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Landscape metrics regularly outperform other traditionally-used ancillary datasets in dasymetric mapping of population / Heng Wan in Computers, Environment and Urban Systems, vol 99 (January 2023)  

Public [article]  inComputers, Environment and Urban Systems > vol 99 (January 2023) . - n° 101899 Titre : Landscape metrics regularly outperform other traditionally-used ancillary datasets in dasymetric mapping of population Type de document : Article/Communication Auteurs : Heng Wan, Auteur ; Jim Yoon, Auteur ; Vivek Srikrishnan, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 101899 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] carte thématique [Termes IGN] densité de population [Termes IGN] distribution spatiale [Termes IGN] Etats-Unis [Termes IGN] indicateur paysager [Termes IGN] interpolation [Termes IGN] occupation du sol [Termes IGN] paysage [Termes IGN] planification urbaine [Termes IGN] réduction d'échelle Résumé : (auteur) Population downscaling and interpolation methods are required to produce data which correspond to spatial units used in urban planning, demography, and environmental modeling. Population data are typically aggregated at census enumeration units, which can have arbitrary, temporally-evolving boundaries. Previous approaches to imperviousness-based dasymetric mapping ignore cell-level patterning of imperviousness within a spatial unit of prediction, which potentially serve as a strong indicator of population. Landscape metrics derived from imperviousness data offer a promising approach to capture these patterns. In this study, we incorporate landscape metrics derived from impervious cover percentage maps into intelligent dasymetric mapping to downscale population from census tracts to block groups in four states with varying population densities: Connecticut, South Carolina, West Virginia, and New Mexico. We compare the performance of the landscape metrics-based models against two baseline models in all four states across three different time periods. The results show that intelligent dasymetric mapping using landscape metrics generally outperforms the two baseline models. We further compare the performance of landscape metrics as an ancillary source of information for dasymetric mapping against other traditionally-used datasets (e.g., land use, roads, nighttime lights data) in three states (Connecticut, South Carolina, and New Mexico) in 2000. We find that class area, landscape shape index, and number of patches consistently achieve lower error rates than other ancillary datasets in all the three states. Numéro de notice : A2023-013 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2022.101899 Date de publication en ligne : 02/11/2022 En ligne : https://doi.org/10.1016/j.compenvurbsys.2022.101899 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102130 [article]

From data to narratives: Scrutinising the spatial dimensions of social and cultural phenomena through lenses of interactive web mapping / Tian Lan in Journal of Geovisualization and Spatial Analysis, vol 6 n° 2 (December 2022)  

Public [article]  inJournal of Geovisualization and Spatial Analysis > vol 6 n° 2 (December 2022) . - n° 22 Titre : From data to narratives: Scrutinising the spatial dimensions of social and cultural phenomena through lenses of interactive web mapping Type de document : Article/Communication Auteurs : Tian Lan, Auteur ; Oliver O'Brien, Auteur ; James Cheshire, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 22 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] carte interactive [Termes IGN] cartographie sensible [Termes IGN] culture [Termes IGN] données démographiques [Termes IGN] données socio-économiques [Termes IGN] impact social [Termes IGN] récit [Termes IGN] Royaume-Uni [Termes IGN] sciences sociales [Termes IGN] web mapping Mots-clés libres : narrative mapping Résumé : (auteur) Modern web mapping techniques have enhanced the storytelling capability of cartography. In this paper, we present our recent development of a web mapping facility that can be used to extract interesting stories and unique insights from a diverse range of socio-economic and demographic variables and indicators, derived from a variety of datasets. We then use three curated narratives to show that online maps are effective ways of interactive storytelling and visualisation, which allow users to tailor their own story maps. We discuss the reasons for the revival of the recent attention to narrative mapping and conclude that our interactive web mapping facility powered by data assets can be employed as an accessible and powerful toolkit, to identify geographic patterns of various social and economic phenomena by social scientists, journalists, policymakers, and the public. Numéro de notice : A2022-541 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s41651-022-00117-x Date de publication en ligne : 16/06/2022 En ligne : https://doi.org/10.1007/s41651-022-00117-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101105 [article]

Human mobility and COVID-19 transmission: a systematic review and future directions / Mengxi Zhang in Annals of GIS, vol 28 n° 4 (November 2022)  

