/10.1007/978-3-319-63946-8_25 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88224 A modelling framework for the study of Spatial Data Infrastructures applied to coastal management and planning / Jade Georis-Creuseveau in International journal of geographical information science IJGIS, vol 31 n° 1-2 (January - February 2017)PermalinkPermalinkTowards a unified narrative-centric spatial clustering model of social media volunteered geographic information / Nick Bennett (2017)PermalinkSig participatif : gagnez du temps et de l'argent / Hubert d' Erceville in SIGmag, n° 11 (décembre 2016)PermalinkCrowdsourcing functions of the living city from Twitter and Foursquare data / Xiaolu Zhou in Cartography and Geographic Information Science, vol 43 n° 5 (November 2016)PermalinkThe socio-environmental data explorer (SEDE) : a social media–enhanced decision support system to explore risk perception to hazard events / Eric Shook in Cartography and Geographic Information Science, vol 43 n° 5 (November 2016)PermalinkAutomatic targeted-domain spatiotemporal event detection in twitter / Ting Hua in Geoinformatica, vol 20 n° 4 (October - December 2016)PermalinkActivity patterns, socioeconomic status and urban spatial structure: what can social media data tell us? / Qunying Huang in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)PermalinkExploration of spatiotemporal and semantic clusters of Twitter data using unsupervised neural networks / Enrico Steiger in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)PermalinkFinding spatial outliers in collective mobility patterns coupled with social ties / Monica Wachowicz in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)Permalink