Descripteur
Termes IGN > mathématiques > statistique mathématique > probabilités > stochastique > estimation statistique > estimation par noyau
estimation par noyau |
Documents disponibles dans cette catégorie (31)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
Space-time density of trajectories : exploring spatio-temporal patterns in movement data / Urška Demšar in International journal of geographical information science IJGIS, vol 24 n° 10 (october 2010)
[article]
Titre : Space-time density of trajectories : exploring spatio-temporal patterns in movement data Type de document : Article/Communication Auteurs : Urška Demšar, Auteur ; K. Virrantaus, Auteur Année de publication : 2010 Article en page(s) : pp 1527 - 1542 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse spatio-temporelle
[Termes IGN] densité
[Termes IGN] données localisées 3D
[Termes IGN] données spatiotemporelles
[Termes IGN] estimation par noyau
[Termes IGN] exploration de données géographiques
[Termes IGN] Finlande
[Termes IGN] navire
[Termes IGN] reconstruction d'itinéraire ou de trajectoire
[Termes IGN] trajectoire (véhicule non spatial)Résumé : (Auteur) Modern positioning and identification technologies enable tracking of almost any type of moving object. A remarkable amount of new trajectory data is thus available for the analysis of various phenomena. In cartography, a typical way to visualise and explore such data is to use a space-time cube, where trajectories are shown as 3D polylines through space and time. With increasingly large movement datasets becoming available, this type of display quickly becomes cluttered and unclear. In this article, we introduce the concept of 3D space-time density of trajectories to solve the problem of cluttering in the space-time cube. The space-time density is a generalisation of standard 2D kernel density around 2D point data into 3D density around 3D polyline data (i.e. trajectories). We present the algorithm for space-time density, test it on simulated data, show some basic visualisations of the resulting density volume and observe particular types of spatio-temporal patterns in the density that are specific to trajectory data. We also present an application to real-time movement data, that is, vessel movement trajectories acquired using the Automatic Identification System (AIS) equipment on ships in the Gulf of Finland. Finally, we consider the wider ramifications to spatial analysis of using this novel type of spatio-temporal visualisation. Numéro de notice : A2010-466 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658816.2010.511223 En ligne : https://doi.org/10.1080/13658816.2010.511223 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30659
in International journal of geographical information science IJGIS > vol 24 n° 10 (october 2010) . - pp 1527 - 1542[article]Réservation
Réserver ce documentExemplaires (2)
Code-barres Cote Support Localisation Section Disponibilité 079-2010061 RAB Revue Centre de documentation En réserve L003 Disponible 079-2010062 RAB Revue Centre de documentation En réserve L003 Disponible Multi-scale spatiotemporal analyses of moose-vehicle collisions: a case study in northern Vermont / Giorgos Mountrakis in International journal of geographical information science IJGIS, vol 23 n°11-12 (november 2009)
[article]
Titre : Multi-scale spatiotemporal analyses of moose-vehicle collisions: a case study in northern Vermont Type de document : Article/Communication Auteurs : Giorgos Mountrakis, Auteur ; K. Gunson, Auteur Année de publication : 2009 Article en page(s) : pp 1389 - 1412 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] accident de la route
[Termes IGN] analyse spatio-temporelle
[Termes IGN] Cervidae
[Termes IGN] estimation par noyau
[Termes IGN] Mammalia
[Termes IGN] outil d'aide à la décision
[Termes IGN] trafic routier
[Termes IGN] véhicule automobile
[Termes IGN] Vermont (Etats-Unis)Résumé : (Auteur) Moose-vehicle collisions (MVCs) pose a serious safety and environmental concern in many regions of Europe and North America. For example, in the state of Vermont, one-third of all reported MVCs resulted in motorist injury or fatality while collisions have increased from two in 1982 to 164 in 2002. Our work used a MVC dataset from 1983 to 1999 in the Northeastern Highlands of Vermont (four major roads) to perform space, time and spatiotemporal analyses and guide future mitigation strategies. An adapted kernel density estimator was implemented for exploratory analyses to detect high density collision hotspots on roads. The kernel in space showed seven major density peaks which varied in magnitude and spread between roads. The kernel estimator in time for all roads showed an exponentially increasing trend with annual periodicity and a seasonal cyclic component, where the majority of collisions occurred from May to October. Spatiotemporal kernel estimation exhibited discontinuous density hotspots in time and space suggesting changing animal movement patterns across roads. We used an adapted Ripley's K-function to test the hypothesis that MVCs clustering occurred at multiple scales in space, in time and in space-time combined. Statistically significant spatial clustering was evident on all roads at spatial scales from 2 to 10 km. A more consistent clustering in time occurred on all roads at a scale distance of 5 years. Similar to the kernel estimation, annual periodicity was also evident. Positive space-time clustering was present at small spatial (5 km) and temporal scales (2 years) indicating that where MVCs occur is also influenced by when they occur. In retrospect, using multiple road lengths, and the combined kernel estimation and Ripley's K-function in time and space, provided a powerful methodology to study varying spatiotemporal patterns of wildlife collisions along roads. This can greatly assist transportation planners in identifying optimal mitigation strategies along specific roads, such as deciding on location and spatial length for permanent and expensive measures (e.g. crossing structures and associated fencing) versus less permanent and inexpensive structures (e.g. wildlife signage and reduced speed limits). Copyright Taylor & Francis Numéro de notice : A2009-513 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658810802406132 En ligne : https://doi.org/10.1080/13658810802406132 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30142
