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Understanding 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)
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Titre : Understanding collective human movement dynamics during large-scale events using big geosocial data analytics Type de document : Article/Communication Auteurs : Junchuan Fan, Auteur ; Kathleen Stewart, Auteur Année de publication : 2021 Article en page(s) : n° 101605 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes descripteurs IGN] collecte de données
[Termes descripteurs IGN] données GPS
[Termes descripteurs IGN] données issues des réseaux sociaux
[Termes descripteurs IGN] données localisées des bénévoles
[Termes descripteurs IGN] données massives
[Termes descripteurs IGN] dynamique spatiale
[Termes descripteurs IGN] échantillonnage de données
[Termes descripteurs IGN] éclipse solaire
[Termes descripteurs IGN] estimation par noyau
[Termes descripteurs IGN] Etats-Unis
[Termes descripteurs IGN] événement
[Termes descripteurs IGN] géolocalisation
[Termes descripteurs IGN] migration humaine
[Termes descripteurs IGN] mobilité territoriale
[Termes descripteurs IGN] téléphonie mobileRésumé : (auteur) Conventional approaches for modeling human mobility pattern often focus on human activity and movement dynamics in their regular daily lives and cannot capture changes in human movement dynamics in response to large-scale events. With the rapid advancement of information and communication technologies, many researchers have adopted alternative data sources (e.g., cell phone records, GPS trajectory data) from private data vendors to study human movement dynamics in response to large-scale natural or societal events. Big geosocial data such as georeferenced tweets are publicly available and dynamically evolving as real-world events are happening, making it more likely to capture the real-time sentiments and responses of populations. However, precisely-geolocated geosocial data is scarce and biased toward urban population centers. In this research, we developed a big geosocial data analytical framework for extracting human movement dynamics in response to large-scale events from publicly available georeferenced tweets. The framework includes a two-stage data collection module that collects data in a more targeted fashion in order to mitigate the data scarcity issue of georeferenced tweets; in addition, a variable bandwidth kernel density estimation(VB-KDE) approach was adopted to fuse georeference information at different spatial scales, further augmenting the signals of human movement dynamics contained in georeferenced tweets. To correct for the sampling bias of georeferenced tweets, we adjusted the number of tweets for different spatial units (e.g., county, state) by population. To demonstrate the performance of the proposed analytic framework, we chose an astronomical event that occurred nationwide across the United States, i.e., the 2017 Great American Eclipse, as an example event and studied the human movement dynamics in response to this event. However, this analytic framework can easily be applied to other types of large-scale events such as hurricanes or earthquakes. Numéro de notice : A2021-275 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/SOCIETE NUMERIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2021.101605 date de publication en ligne : 05/02/2021 En ligne : https://doi.org/10.1016/j.compenvurbsys.2021.101605 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97358
in Computers, Environment and Urban Systems > vol 87 (May 2021) . - n° 101605[article]Articuler cognition spatiale et cognition environnementale pour saisir les représentations socio-cognitives de l'espace / Thierry Ramadier in Revue internationale de géomatique, vol 30 n° 1-2 (janvier - mars 2020)
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Titre : Articuler cognition spatiale et cognition environnementale pour saisir les représentations socio-cognitives de l'espace Type de document : Article/Communication Auteurs : Thierry Ramadier, Auteur Année de publication : 2021 Article en page(s) : pp 13 - 35 Note générale : bibliographie Langues : Français (fre) Descripteur : [Termes descripteurs IGN] cognition
[Termes descripteurs IGN] géographie sociale
[Termes descripteurs IGN] phénomène géographique
[Termes descripteurs IGN] représentation mentale spatialeNuméro de notice : A2020- Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.3166/rig.2020.00101 En ligne : http://dx.doi.org/10.3166/rig.2020.00101 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97514
in Revue internationale de géomatique > vol 30 n° 1-2 (janvier - mars 2020) . - pp 13 - 35[article]Réservation
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[article]
Titre : Des pixels et des peuples Type de document : Article/Communication Auteurs : Laurent Polidori, Auteur Année de publication : 2021 Article en page(s) : pp 15 - 15 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes descripteurs IGN] croissance urbaine
[Termes descripteurs IGN] détection de changement
[Termes descripteurs IGN] frontière
[Termes descripteurs IGN] image thermique
[Termes descripteurs IGN] indicateur démographique
[Termes descripteurs IGN] mode d'occupation du sol
[Termes descripteurs IGN] population rurale