Public [article]  inAnnals of GIS > vol 28 n° 4 (November 2022) . - pp 501 - 514 Titre : Human mobility and COVID-19 transmission: a systematic review and future directions Type de document : Article/Communication Auteurs : Mengxi Zhang, Auteur ; Siqin Wang, Auteur ; Tao Hu, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 501 - 514 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] corrélation automatique de points homologues [Termes IGN] données spatiotemporelles [Termes IGN] épidémie [Termes IGN] hétérogénéité spatiale [Termes IGN] littérature [Termes IGN] maladie virale [Termes IGN] mobilité territoriale [Termes IGN] modèle dynamique [Termes IGN] modélisation spatio-temporelle [Termes IGN] régression linéaire Résumé : (auteur) Without a widely distributed vaccine, controlling human mobility has been identified and promoted as the primary strategy to mitigate the transmission of COVID-19. Many studies have reported the relationship between human mobility and COVID-19 transmission by utilizing the spatial-temporal information of mobility data from various sources. To better understand the role of human mobility in the pandemic, we conducted a systematic review of articles that measure the relationship between human mobility and COVID-19 in terms of their data sources, mathematical models, and key findings. Following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, we selected 47 articles from the Web of Science Core Collection up to September 2020. Restricting human mobility reduced the transmission of COVID-19, although the effectiveness and stringency of policy implementation vary temporally and spatially across different stages of the pandemic. We call for prompt and sustainable measures to control the pandemic. We also recommend researchers 1) to enhance multi-disciplinary collaboration; 2) to adjust the implementation and stringency of mobility-control policies in corresponding to the rapid change of the pandemic; 3) to improve mathematical models used in analysing, simulating, and predicting the transmission of the disease; and 4) to enrich the source of mobility data to ensure data accuracy and suability. Numéro de notice : A2022-863 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/19475683.2022.2041725 Date de publication en ligne : 03/03/2022 En ligne : https://doi.org/10.1080/19475683.2022.2041725 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102153 [article]

An analysis of twitter as a relevant human mobility proxy / Fernando Terroso-Saenz in Geoinformatica [en ligne], vol 26 n° 4 (October 2022)  

Public [article]  inGeoinformatica [en ligne] > vol 26 n° 4 (October 2022) . - pp 677 - 706 Titre : An analysis of twitter as a relevant human mobility proxy Type de document : Article/Communication Auteurs : Fernando Terroso-Saenz, Auteur ; Andres Muñoz, Auteur ; Francisco Arcas, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 677 - 706 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] données issues des réseaux sociaux [Termes IGN] données spatiotemporelles [Termes IGN] épidémie [Termes IGN] Espagne [Termes IGN] géobalise [Termes IGN] maladie virale [Termes IGN] mobilité territoriale [Termes IGN] Twitter Résumé : (auteur) During the last years, the analysis of spatio-temporal data extracted from Online Social Networks (OSNs) has become a prominent course of action within the human-mobility mining discipline. Due to the noisy and sparse nature of these data, an important effort has been done on validating these platforms as suitable mobility proxies. However, such a validation has been usually based on the computation of certain features from the raw spatio-temporal trajectories extracted from OSN documents. Hence, there is a scarcity of validation studies that evaluate whether geo-tagged OSN data are able to measure the evolution of the mobility in a region at multiple spatial scales. For that reason, this work proposes a comprehensive comparison of a nation-scale Twitter (TWT) dataset and an official mobility survey from the Spanish National Institute of Statistics. The target time period covers a three-month interval during which Spain was heavily affected by the COVID-19 pandemic. Both feeds have been compared in this context by considering different mobility-related features and spatial scales. The results show that TWT could capture only a limited number features of the latent mobility behaviour of Spain during the study period. Numéro de notice : A2022-866 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-021-00460-z Date de publication en ligne : 15/02/2022 En ligne : https://doi.org/10.1007/s10707-021-00460-z Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102159 [article]

Predicting the variability in pedestrian travel rates and times using crowdsourced GPS data / Michael J. Campbell in Computers, Environment and Urban Systems, vol 97 (October 2022)  

