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Assessing COVID-induced changes in spatiotemporal structure of mobility in the United States in 2020: a multi-source analytical framework / Evgeny Noi in International journal of geographical information science IJGIS, vol 36 n° 3 (March 2022)
[article]
Titre : Assessing COVID-induced changes in spatiotemporal structure of mobility in the United States in 2020: a multi-source analytical framework Type de document : Article/Communication Auteurs : Evgeny Noi, Auteur ; Alexander Rudolph, Auteur ; Somayeh Dodge, Auteur Année de publication : 2022 Article en page(s) : pp 585 - 616 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse spatio-temporelle
[Termes IGN] autocorrélation spatiale
[Termes IGN] comportement
[Termes IGN] données multisources
[Termes IGN] données spatiotemporelles
[Termes IGN] épidémie
[Termes IGN] Etats-Unis
[Termes IGN] hétérogénéité spatiale
[Termes IGN] maladie virale
[Termes IGN] mobilité humaine
[Termes IGN] mobilité territorialeRésumé : (auteur) The COVID-19 pandemic resulted in profound changes in mobility patterns and altered travel behaviors locally and globally. As a result, movement metrics have widely been used by researchers and policy makers as indicators to study, model, and mitigate the impacts of the COVID-19 pandemic. However, the veracity and variability of these mobility metrics have not been studied. This paper provides a systematic review of mobility and social distancing metrics available to researchers during the pandemic in 2020 in the United States. Twenty-six indices across nine different sources are analyzed and assessed with respect to their spatial and temporal coverage as well as sample representativeness at the county-level. Finally global and local indicators of spatial association are computed to explore spatial and temporal heterogeneity in mobility patterns. The structure of underlying changes in mobility and social distancing is examined in different US counties and across different data sets. We argue that a single measure might not describe all aspects of mobility perfectly. Numéro de notice : A2022-207 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.2005796 Date de publication en ligne : 21/12/2021 En ligne : https://doi.org/10.1080/13658816.2021.2005796 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100023
in International journal of geographical information science IJGIS > vol 36 n° 3 (March 2022) . - pp 585 - 616[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2022031 SL Revue Centre de documentation Revues en salle Disponible Changing mobility patterns in the Netherlands during COVID-19 outbreak / Sander Van Der Drift in Journal of location-based services, vol 16 n° 1 (March 2022)
[article]
Titre : Changing mobility patterns in the Netherlands during COVID-19 outbreak Type de document : Article/Communication Auteurs : Sander Van Der Drift, Auteur ; Luc Wismans, Auteur ; Marie-José Olde-Kalter, Auteur Année de publication : 2022 Article en page(s) : pp 1 - 24 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] bicyclette
[Termes IGN] comportement
[Termes IGN] épidémie
[Termes IGN] estimation bayesienne
[Termes IGN] mobilité territoriale
[Termes IGN] Pays-Bas
[Termes IGN] téléphone intelligent
[Termes IGN] transport
[Termes IGN] transport public
[Termes IGN] travail à domicile
[Termes IGN] véhicule automobileRésumé : (auteur) The COVID-19 outbreak and associated measures taken had an enormous impact on society as well as a disruptive, but not necessarily negative, impact on mobility. The Ministry of Infrastructure and Water Management received the most recent insights from the Dutch Mobility Panel (DMP) on a weekly basis. These insights were used to monitor the travel behaviour and to analyse changes in the behaviour of different groups and usage of modes of transport during COVID-19. The analysis shows an enormous decrease in travel at the beginning of the implementation of the so-called ‘intelligent’ lockdown and gradual increase again towards comparable levels as before this ‘intelligent lockdown, although the distribution over time, motives and used modes has changed. It becomes clear that not everyone needs to travel during peak hours and commuter travel is also not the main reason for the increase in car usage. Furthermore, cycling has shown to be an alternative option for travellers and public transport is hardly used anymore. If it is possible to sustain the lower level of car usage and integrate public transport as an important alternative for travel again, the COVID-19 impact on mobility could have a substantial remaining positive impact on mobility. Numéro de notice : A2022-391 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/17489725.2021.1876259 Date de publication en ligne : 11/03/2021 En ligne : https://doi.org/10.1080/17489725.2021.1876259 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100682
in Journal of location-based services > vol 16 n° 1 (March 2022) . - pp 1 - 24[article]Early warning of COVID-19 hotspots using human mobility and web search query data / Takahiro Yabe in Computers, Environment and Urban Systems, vol 92 (March 2022)
[article]
Titre : Early warning of COVID-19 hotspots using human mobility and web search query data Type de document : Article/Communication Auteurs : Takahiro Yabe, Auteur ; Kota Tsubouchi, Auteur ; Yoshihide Sekimoto, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 101747 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] aide à la localisation