[Termes descripteurs IGN] population urbaineRésumé : (Auteur) Instruments de mesure physique, les satellites sont parfois utilisés pour l'étude des sociétés. Numéro de notice : A2021-324 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article nature-HAL : ArtSansCL DOI : sans date de publication en ligne : 07/04/2021 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97482
in Géomètre > n° 2190 (avril 2021) . - pp 15 - 15[article]Geographical random forests: a spatial extension of the random forest algorithm to address spatial heterogeneity in remote sensing and population modelling / Stefanos Georganos in Geocarto international, vol 36 n° 2 ([01/02/2021])
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Titre : Geographical random forests: a spatial extension of the random forest algorithm to address spatial heterogeneity in remote sensing and population modelling Type de document : Article/Communication Auteurs : Stefanos Georganos, Auteur ; Tais Grippa, Auteur ; Assane Niang Gadiaga, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 121 -1 36 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes descripteurs IGN] apprentissage automatique
[Termes descripteurs IGN] autocorrélation spatiale
[Termes descripteurs IGN] classification par forêts aléatoires
[Termes descripteurs IGN] Dakar
[Termes descripteurs IGN] densité de population
[Termes descripteurs IGN] distribution spatiale
[Termes descripteurs IGN] hétérogénéité spatiale
[Termes descripteurs IGN] modèle dynamique
[Termes descripteurs IGN] population
[Termes descripteurs IGN] utilisation du solRésumé : (auteur) Machine learning algorithms such as Random Forest (RF) are being increasingly applied on traditionally geographical topics such as population estimation. Even though RF is a well performing and generalizable algorithm, the vast majority of its implementations is still ‘aspatial’ and may not address spatial heterogenous processes. At the same time, remote sensing (RS) data which are commonly used to model population can be highly spatially heterogeneous. From this scope, we present a novel geographical implementation of RF, named Geographical Random Forest (GRF) as both a predictive and exploratory tool to model population as a function of RS covariates. GRF is a disaggregation of RF into geographical space in the form of local sub-models. From the first empirical results, we conclude that GRF can be more predictive when an appropriate spatial scale is selected to model the data, with reduced residual autocorrelation and lower Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE) values. Finally, and of equal importance, GRF can be used as an effective exploratory tool to visualize the relationship between dependent and independent variables, highlighting interesting local variations and allowing for a better understanding of the processes that may be causing the observed spatial heterogeneity. Numéro de notice : A2021-080 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1595177 date de publication en ligne : 10/06/2019 En ligne : https://doi.org/10.1080/10106049.2019.1595177 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96822
in Geocarto international > vol 36 n° 2 [01/02/2021] . - pp 121 -1 36[article]Population dynamics and natural hazard risk management: conceptual and practical linkages for the case of Austrian policy making / Christoph Clar in Natural Hazards, Vol 105 n° 2 (January 2021)
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Titre : Population dynamics and natural hazard risk management: conceptual and practical linkages for the case of Austrian policy making Type de document : Article/Communication Auteurs : Christoph Clar, Auteur ; Lukas Löschner, Auteur ; Ralf Nordbeck, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 765 - 1796 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes descripteurs IGN] aide à la décision
[Termes descripteurs IGN] Autriche
[Termes descripteurs IGN] décroissance urbaine
[Termes descripteurs IGN] démographie
[Termes descripteurs IGN] enquête
[Termes descripteurs IGN] politique publique
[Termes descripteurs IGN] populationRésumé : (auteur) This contribution explores the conceptual and empirical linkages between population dynamics and natural hazard risk management (NHRM). Following a review of the international scholarly literature, we conduct a mixed-methods approach in Austria, combining an online survey among policy makers and other stakeholders with a thematic analysis of policy documents. The aim is to investigate the practical relevance of socio-demographic change in Austria’s NHRM. The study shows that many hazard-prone regions in Austria face population change, in particular demographic ageing and population decline. In addition, our findings from the online survey demonstrate the relevance of population dynamics in NHRM, especially with regard to hazard response and recovery. Nonetheless, policy formulation in NHRM overwhelmingly disregards demographic change as a relevant factor. Accordingly, the study underscores the importance of future-oriented risk management strategies to better account for ongoing and expected socio-demographic changes. Numéro de notice : A2021-202 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s11069-020-04376-z date de publication en ligne : 24/10/2020 En ligne : https://doi.org/10.1007/s11069-020-04376-z Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97162
