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Understanding 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)
[article]
Titre : Understanding and predicting the spatio-temporal spread of COVID-19 via integrating diffusive graph embedding and compartmental models Type de document : Article/Communication Auteurs : Tong Zhang, Auteur ; Jing Li, Auteur Année de publication : 2021 Article en page(s) : pp 3025 - 3047 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] apprentissage profond
[Termes IGN] Colorado (Etats-Unis)
[Termes IGN] données spatiotemporelles
[Termes IGN] épidémie
[Termes IGN] maladie virale
[Termes IGN] mobilité territoriale
[Termes IGN] modèle de simulation
[Termes IGN] modélisation spatio-temporelle
[Termes IGN] outil d'aide à la décision
[Termes IGN] quartier
[Termes IGN] réseau de transport
[Termes IGN] risque sanitaire
[Termes IGN] surveillance sanitaireRésumé : (Auteur) In order to find useful intervention strategies for the novel coronavirus (COVID-19), it is vital to understand how the disease spreads. In this study, we address the modeling of COVID-19 spread across space and time, which facilitates understanding of the pandemic. We propose a hybrid data-driven learning approach to capture the mobility-related spreading mechanism of infectious diseases, utilizing multi-sourced mobility and attributed data. This study develops a visual analytic approach that identifies and depicts the strength of the transmission pathways of COVID-19 between areal units by integrating data-driven deep learning and compartmental epidemic models, thereby engaging stakeholders (e.g., public health officials, managers from transportation agencies) to make informed intervention decisions and enable public messaging. A case study in the state of Colorado, USA was performed to demonstrate the applicability of the proposed transmission modeling approach in understanding the spatio-temporal spread of COVID-19 at the neighborhood level. Transmission path maps are presented and analyzed, demonstrating their utility in evaluating the effects of mitigation measures. In addition, integrated embeddings also support daily prediction of infected cases and role analysis of each area unit during the transmission of the virus. Numéro de notice : A2021-932 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12803 Date de publication en ligne : 16/07/2021 En ligne : https://doi.org/10.1111/tgis.12803 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99447
in Transactions in GIS > vol 25 n° 6 (December 2021) . - pp 3025 - 3047[article]Analyzing routes in Ottoman Greater Syria using historical GIS: The 1849 Saida map / Motti Zohar in Transactions in GIS, vol 25 n° 5 (October 2021)
[article]
Titre : Analyzing routes in Ottoman Greater Syria using historical GIS: The 1849 Saida map Type de document : Article/Communication Auteurs : Motti Zohar, Auteur ; Yuval Ben-Bassat, Auteur Année de publication : 2021 Article en page(s) : pp 2612 - 2640 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] archives
[Termes IGN] carte ancienne
[Termes IGN] dix-neuvième siècle
[Termes IGN] durée de trajet
[Termes IGN] histoire
[Termes IGN] itinéraire
[Termes IGN] Liban
[Termes IGN] réseau routier
[Termes IGN] Syrie
[Termes IGN] système d'information historiqueRésumé : (auteur) Ottoman cartographic materials are important sources of information on 19th and early 20th-century Greater Syria. However, large portions of this corpus have yet to be examined. This study explores a rare mid-19th-century Ottoman map of the Province of Saida preserved in the Ottoman Archive in Istanbul. It lists travel times between villages, towns, and administrative centers in Greater Syria under Ottoman rule, and shows the network of routes connecting these localities. Using an historical GIS approach, we evaluated the characteristics of the map and its cartographical accuracy and merits. The network of routes on the map is compared to route reconstructions based on least-cost-path principles. The discussion focuses on the historical context of the map and the ways in which it reflects the strength of Ottoman rule and familiarity with Greater Syria at the time. Numéro de notice : A2021-814 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1111/tgis.12788 Date de publication en ligne : 15/07/2021 En ligne : https://doi.org/10.1111/tgis.12788 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98890
in Transactions in GIS > vol 25 n° 5 (October 2021) . - pp 2612 - 2640[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)
[article]
Titre : Impact of travel time uncertainties on modeling of spatial accessibility: a comparison of street data sources Type de document : Article/Communication Auteurs : Yan Lin, Auteur ; Christopher Lippitt, Auteur ; Daniel Beene, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 471 - 490 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] accessibilité
[Termes IGN] analyse de sensibilité
[Termes IGN] ArcMap
[Termes IGN] données localisées des bénévoles
[Termes IGN] durée de trajet
[Termes IGN] Google Maps
[Termes IGN] incertitude des données
[Termes IGN] indexation spatiale
[Termes IGN] navigation automobile
[Termes IGN] Nouveau-Mexique (Etats-Unis)
[Termes IGN] OpenStreetMap
[Termes IGN] plan de déplacement urbain
[Termes IGN] réseau routier
[Termes IGN] système d'information géographique