[Termes IGN] analyse de données
[Termes IGN] analyse de groupement
[Termes IGN] épidémie
[Termes IGN] exploration de données
[Termes IGN] maladie virale
[Termes IGN] mobilité urbaine
[Termes IGN] modèle de simulation
[Termes IGN] prévention des risques
[Termes IGN] requête spatiale
[Termes IGN] ressources web
[Termes IGN] surveillance sanitaire
[Termes IGN] Tokyo (Japon)Résumé : (auteur) COVID-19 has disrupted the global economy and well-being of people at an unprecedented scale and magnitude. To contain the disease, an effective early warning system that predicts the locations of outbreaks is of crucial importance. Studies have shown the effectiveness of using large-scale mobility data to monitor the impacts of non-pharmaceutical interventions (e.g., lockdowns) through population density analysis. However, predicting the locations of potential outbreak occurrence is difficult using mobility data alone. Meanwhile, web search queries have been shown to be good predictors of the disease spread. In this study, we utilize a unique dataset of human mobility trajectories (GPS traces) and web search queries with common user identifiers (> 450 K users), to predict COVID-19 hotspot locations beforehand. More specifically, web search query analysis is conducted to identify users with high risk of COVID-19 contraction, and social contact analysis was further performed on the mobility patterns of these users to quantify the risk of an outbreak. Our approach is empirically tested using data collected from users in Tokyo, Japan. We show that by integrating COVID-19 related web search query analytics with social contact networks, we are able to predict COVID-19 hotspot locations 1–2 weeks beforehand, compared to just using social contact indexes or web search data analysis. This study proposes a novel method that can be used in early warning systems for disease outbreak hotspots, which can assist government agencies to prepare effective strategies to prevent further disease spread. Human mobility data and web search query data linked with common IDs are used to predict COVID-19 outbreaks. High risk social contact index captures both the contact density and COVID-19 contraction risks of individuals. Real world data was collected from 200 K individual users in Tokyo during the COVID-19 pandemic. Experiments showed that the index can be used for microscopic outbreak early warning. Numéro de notice : A2022-114 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2021.101747 Date de publication en ligne : 17/12/2021 En ligne : https://doi.org/10.1016/j.compenvurbsys.2021.101747 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99637
in Computers, Environment and Urban Systems > vol 92 (March 2022) . - n° 101747[article]Measuring and mapping long-term changes in migration flows using population-scale family tree data / Caglar Koylu in Cartography and Geographic Information Science, vol 49 n° 2 (March 2022)
[article]
Titre : Measuring and mapping long-term changes in migration flows using population-scale family tree data Type de document : Article/Communication Auteurs : Caglar Koylu, Auteur ; Alice Kasakoff, Auteur Année de publication : 2022 Article en page(s) : pp 154 - 170 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique
[Termes IGN] analyse diachronique
[Termes IGN] cartographie des flux
[Termes IGN] données localisées des bénévoles
[Termes IGN] Etats-Unis
[Termes IGN] généalogie
[Termes IGN] histoire
[Termes IGN] migration humaine
[Termes IGN] origine - destination
[Termes IGN] représentation du changementRésumé : (auteur) Studying migration over a long period is challenging due to lack of data, uneven data quality, and the methodological challenges that arise when analyzing migration over large geographic areas and long time spans with constantly changing political boundaries. Crowd-sourced family tree data are an untapped source of volunteered geographic information generated by millions of users. These trees contain information on individuals such as birth and death places and years, and kinship ties, and have the potential to support analysis of population dynamics and migration over many generations and far into the past. In this article, we introduce a methodology to measure and map long-term changes in migration flows using a population-scale family-tree data set. Our methodology includes many steps such as extracting migration events, temporal periodization, gravity normalization, and producing time-series flow maps. We study internal migration in the continental United States between 1789 and 1924 using birthplaces and birthyears of children from a cleaned, geocoded, and connected set of family trees from Rootsweb.com. To the best of our knowledge, the results are the first migration flow maps that show how the internal migration flows within the U.S. changed over such a long period of time (i.e. 135 years). Numéro de notice : A2022-138 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/15230406.2021.2011419 Date de publication en ligne : 19/01/2022 En ligne : https://doi.org/10.1080/15230406.2021.2011419 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99759
