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Detecting spatiotemporal traffic events using geosocial media data / Shishuo Xu in Computers, Environment and Urban Systems, vol 94 (June 2022)
[article]
Titre : Detecting spatiotemporal traffic events using geosocial media data Type de document : Article/Communication Auteurs : Shishuo Xu, Auteur ; Songnian Li, Auteur ; Wei Huang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 101797 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] analyse de groupement
[Termes IGN] base de données d'objets mobiles
[Termes IGN] base de données spatiotemporelles
[Termes IGN] détection d'événement
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] données spatiotemporelles
[Termes IGN] planification urbaine
[Termes IGN] sécurité routière
[Termes IGN] Toronto
[Termes IGN] trafic routier
[Termes IGN] TwitterRésumé : (auteur) Social media platforms enable efficient traffic event detection by allowing users to produce geo-tagged content (e.g., tweets) known as geosocial media data. Geosocial media data improve road safety by providing timely updates for traffic flow and traffic control. Recent studies on traffic event detection with geosocial media data have been focused around keyword-based query approaches, where the event content was inferred by predetermined categories, to retrieve relevant traffic events. Spatiotemporal features associated with traffic-related posts have not been fully investigated. In this study, we filtered irrelevant posts with association rules. A spatiotemporal clustering-based method was then used to retrieve traffic events from these filtered posts, where the content of detected events was automatically inferred with a set of representative terms. For comparison, a typical text classification-based method was also used by classifying the posts filtered from association rules into different categories. By validating the detection results with vehicle travel speed data, we demonstrate that the former outperforms the latter in terms of the number of correctly detected traffic events from one-year of Twitter data in Toronto, Canada. Our proposed approach helps organizations and governments to be aware of when and where traffic events occur by identifying event hotspots and peak periods, which improves both traffic management and urban planning. Numéro de notice : A2022-264 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2022.101797 Date de publication en ligne : 26/03/2022 En ligne : https://doi.org/10.1016/j.compenvurbsys.2022.101797 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100261
in Computers, Environment and Urban Systems > vol 94 (June 2022) . - n° 101797[article]A geospatial workflow for the assessment of public transit system performance using near real-time data / Anastassios Dardas in Transactions in GIS, vol 26 n° 4 (June 2022)
[article]
Titre : A geospatial workflow for the assessment of public transit system performance using near real-time data Type de document : Article/Communication Auteurs : Anastassios Dardas, Auteur ; Brent Hall, Auteur ; Jon Salter, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 1642 - 1664 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] ArcGIS
[Termes IGN] Calgary
[Termes IGN] collecte de données
[Termes IGN] données spatiotemporelles
[Termes IGN] itinéraire
[Termes IGN] planification urbaine
[Termes IGN] Python (langage de programmation)
[Termes IGN] stockage de données
[Termes IGN] temps réel
[Termes IGN] trafic routier
[Termes IGN] transport public
[Termes IGN] WebSIGRésumé : (auteur) This article presents the development of a Geographical Information Systems (GIS) workflow that harvests high-volume and high-frequency near real-time data from a public General Transit Feed Specification (GTFS) and calculates metrics for the assessment of on-time and route speed performance for a public transit system. The approach is applied to near real-time and static GTFS data collected over a 9-month period for the City of Calgary, Alberta, Canada. The workflow uses two Azure Virtual Machines (VMs), one to harvest the data and the other to process observations in parallel using Python and the ArcGIS API libraries. A Web GIS application is described that queries data from MongoDB to visualize the performance results in spatiotemporal form. The purpose of the workflow and Web GIS application is to provide actionable information to transit planners to improve public transportation systems. The data management and analysis workflow is transferable to similar GTFS data from other cities. Numéro de notice : A2022-531 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : sans Date de publication en ligne : 02/05/2022 En ligne : https://doi.org/10.1111/tgis.12942 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101078
in Transactions in GIS > vol 26 n° 4 (June 2022) . - pp 1642 - 1664[article]GIS and machine learning for analysing influencing factors of bushfires using 40-year spatio-temporal bushfire data / Wanqin He in ISPRS International journal of geo-information, vol 11 n° 6 (June 2022)
[article]