[Termes IGN] transport publicRésumé : (auteur) GIS-based spatial access measures have been used extensively to monitor social equity and to help develop policy. However, inherent uncertainties in the road datasets used in spatial access estimates remain largely underreported. These uncertainties might result in unrecognized biases within visualization products and decision-making outcomes that strive to improve social equity based on seemingly egalitarian accessibility metrics. To better understand and address these uncertainties, we evaluated variations in travel impedance for car and bus transportation using proprietary, volunteer-information-based, and free (non-volunteer-information-based) street networks. We then interpreted the measured variations through the lens of street data uncertainty and its propagation in a common E2SFCA model of spatial accessibility. Results indicated that travel impedance disagreement propagates through the modeling process to effect agreement of spatial access index (SPAI) estimates among different street sources, with larger uncertainties observed for bus travel than car travel. Higher impedance coefficients (β), a model parameter, reduced the impact of street-source variations on estimates. Less urbanized regions were found to experience higher street-source variations when compared with the core-metropolitan area. We also demonstrated that a relative spatial access measure – the spatial access ratio (SPAR) – reduced uncertainties introduced by the choice of street datasets. Careful selection of reliable street sources and model parameters (e.g. higher β), as well as consideration of the potential for bias, particularly for less urbanized areas and areas reliant on public transportation, is warranted when leveraging SPAI to inform policy. When reliable/accurate road network data are not accessible or data quality information is not available, the SPAR is a suitable alternative or supplement to SPAI for visualization and analyses. Numéro de notice : A2021-712 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/15230406.2021.1960609 Date de publication en ligne : 01/09/2021 En ligne : https://doi.org/10.1080/15230406.2021.1960609 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98617
in Cartography and Geographic Information Science > vol 48 n° 6 (October 2021) . - pp 471 - 490[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 032-2021061 RAB Revue Centre de documentation En réserve L003 Disponible Spatial interpolation of mobile positioning data for population statistics / Anto Aasa in Journal of location-based services, vol 15 n° 4 ([01/10/2021])
[article]
Titre : Spatial interpolation of mobile positioning data for population statistics Type de document : Article/Communication Auteurs : Anto Aasa, Auteur ; Pilleriine Kamenjuk, Auteur ; Erki Saluveer, Auteur ; et al., Auteur Année de publication : 2021 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] analyse comparative
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] données démographiques
[Termes IGN] données GNSS
[Termes IGN] interpolation spatiale
[Termes IGN] mobilité humaine
[Termes IGN] traitement de données localiséesRésumé : (auteur) Mobile positioning is recognised to be one of the most promising new sources of data for the production of fast and cost-effective statistics regarding population and mobility. Considerable interest has been shown by government institutions in their search for a way to use mobile positioning data to produce official statistics, although to date there are only few examples of successful projects. Apart from data access and sampling, the main challenges relate to the spatial interpolation of mobile positioning data and extrapolation of recorded data to the level of the entire population. This area of work has to date received relatively little attention in the academic discussion. In the current study, we compare five different methods of spatial interpolation of mobile positioning data. The best methods of describing population distribution and size in comparison with Census data are the adaptive Morton grid and the Random forest model (R2 > 0.9), while the more widely used point-in-polygon and areal-weighted methods produce results that are far less satisfactory (R2 = 0.42; R2 = 0.35). Careful selection of spatial interpolation methods is therefore of the utmost importance for producing reliable population statistics from mobile positioning data. Numéro de notice : A2021-727 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/17489725.2021.1917710 Date de publication en ligne : 10/05/2021 En ligne : https://doi.org/10.1080/17489725.2021.1917710 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98658
in Journal of location-based services > vol 15 n° 4 [01/10/2021][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
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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)PermalinkImproving human mobility identification with trajectory augmentation / Fan Zhou in Geoinformatica, vol 25 n° 3 (July 2021)PermalinkMapping trajectories and flows: facilitating a human-centered approach to movement data analytics / Somayeh Dodge in Cartography and Geographic Information Science, vol 48 n° 4 (July 2021)PermalinkUsing information entropy and a multi-layer neural network with trajectory data to identify transportation modes / Qingying Yu in International journal of geographical information science IJGIS, vol 35 n° 7 (July 2021)PermalinkReconsidering movement and exposure: Towards a more dynamic health geography / Malcolm Campbell in Geography compass, vol 15 n° 6 (June 2021)PermalinkSimulating multi-exit evacuation using deep reinforcement learning / Dong Xu in Transactions in GIS, Vol 25 n° 3 (June 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)PermalinkWhat is the difference between augmented reality and 2D navigation electronic maps in pedestrian wayfinding? / Weihua Dong in Cartography and Geographic Information Science, vol 48 n° 3 (May 2021)PermalinkEvaluating the effectiveness of different cartographic design variants for influencing route choice / Stefan Fuest in Cartography and Geographic Information Science, vol 48 n° 2 (March 2021)Permalink