in Natural Hazards > Vol 105 n° 2 (January 2021) . - pp 765 - 1796[article]Incorporating memory-based preferences and point-of-interest stickiness into recommendations in location-based social networks / Hang Zhang in ISPRS International journal of geo-information, vol 10 n° 1 (January 2021)
PermalinkLocal fuzzy geographically weighted clustering: a new method for geodemographic segmentation / George Grekousis in International journal of geographical information science IJGIS, vol 35 n° 1 (January 2021)
PermalinkUrban construction waste with VHR remote sensing using multi-feature analysis and a hierarchical segmentation method / Qiang Chen in Remote sensing, vol 13 n° 1 (January 2021)
PermalinkExploring the heterogeneity of human urban movements using geo-tagged tweets / Ding Ma in International journal of geographical information science IJGIS, vol 34 n° 12 (December 2020)
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PermalinkUsing multi-agent simulation to predict natural crossing points for pedestrians and choose locations for mid-block crosswalks / Egor Smirrnov in Geo-spatial Information Science, vol 23 n° 4 (December 2020)
PermalinkModalflow: cross-origin flow data visualization for urban mobility / Ignacio Pérez-Messina in Algorithms, vol 13 n° 11 (November 2020)
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PermalinkMonitoring population dynamics in the Pearl River Delta from 2000 to 2010 / Sisi Yu in Geocarto international, vol 35 n° 14 ([15/10/2020])
PermalinkUrban Wi-Fi fingerprinting along a public transport route / Guenther Retscher in Journal of applied geodesy, vol 14 n° 4 (October 2020)
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PermalinkSpectral–spatial–temporal MAP-based sub-pixel mapping for land-cover change detection / Da He in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)
PermalinkUber movement data: a proxy for average one-way commuting times by car / Yeran Sun in ISPRS International journal of geo-information, vol 9 n° 3 (March 2020)
PermalinkAssessing public transit performance using real-time data: spatiotemporal patterns of bus operation delays in Columbus, Ohio, USA / Yongha Park in International journal of geographical information science IJGIS, vol 34 n° 2 (February 2020)
PermalinkSimilarity measurement on human mobility data with spatially weighted structural similarity index (SpSSIM) / Chanwoo Jin in Transactions in GIS, Vol 24 n° 1 (February 2020)
PermalinkLa biodiversité à l’épreuve des choix d’aménagement : une approche par la modélisation appliquée à la Région Occitanie / Coralie Calvet in Sciences, eaux & territoires, n° 31 (janvier 2020)
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PermalinkSpatio-temporal mobility and Twitter: 3D visualisation of mobility flows / Joaquín Osorio Arjona in Journal of maps, vol 16 n° 1 ([02/01/2020])
PermalinkAnalyse spatio-temporelle des mobilités de randonneurs dans le PNR du Massif des Bauges / Colin Kerouanton (2020)
PermalinkPermalinkRevealing the Correlation between Population Density and the Spatial Distribution of Urban Public Service Facilities with Mobile Phone Data / Yi Shi in ISPRS International journal of geo-information, Vol 9 n° 1 (January 2020)
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PermalinkMeasuring differential access to facilities between population groups using spatial Lorenz curves and related indices / Gordon A. Cromley in Transactions in GIS, Vol 23 n° 6 (November 2019)
PermalinkPressures and threats to nature related to human activities in European urban and suburban forests / Ewa Referowska-Chodak in Forests, vol 10 n° 9 (September 2019)
PermalinkHigh‐resolution national land use scenarios under a shrinking population in Japan / Haruka Ohashi in Transactions in GIS, vol 23 n° 4 (August 2019)
PermalinkL’accessibilité ferroviaire à Paris des grandes aires urbaines françaises : approche par la time geography / Laurent Chapelon in Mappemonde [en ligne], n° 127 (juillet 2019)
PermalinkExploring the uncertainty of activity zone detection using digital footprints with multi-scaled DBSCAN / Xinyi Liu in International journal of geographical information science IJGIS, Vol 33 n° 5-6 (May - June 2019)
PermalinkUnderstanding demographic and socioeconomic biases of geotagged Twitter users at the county level / Jiang Juqin in Cartography and Geographic Information Science, vol 46 n° 3 (May 2019)
PermalinkA methodology with a distributed algorithm for large-scale trajectory distribution prediction / QiuLei Guo in International journal of geographical information science IJGIS, Vol 33 n° 3-4 (March - April 2019)
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PermalinkDigital preservation, social history, and the Quon Sang Lung Laundry building : a case study from Fort Macleod, Alberta, Canada / Peter Dawson in Applied geomatics, vol 10 n° 4 (December 2018)
PermalinkUsing Network Segments in the Visualization of Urban Isochrones / Jeff Allen in Cartographica, vol 53 n° 4 (winter 2018)
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PermalinkSpatial discontinuities, health and mobility - What do the Google's POIs and tweets tell us about Bangkok's (Thailand) structures and spatial dynamics? / Alexandre Cebeillac in Revue internationale de géomatique, vol 28 n° 4 (octobre - décembre 2018)
PermalinkFine-grained prediction of urban population using mobile phone location data / Jie Chen in International journal of geographical information science IJGIS, vol 32 n° 9-10 (September - October 2018)
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