in Cartography and Geographic Information Science > vol 49 n° 2 (March 2022) . - pp 154 - 170[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 032-2022021 RAB Revue Centre de documentation En réserve L003 Disponible Modular multi-dimensional tool for emergency evacuation including location-based social network data / Ilil Blum Shem-Tov in Journal of location-based services, vol 16 n° 1 (March 2022)
[article]
Titre : Modular multi-dimensional tool for emergency evacuation including location-based social network data Type de document : Article/Communication Auteurs : Ilil Blum Shem-Tov, Auteur ; Shlomo Bekhor, Auteur Année de publication : 2022 Article en page(s) : pp 54 - 75 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] distribution spatiale
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] données localisées des bénévoles
[Termes IGN] origine - destination
[Termes IGN] réseau social géodépendant
[Termes IGN] secours d'urgence
[Termes IGN] téléphone intelligentRésumé : (auteur) This paper presents the concept of a modular multi-dimensional tool (MMDT) for evacuation planning models. The goal of MMDT is to propose alternative route and destination locations that can be evaluated and compared to one another. The proposed tool can represent a very large number of scenarios and its strength is in its modularity and efficiency. The MMDT can be applied using both conventional evacuation models and decentralised personalised evacuation models based on Location-Based Social Networks (LBSN) to reduce overall evacuation times. Large-scale test cases using anonymous LBSN data illustrate the MMDT on several scenarios. Results indicate a significant reduction in evacuation times when using decentralised personal evacuation. Numéro de notice : A2022-389 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/17489725.2021.1990422 Date de publication en ligne : 16/11/2021 En ligne : https://doi.org/10.1080/17489725.2021.1990422 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100679
in Journal of location-based services > vol 16 n° 1 (March 2022) . - pp 54 - 75[article]Understanding the movement predictability of international travelers using a nationwide mobile phone dataset collected in South Korea / Yang Xu in Computers, Environment and Urban Systems, vol 92 (March 2022)PermalinkNovel model for predicting individuals’ movements in dynamic regions of interest / Xiaoqi Shen in GIScience and remote sensing, vol 59 n° 1 (2022)PermalinkRecurrent origin–destination network for exploration of human periodic collective dynamics / Xiaojian Chen in Transactions in GIS, vol 26 n° 1 (February 2022)PermalinkSNN_flow: a shared nearest-neighbor-based clustering method for inhomogeneous origin-destination flows / Qiliang Liu in International journal of geographical information science IJGIS, vol 36 n° 2 (February 2022)PermalinkApport de l’intelligence artificielle au domaine des villes intelligentes : application à l’assistance des déplacements des personnes à mobilité réduite / Nathan Aky (2022)PermalinkAttributing pedestrian networks with semantic information based on multi-source spatial data / Xue Yang in International journal of geographical information science IJGIS, vol 36 n° 1 (January 2022)PermalinkContextual location recommendation for location-based social networks by learning user intentions and contextual triggers / Seyyed Mohammadreza Rahimi in Geoinformatica, vol 26 n° 1 (January 2022)PermalinkCréation d’un indicateur de qualité de la desserte des transports pour des parcelles à une échelle locale / Nick Lin (2022)PermalinkExplorer les processus de mobilité passée : raisonnement ontologique fondé sur la connaissance des pratiques socioculturelles et des vestiges archéologiques / Laure Nuninger in Revue internationale de géomatique, vol 31 n° 1-2 (janvier - juin 2022)PermalinkA hierarchical model for semantic trajectories and event extraction in indoor and outdoor spaces / Hassan Noureddine (2022)PermalinkPedestrian trajectory prediction with convolutional neural networks / Simone Zamboni in Pattern recognition, vol 121 (January 2022)PermalinkRoad traffic crashes and emergency response optimization: a geo-spatial analysis using closest facility and location-allocation methods / Sulaiman Yunus in Geomatics, Natural Hazards and Risk, vol 13 (2022)PermalinkSpécification et qualité du réseau cyclable, application à la recherche d’itinéraires / Raphaël Bres (2022)PermalinkConnecting family trees to construct a population-scale and longitudinal geo-social network for the U.S. / Caglar Koylu in International journal of geographical information science IJGIS, vol 35 n° 12 (December 2021)PermalinkA semantics-based trajectory segmentation simplification method / Minshi Liu in Journal of Geovisualization and Spatial Analysis, vol 5 n° 2 (December 2021)PermalinkUnderstanding and predicting the spatio-temporal spread of COVID-19 via integrating diffusive graph embedding and compartmental models / Tong Zhang in Transactions in GIS, vol 25 n° 6 (December 2021)PermalinkAnalyzing routes in Ottoman Greater Syria using historical GIS: The 1849 Saida map / Motti Zohar in Transactions in GIS, vol 25 n° 5 (October 2021)PermalinkImpact 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)PermalinkSpatial interpolation of mobile positioning data for population statistics / Anto Aasa in Journal of location-based services, vol 15 n° 4 ([01/10/2021])PermalinkUnderstanding 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)Permalink