Titre : GIS and machine learning for analysing influencing factors of bushfires using 40-year spatio-temporal bushfire data Type de document : Article/Communication Auteurs : Wanqin He, Auteur ; Sara Shirowzhan, Auteur ; Christopher Pettit, Auteur Année de publication : 2022 Article en page(s) : n° 336 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] analyse diachronique
[Termes IGN] apprentissage automatique
[Termes IGN] brousse
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] coefficient de corrélation
[Termes IGN] données météorologiques
[Termes IGN] données spatiotemporelles
[Termes IGN] humidité du sol
[Termes IGN] incendie
[Termes IGN] indice de végétation
[Termes IGN] Nouvelle-Galles du Sud
[Termes IGN] prévention des risques
[Termes IGN] régression linéaire
[Termes IGN] Spark
[Termes IGN] système d'information géographique
[Termes IGN] température de l'airRésumé : (auteur) The causes of bushfires are extremely complex, and their scale of burning and probability of occurrence are influenced by the interaction of a variety of factors such as meteorological factors, topography, human activity and vegetation type. An in-depth understanding of the combined mechanisms of factors affecting the occurrence and spread of bushfires is needed to support the development of effective fire prevention plans and fire suppression measures and aid planning for geographic, ecological maintenance and urban emergency management. This study aimed to explore how bushfires, meteorological variability and other natural factors have interacted over the past 40 years in NSW Australia and how these influencing factors synergistically drive bushfires. The CSIRO’s Spark toolkit has been used to simulate bushfire burning spread over 24 h. The study uses NSW wildfire data from 1981–2020, combined with meteorological factors (temperature, precipitation, wind speed), vegetation data (NDVI data, vegetation type) and topography (slope, soil moisture) data to analyse the relationship between bushfires and influencing factors quantitatively. Machine learning-random forest regression was then used to determine the differences in the influence of bushfire factors on the incidence and burn scale of bushfires. Finally, the data on each influence factor was imported into Spark, and the results of the random forest model were used to set different influence weights in Spark to visualise the spread of bushfires burning over 24 h in four hotspot regions of bushfire in NSW. Wind speed, air temperature and soil moisture were found to have the most significant influence on the spread of bushfires, with the combined contribution of these three factors exceeding 60%, determining the spread of bushfires and the scale of burning. Precipitation and vegetation showed a greater influence on the annual frequency of bushfires. In addition, burn simulations show that wind direction influences the main direction of fire spread, whereas the shape of the flame front is mainly due to the influence of land classification. Besides, the simulation results from Spark could predict the temporal and spatial spread of fire, which is a potential decision aid for fireproofing agencies. The results of this study can inform how fire agencies can better understand fire occurrence mechanisms and use bushfire prediction and simulation techniques to support both their operational (short-term) and strategic (long-term) fire management responses and policies. Numéro de notice : A2022-481 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi11060336 Date de publication en ligne : 05/06/2022 En ligne : https://doi.org/10.3390/ijgi11060336 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100894
in ISPRS International journal of geo-information > vol 11 n° 6 (June 2022) . - n° 336[article]GIS-based assessment of long-term traffic accidents using spatiotemporal and empirical Bayes analysis in Turkey / Saffet Erdoğan in Applied geomatics, vol 14 n° 2 (June 2022)
[article]
Titre : GIS-based assessment of long-term traffic accidents using spatiotemporal and empirical Bayes analysis in Turkey Type de document : Article/Communication Auteurs : Saffet Erdoğan, Auteur ; Mehmet Ali Dereli, Auteur ; Halil İbrahim Şenol, Auteur Année de publication : 2022 Article en page(s) : pp 147 - 162 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] accident de la route
[Termes IGN] analyse de groupement
[Termes IGN] distribution spatiale
[Termes IGN] données spatiotemporelles
[Termes IGN] données statistiques
[Termes IGN] sécurité routière
[Termes IGN] système d'information géographique
[Termes IGN] théorème de Bayes
[Termes IGN] trafic routier
