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Analysis of the spatial range of service and accessibility of hospitals designated for coronavirus disease 2019 in Yunnan Province, China / Liangting Zheng in Geocarto international, vol 37 n° 22 ([10/10/2022])
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Titre : Analysis of the spatial range of service and accessibility of hospitals designated for coronavirus disease 2019 in Yunnan Province, China Type de document : Article/Communication Auteurs : Liangting Zheng, Auteur ; Jia Li, Auteur ; Wenying Hu, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 6519 - 6537 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] accessibilité
[Termes IGN] diagramme de Voronoï
[Termes IGN] données médicales
[Termes IGN] données routières
[Termes IGN] épidémie
[Termes IGN] interpolation inversement proportionnelle à la distance
[Termes IGN] interpolation par pondération de zones
[Termes IGN] maladie virale
[Termes IGN] médecine humaine
[Termes IGN] secours d'urgence
[Termes IGN] Yunnan (Chine)Résumé : (auteur) COVID-19 poses a major threat to global health care systems, and the recent surge in mortality rates confirms the importance of timely access to care. The capacity of medical service providers is reflected both in the spatial accessibility of medical institutions and in the spatial scope of their services. Therefore, this study aims to investigate the spatial scope of services and spatial accessibility of COVID-19-designated hospitals in Yunnan Province, China. Data are collected from multiple sources and included COVID-19 case data, road data, and data from designated hospitals for COVID-19 in Yunnan Province. The optimal spatial service range for designated hospitals is delineated using a weighted Voronoi diagram that takes into account the number of medical staff and the number of beds in the hospital. Traffic accessibility coefficients are introduced to analyze the spatial accessibility of COVID-19-designated hospitals, and the spatial accessibility of each designated hospital is visualized using the inverse distance weighting interpolation algorithm. The results show the following: (1) COVID-19 cases in Yunnan Province are concentrated in the central and northern regions. The largest single cells in the weighted Voronoi diagram are mainly Pu'er (59168 km2), Honghe (35569 km2), and Baoshan (46795 km2), and the time cost of attainting medical treatment is greater for residents in marginal areas. (2) Within the service space of designated hospitals, 90.24% of patients could obtain medical assistance within 2 h. Those in 52 (36.36%) counties within a municipal jurisdiction could obtain medical services within 2 h, and 76.47% of counties have above-average spatial accessibility. (3) Medical resources in Yunnan Province should be shifted toward the high-risk east-central region and the less spatially accessible in southern and western regions. Numéro de notice : A2022-728 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2021.1943008 Date de publication en ligne : 09/07/2021 En ligne : https://doi.org/10.1080/10106049.2021.1943008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101674
in Geocarto international > vol 37 n° 22 [10/10/2022] . - pp 6519 - 6537[article]Using mobile laser scanning data for automated extraction of road markings / Haiyan Guan in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)
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Titre : Using mobile laser scanning data for automated extraction of road markings Type de document : Article/Communication Auteurs : Haiyan Guan, Auteur ; Jonathan Li, Auteur ; Yongtao Yu, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 93 - 107 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] densité des points
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] extraction automatique
[Termes IGN] interpolation inversement proportionnelle à la distance
[Termes IGN] morphologie mathématique
[Termes IGN] semis de points
[Termes IGN] seuillage de points
[Termes IGN] signalisation routièreRésumé : (Auteur) A mobile laser scanning (MLS) system allows direct collection of accurate 3D point information in unprecedented detail at highway speeds and at less than traditional survey costs, which serves the fast growing demands of transportation-related road surveying including road surface geometry and road environment. As one type of road feature in traffic management systems, road markings on paved roadways have important functions in providing guidance and information to drivers and pedestrians. This paper presents a stepwise procedure to recognize road markings from MLS point clouds. To improve computational efficiency, we first propose a curb-based method for road surface extraction. This method first partitions the raw MLS data into a set of profiles according to vehicle trajectory data, and then extracts small height jumps caused by curbs in the profiles via slope and elevation-difference thresholds. Next, points belonging to the extracted road surface are interpolated into a geo-referenced intensity image using an extended inverse-distance-weighted (IDW) approach. Finally, we dynamically segment the geo-referenced intensity image into road-marking candidates with multiple thresholds that correspond to different ranges determined by point-density appropriate normality. A morphological closing operation with a linear structuring element is finally used to refine the road-marking candidates by removing noise and improving completeness. This road-marking extraction algorithm is comprehensively discussed in the analysis of parameter sensitivity and overall performance. An experimental study performed on a set of road markings with ground-truth shows that the proposed algorithm provides a promising solution to the road-marking extraction from MLS data. Numéro de notice : A2014-015 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.11.005 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.11.005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32920
