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A multi-factor spatial optimization approach for emergency medical facilities in Beijing / Liang Zhou in ISPRS International journal of geo-information, vol 9 n° 6 (June 2020)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 6 (June 2020) . - 15 p. Titre : A multi-factor spatial optimization approach for emergency medical facilities in Beijing Type de document : Article/Communication Auteurs : Liang Zhou, Auteur ; Shaohua Wang, Auteur ; Zhibang Xu, Auteur Année de publication : 2020 Article en page(s) : 15 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] accessibilité [Termes descripteurs IGN] allocation [Termes descripteurs IGN] implantation (topographie) [Termes descripteurs IGN] mégalopole [Termes descripteurs IGN] modélisation spatio-temporelle [Termes descripteurs IGN] Pékin (Chine) [Termes descripteurs IGN] réseau routier [Termes descripteurs IGN] secours d'urgence [Termes descripteurs IGN] trafic routier [Termes descripteurs IGN] vitesse de déplacement Résumé : (auteur) The outcomes for emergency medical services (EMS) are highly dependent on space-time accessibility. Prior research describes the location of EMS needs with low accuracy and has not integrated a temporal analysis of the road network, which accounts for varying mobility in a dynamic transportation network. In this study, we formulated a network-based location-allocation model (NLAM) and analyzed the spatial characteristics of emergency medical facilities within the fifth ring road in Beijing by considering time, traffic, and population characteristics. The conclusions are as follows: (1) The high demand area for EMS is concentrated in the areas in middle, north, and east during the daytime (8:00–20:00) and in the middle and north during the nighttime (20:00–8:00). From day to night, the centroid of the potential demand distribution shifts in the Western and Southern areas. (2) The road traffic data is sampled 20 times throughout the week, and variations in the average driving speed affect a higher mean driving speed on the weekend. This primarily impacts the main roads, due to these roads experiencing the greatest fluctuation in speed throughout the week of any roadway in the study area. (3) Finally, the 15-min coverage of emergency medical facilities are sampled 20 times in one week and analyzed. Fortunately, there is 100% coverage at night; however, due to traffic congestion, there were a few blind coverage areas in the daytime. The blind area is prevalent in Shijingshan South Station and the Jingxian Bridge in the South fifth ring. Numéro de notice : A2020-313 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9060361 date de publication en ligne : 01/06/2020 En ligne : https://doi.org/10.3390/ijgi9060361 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95167 [article]

A random set approach for modeling integrated uncertainties of traffic islands derived from airborne laser scanning points / Liang Zhou in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 9 (September 2013)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 79 n° 9 (September 2013) . - pp 835 - 845 Titre : A random set approach for modeling integrated uncertainties of traffic islands derived from airborne laser scanning points Type de document : Article/Communication Auteurs : Liang Zhou, Auteur ; Alfred Stein, Auteur Année de publication : 2013 Article en page(s) : pp 835 - 845 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] incertitude des données [Termes descripteurs IGN] modèle d'incertitude [Termes descripteurs IGN] qualité des données [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] trafic routier Résumé : (Auteur) Traffic islands play a major role in transport studies by affecting traffic behavior safety, air pollution, and transport decision support. Point data obtained by laser scanning enable the determination of their locations. Planimetric errors, vertical errors, and limited point spacing however affect their spatial data quality (SDQ). In this study, we defined uncertainty as the lack of accuracy and analyzed its importance by modeling each traffic island as a random set. The covering functions of the point data and their intermediate locations were determined by point segmentation, followed by interpolation. In this way, traffic islands were delineated from the background with a transition zone. The study showed that point spacing has the largest contribution to the positonal accuracy of a traffic island. The area of the transition zone has a linear relation with the planimetric errors, whereas the influence of the vertical errors on the accuracy decreases with increasing point spacing. Experiments were conducted to investigate the influences of the parameters in an SDQ analysis. The study demonstrated how different sources of uncertainty can be integrated. Results showed the advantages of using random sets for SDQ modelling. We concluded that modelling of traffic islands by random sets provides meaningful information to integrate uncertainties. Numéro de notice : A2013-506 Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.79.9.835 En ligne : https://doi.org/10.14358/PERS.79.9.835 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32644 [article]

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