[Termes IGN] TurquieRésumé : (auteur) The number of traffic fatalities continues to rise steadily throughout the world. In 2016, it reached 1.35 million. The spatiotemporal analysis makes a big contribution when used with spatial and statistical analysis together in terms of the understanding of the change. This study focuses on spatiotemporal fluctuations in traffic accident hotspots to gain useful insights into traffic safety in Turkey in 2004–2017 period. For this purpose, 372,800 accident records are arranged on a GIS platform. The areas that lack traffic safety and require more attention were determined using spatial, temporal, and empirical Bayesian analysis. Although similar results were detected with spatiotemporal and empiric Bayes analysis, spatiotemporal analysis was used to understand where traffic accidents clustering, and how the trends of traffic accidents change whether are increasing or decreasing. As a result of the analysis, an increasing trend has been found in many locations in Turkey from 2004 to 2017. Numéro de notice : A2022-461 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s12518-022-00419-1 Date de publication en ligne : 02/02/2022 En ligne : https://doi.org/10.1007/s12518-022-00419-1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100788
in Applied geomatics > vol 14 n° 2 (June 2022) . - pp 147 - 162[article]Narrative cartography with knowledge graphs / Gengchen Mai in Journal of Geovisualization and Spatial Analysis, vol 6 n° 1 (June 2022)
[article]
Titre : Narrative cartography with knowledge graphs Type de document : Article/Communication Auteurs : Gengchen Mai, Auteur ; Weiming Huang, Auteur ; Ling Cai, Auteur ; et al., Auteur Année de publication : 2022 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] ArcGIS
[Termes IGN] cartographie ancienne
[Termes IGN] cartographie par internet
[Termes IGN] données spatiotemporelles
[Termes IGN] géovisualisation
[Termes IGN] modèle d'ontologie
[Termes IGN] ontologie
[Termes IGN] réseau sémantique
[Termes IGN] SPARQL
[Termes IGN] système d'information géographique
[Termes IGN] web sémantiqueRésumé : (auteur) Narrative cartography is a discipline which studies the interwoven nature of stories and maps. However, conventional geovisualization techniques of narratives often encounter several prominent challenges, including the data acquisition & integration challenge and the semantic challenge. To tackle these challenges, in this paper, we propose the idea of narrative cartography with knowledge graphs (KGs). Firstly, to tackle the data acquisition & integration challenge, we develop a set of KG-based GeoEnrichment toolboxes to allow users to search and retrieve relevant data from integrated cross-domain knowledge graphs for narrative mapping from within a GISystem. With the help of this tool, the retrieved data from KGs are directly materialized in a GIS format which is ready for spatial analysis and mapping. Two use cases — Magellan’s expedition and World War II — are presented to show the effectiveness of this approach. In the meantime, several limitations are identified from this approach, such as data incompleteness, semantic incompatibility, and the semantic challenge in geovisualization. For the later two limitations, we propose a modular ontology for narrative cartography, which formalizes both the map content (Map Content Module) and the geovisualization process (Cartography Module). We demonstrate that, by representing both the map content and the geovisualization process in KGs (an ontology), we can realize both data reusability and map reproducibility for narrative cartography. Numéro de notice : A2022-946 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s41651-021-00097-4 Date de publication en ligne : 02/02/2022 En ligne : https://doi.org/10.1007/s41651-021-00097-4 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99869
in Journal of Geovisualization and Spatial Analysis > vol 6 n° 1 (June 2022)[article]Impacts of spatiotemporal resolution and tiling on SLEUTH model calibration and forecasting for urban areas with unregulated growth patterns / Damilola Eyelade in International journal of geographical information science IJGIS, vol 36 n° 5 (May 2022)PermalinkUnmixing-based spatiotemporal image fusion accounting for complex land cover changes / Xiaolu Jiang in IEEE Transactions on geoscience and remote sensing, vol 60 n° 5 (May 2022)PermalinkIdentification and classification of routine locations using anonymized mobile communication data / Gonçalo Ferreira in ISPRS International journal of geo-information, vol 11 n° 4 (April 2022)PermalinkIdentifying locations for new bike-sharing stations in Glasgow: an analysis of spatial equity and demand factors / Jeneva Beairsto in Annals of GIS, vol 28 n° 2 (April 2022)PermalinkParcel-based summer maize mapping and phenology estimation combined using Sentinel-2 and time series Sentinel-1 data / Yanyan Wang in International journal of applied Earth observation and geoinformation, vol 108 (April 2022)PermalinkPotential of Bayesian formalism for the fusion and assimilation of sequential forestry data in time and space / Cheikh Mohamedou in Canadian Journal of Forest Research, Vol 52 n° 4 (April 2022)PermalinkAssessing 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)PermalinkCartographie et caractérisation des lieux d'intérêt de cervidés en milieu forestier / Laurence Jolivet in Cartes & Géomatique, n° 247-248 (mars-juin 2022)PermalinkNovel model for predicting individuals’ movements in dynamic regions of interest / Xiaoqi Shen in GIScience and remote sensing, vol 59 n° 1 (2022)PermalinkPossibilities for assessment and geovisualization of spatial and temporal water quality data using a webGIS application / Daniel Balla in ISPRS International journal of geo-information, vol 11 n° 2 (February 2022)Permalink