Public [article]  inComputers, Environment and Urban Systems > vol 97 (October 2022) . - n° 101866 Titre : Predicting the variability in pedestrian travel rates and times using crowdsourced GPS data Type de document : Article/Communication Auteurs : Michael J. Campbell, Auteur ; Philip E. Dennison, Auteur ; Matthew Thompson, Auteur Année de publication : 2022 Article en page(s) : n° 101866 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] base de données localisées [Termes IGN] Californie (Etats-Unis) [Termes IGN] chemin le moins coûteux, algorithme du [Termes IGN] données issues des réseaux sociaux [Termes IGN] durée de trajet [Termes IGN] mobilité urbaine [Termes IGN] navigation pédestre [Termes IGN] pente [Termes IGN] planification urbaine [Termes IGN] trace GPS [Termes IGN] Utah (Etas-Unis) Résumé : (auteur) Accurately predicting pedestrian travel times is critically valuable in emergency response, wildland firefighting, disaster management, law enforcement, and urban planning. However, the relationship between pedestrian movement and landscape conditions is highly variable between individuals, making it difficult to estimate how long it will take broad populations to get from one location to another on foot. Although functions exist for predicting travel rates, they typically oversimplify the inherent variability of pedestrian travel by assuming the effects of landscapes on movement are universal. In this study, we present an approach for predicting the variability in pedestrian travel rates and times using a large, crowdsourced database of GPS tracks. Acquired from the outdoor recreation website AllTrails, these tracks represent nearly 2000 hikes on a diverse range of trails in Utah and California, USA. We model travel rates as a function of the slope of the terrain by generating a series of non-linear percentile models from the 2.5 th to the 97.5 th by 2.5 percentiles. The 50 th percentile model, representing the hiking speed of the typical individual, demonstrates marked improvement over existing slope-travel rate functions when compared to an independent test dataset. Our results demonstrate novel capacity to estimate travel time variability, with modeled percentiles being able to predict actual percentiles with less than 10% error. Travel rate functions can also be applied to least cost path analysis to provide variability in travel times. Numéro de notice : A2022-599 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.compenvurbsys.2022.101866 Date de publication en ligne : 20/08/2022 En ligne : https://doi.org/10.1016/j.compenvurbsys.2022.101866 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101452 [article]

Identification of urban sectors prone to solid waste accumulation: A machine learning approach based on social indicators / Luis Izquierdo-Horna in Computers, Environment and Urban Systems, vol 96 (September 2022)  

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Measuring COVID-19 vulnerability for Northeast Brazilian municipalities: Social, economic, and demographic factors based on multiple criteria and spatial analysis / Ciro José Jardim De Figueiredo in ISPRS International journal of geo-information, vol 11 n° 8 (August 2022)  

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Use of GIS and dasymetric mapping for estimating tsunami-affected population to facilitate humanitarian relief logistics: a case study from Phuket, Thailand / Kiatkulchai Jitt-Aer in Natural Hazards, vol 113 n° 1 (August 2022)  

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Can machine learning improve small area population forecasts? A forecast combination approach / Irina Grossman in Computers, Environment and Urban Systems, vol 95 (July 2022)  

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Interactive visual analytics of moving passenger flocks using massive smart card data / Tong Zhang in Cartography and Geographic Information Science, Vol 49 n° 4 (July 2022)  

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Coupling graph deep learning and spatial-temporal influence of built environment for short-term bus travel demand prediction / Tianhong Zhao in Computers, Environment and Urban Systems, vol 94 (June 2022)  

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Mapping monthly population distribution and variation at 1-km resolution across China / Zhifeng Cheng in International journal of geographical information science IJGIS, vol 36 n° 6 (June 2022)  

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The effect of intra-urban mobility flows on the spatial heterogeneity of social media activity: investigating the response to rainfall events / Sidgley Camargo de Andrade in International journal of geographical information science IJGIS, vol 36 n° 6 (June 2022)  

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Discovering co-location patterns in multivariate spatial flow data / Jiannan Cai in International journal of geographical information science IJGIS, vol 36 n° 4 (April 2022)  

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Human movement patterns of different racial-ethnic and economic groups in U.S. top 50 populated cities: What can social media tell us about isolation? / Meiliu Wu in Annals of GIS, vol 28 n° 2 (April 2022)  

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