in ISPRS Journal of photogrammetry and remote sensing > vol 87 (January 2014) . - pp 93 - 107[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-2014011 RAB Revue Centre de documentation En réserve L003 Disponible Predicting surface fuel models and fuel metrics using Lidar and CIR imagery in a dense, mountainous forest / Marek Jakubowksi in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 1 (January 2013)
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Titre : Predicting surface fuel models and fuel metrics using Lidar and CIR imagery in a dense, mountainous forest Type de document : Article/Communication Auteurs : Marek Jakubowksi, Auteur ; Quinhua Guo, Auteur ; Brandon Collins, Auteur ; Scott Stephens, Auteur ; Maggi Kelly, Auteur Année de publication : 2013 Article en page(s) : pp 37 - 49 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] biomasse (combustible)
[Termes IGN] Californie (Etats-Unis)
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt
[Termes IGN] image multibande
[Termes IGN] image optique
[Termes IGN] interpolation inversement proportionnelle à la distance
[Termes IGN] lutte contre l'incendie
[Termes IGN] montagne
[Termes IGN] PinophytaRésumé : (Auteur) We compared the ability of several classification and regression algorithms to predict forest stand structure metrics and standard surface fuel models. Our study area spans a dense, topographically complex Sierra Nevada mixed-conifer forest. We used clustering, regression trees, and support vector machine algorithms to analyze high density (average 9 pulses/m2), discrete return, small-footprint lidar data, along with multispectral imagery. Stand structure metric predictions generally decreased with increased canopy penetration. For example, from the top of canopy, we predicted canopy height (r2 ! 0.87), canopy cover (r2 ! 0.83), basal area (r2 ! 0.82), shrub cover (r2 ! 0.62), shrub height (r2 ! 0.59), combined fuel loads (r2 ! 0.48), and fuel bed depth (r2 ! 0.35). While the general fuel types were predicted accurately, specific surface fuel model predictions were poor (76 percent and "50 percent correct classification, respectively) using all algorithms. These fuel components are critical inputs for wildfire behavior modeling, which ultimately support forest management decisions. This comprehensive examination of the relative utility of lidar and optical imagery will be useful for forest science and management. Numéro de notice : A2013-004 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14358/PERS.79.1.37 En ligne : http://kellylab.berkeley.edu/storage/papers/2013-Jakubowski-etal-PERS.pdf Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32142
in Photogrammetric Engineering & Remote Sensing, PERS > vol 79 n° 1 (January 2013) . - pp 37 - 49[article]Street-level spatial interpolation using network-based IDW and ordinary kriging / N. Shiode in Transactions in GIS, vol 15 n° 4 (August 2011)
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Titre : Street-level spatial interpolation using network-based IDW and ordinary kriging Type de document : Article/Communication Auteurs : N. Shiode, Auteur ; S. Shiode, Auteur Année de publication : 2011 Article en page(s) : pp 457 - 477 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] interpolation inversement proportionnelle à la distance
[Termes IGN] interpolation spatiale
[Termes IGN] krigeage
[Termes IGN] lissage de données
[Termes IGN] réseau routierRésumé : (Auteur) This study proposes network-based spatial interpolation methods to help predict unknown spatial values along networks more accurately. It expands on two of the commonly used spatial interpolation methods, IDW (inverse distance weighting) and OK (ordinary kriging), and applies them to analyze spatial data observed on a network. The study first provides the methodological framework, and it then examines the validity of the proposed methods by cross-validating elevations from two contrasting patterns of street network and comparing the MSEs (Mean Squared Errors) of the predicted values measured with the two proposed network-based methods and their conventional counterparts. The study suggests that both network-based IDW and network-based OK are generally more accurate than their existing counterparts, with network-based OK constantly outperforming the other methods. The network-based methods also turn out to be more sensitive to the edge effect, and their performance improves after edge correction. Furthermore, the MSEs of standard OK and network-based OK improve as more sample locations are used, whereas those of standard IDW and network-based IDW remain stable regardless of the number of sample locations. The two network-based methods use a similar set of sample locations, and their performance is inherently affected by the difference in their weight distribution among sample locations. Numéro de notice : A2011-346 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/j.1467-9671.2011.01278.x Date de publication en ligne : 16/08/2011 En ligne : https://doi.org/10.1111/j.1467-9671.2011.01278.x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31125
in Transactions in GIS > vol 15 n° 4 (August 2011) . - pp 457 - 477[article]Exploring population spatial concentrations in Northern Ireland by community background and other characteristics: an application of geographically weighted spatial statistics / C.D. Lloyd in International journal of geographical information science IJGIS, vol 24 n°7-8 (july 2010)
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Titre : Exploring population spatial concentrations in Northern Ireland by community background and other characteristics: an application of geographically weighted spatial statistics Type de document : Article/Communication Auteurs : C.D. Lloyd, Auteur Année de publication : 2010 Article en page(s) : pp 1193 - 1221 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] autocorrélation spatiale
[Termes IGN] géostatistique
[Termes IGN] interpolation inversement proportionnelle à la distance
[Termes IGN] interpolation par pondération de zones
[Termes IGN] Irlande du nord
[Termes IGN] pondération
[Termes IGN] population
[Termes IGN] régression géographiquement pondérée
[Termes IGN] religion
[Termes IGN] urbanisationRésumé : (Auteur) Information on how populations are spatially concentrated by different characteristics is a key means of guiding government policies in a variety of contexts, in addition to being of substantial academic interest. In particular, to reduce inequalities between groups, it is necessary to understand the characteristics of these groups in terms of their composition and their geographical structure. This article explores the degree to which the population of Northern Ireland is spatially concentrated by a range of characteristics. There is a long history of interest in residential segregation by religion in Northern Ireland; this article assesses population concentration not only by community background ('religion or religion brought up in') but also by housing tenure, employment and other socioeconomic and demographic characteristics. The spatial structure of geographical variables can be captured by a range of spatial statistics including Moran's I. Such approaches utilise information on connections between observations or the distances between them. While such approaches are conceptually an improvement on standard aspatial statistics, a logical further step is to compute statistics on a local basis on the grounds that most real-world properties are not spatially homogenous and, therefore, global measures may mask much variation. In population geography, which provides the substantive focus for this article, there are still relatively few studies that assess in depth the application of geographically weighted statistics for exploring population characteristics individually and for exploring relations between variables. This article demonstrates the value of such approaches by using a variety of geographically weighted statistical measures to explore outputs from the 2001 Census of Population of Northern Ireland. A key objective is to assess the degree to which the population is spatially divided, as judged by the selected variables. In other words, do people cluster more strongly with others who share their community background or others who have a similar socioeconomic status in some respect? The analysis demonstrates how geographically weighted statistics can be used to explore the degree to which single socioeconomic and demographic variables and relations between such variables differ at different spatial scales and at different geographical locations. For example, the results show that there are regions comprising neighbouring areas with large proportions of people from the same community background, but with variable unemployment levels, while in other areas the first case holds true but unemployment levels are consistently low. The analysis supports the contention that geographical variations in population characteristics are the norm, and these cannot be captured without using local methods. An additional methodological contribution relates to the treatment of counts expressed as percentages. Numéro de notice : A2010-326 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658810903321321 En ligne : https://doi.org/10.1080/13658810903321321 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30520
in International journal of geographical information science IJGIS > vol 24 n°7-8 (july 2010) . - pp 1193 - 1221[article]Exemplaires(2)
Code-barres Cote Support Localisation Section Disponibilité 079-2010041 RAB Revue Centre de documentation En réserve L003 Disponible 079-2010042 RAB Revue Centre de documentation En réserve L003 Disponible Effects of topographic variability and Lidar sampling density on several DEM interpolation methods / Q. Guo in Photogrammetric Engineering & Remote Sensing, PERS, vol 76 n° 6 (June 2010)
PermalinkModelling vertical error in LiDAR-derived digital elevation models / F. Aguilar in ISPRS Journal of photogrammetry and remote sensing, vol 65 n° 1 (January - February 2010)
PermalinkFinding appropriate interpolation techniques for topographic surface generation for mudslide risk zonation / A. Vansarochana in Geocarto international, vol 24 n° 4 (August - September 2009)
PermalinkA theoretical approach to the use of cyberinfrastructure in geographical analysis / Shaowen Wang in International journal of geographical information science IJGIS, vol 23 n° 1-2 (january 2009)
PermalinkErrors within the inverse distance weighted (IDW) interpolation procedure / G. Achilleos in Geocarto international, vol 23 n° 6 (December 2008 - January 2009)
PermalinkSRTM resample with short distance-low nugget kriging / C.H. Grohmann in International journal of geographical information science IJGIS, vol 22 n° 8-9 (august 2008)
PermalinkA theoretical approach to modeling the accuracy assessment of digital elevation models / F. Aguilar in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 12 (December 2007)
PermalinkWeighting function alternatives for a subpixel allocation model / Y. Makido in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 11 (November 2007)
PermalinkEfficient multiresolution spatial predictions for large data arrays / Magnussen, Steen in Remote sensing of environment, vol 109 n° 4 (30 August 2007)
PermalinkDasymetric modelling of small-area population distribution using land cover and light emissions data / D.J. Briggs in Remote sensing of environment, vol 108 n° 4 (29 June 2007)
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