in International journal of geographical information science IJGIS > vol 23 n°11-12 (november 2009) . - pp 1389 - 1412[article]Réservation
Réserver ce documentExemplaires (2)
Code-barres Cote Support Localisation Section Disponibilité 079-09071 RAB Revue Centre de documentation En réserve L003 Disponible 079-09072 RAB Revue Centre de documentation En réserve L003 Disponible A kernel density estimation method for networks, its computational method and a GIS-based tool / Atsuyuki Okabe in International journal of geographical information science IJGIS, vol 23 n° 1-2 (january 2009)
[article]
Titre : A kernel density estimation method for networks, its computational method and a GIS-based tool Type de document : Article/Communication Auteurs : Atsuyuki Okabe, Auteur ; T. Satoh, Auteur ; K. Sugiharas, Auteur Année de publication : 2009 Article en page(s) : pp 7 - 32 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] densité des points
[Termes IGN] erreur systématique
[Termes IGN] estimation par noyau
[Termes IGN] implémentation (informatique)
[Termes IGN] module d'extension
[Termes IGN] noeud
[Termes IGN] réseau routier
[Termes IGN] système d'information géographique
[Termes IGN] visualisation de donnéesRésumé : (Auteur) We develop a kernel density estimation method for estimating the density of points on a network and implement the method in the GIS environment. This method could be applied to, for instance, finding 'hot spots' of traffic accidents, street crimes or leakages in gas and oil pipe lines. We first show that the application of the ordinary two-dimensional kernel method to density estimation on a network produces biased estimates. Second, we formulate a 'natural' extension of the univariate kernel method to density estimation on a network, and prove that its estimator is biased; in particular, it overestimates the densities around nodes. Third, we formulate an unbiased discontinuous kernel function on a network. Fourth, we formulate an unbiased continuous kernel function on a network. Fifth, we develop computational methods for these kernels and derive their computational complexity; and we also develop a plug-in tool for operating these methods in the GIS environment. Sixth, an application of the proposed methods to the density estimation of traffic accidents on streets is illustrated. Lastly, we summarize the major results and describe some suggestions for the practical use of the proposed methods. Numéro de notice : A2009-125 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658810802475491 En ligne : https://doi.org/10.1080/13658810802475491 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29755
in International journal of geographical information science IJGIS > vol 23 n° 1-2 (january 2009) . - pp 7 - 32[article]Réservation
Réserver ce documentExemplaires (2)
Code-barres Cote Support Localisation Section Disponibilité 079-09011 RAB Revue Centre de documentation En réserve L003 Disponible 079-09012 RAB Revue Centre de documentation En réserve L003 Disponible Spatial aspects of MRSA epidemiology: a case study using stochastic simulation, kernel estimation and SaTScan / Lucy Bastin in International journal of geographical information science IJGIS, vol 21 n° 6-7 (july 2007)
[article]
Titre : Spatial aspects of MRSA epidemiology: a case study using stochastic simulation, kernel estimation and SaTScan Type de document : Article/Communication Auteurs : Lucy Bastin, Auteur ; J. Rollason, Auteur ; A. Hilton, Auteur ; et al., Auteur Année de publication : 2007 Article en page(s) : pp 811 - 836 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] analyse de groupement
[Termes IGN] analyse spatiale
[Termes IGN] épidémie
[Termes IGN] estimation par noyau
[Termes IGN] Grande-Bretagne
[Termes IGN] maladie bactérienne
[Termes IGN] simulation
[Termes IGN] surveillance sanitaireRésumé : (Auteur) The identification of disease clusters in space or space-time is of vital importance for public health policy and action. In the case of methicillin-resistant Staphylococcus aureus (MRSA), it is particularly important to distinguish between community and health care-associated infections, and to identify reservoirs of infection. 832 cases of MRSA in the West Midlands (UK) were tested for clustering and evidence of community transmission, after being geo-located to the centroids of UK unit postcodes (postal areas roughly equivalent to Zip+4 zip code areas). An age-stratified analysis was also carried out at the coarser spatial resolution of UK Census Output Areas. Stochastic simulation and kernel density estimation were combined to identify significant local clusters of MRSA (p Numéro de notice : A2007-273 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658810601135767 En ligne : https://doi.org/10.1080/13658810601135767 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28636
in International journal of geographical information science IJGIS > vol 21 n° 6-7 (july 2007) . - pp 811 - 836[article]Réservation
Réserver ce documentExemplaires (2)
Code-barres Cote Support Localisation Section Disponibilité 079-07041 RAB Revue Centre de documentation En réserve L003 Disponible 079-07042 RAB Revue Centre de documentation En réserve L003 Disponible Mapping wildfire occurrence at regional scale / J. De La Riva in Remote sensing of environment, vol 92 n° 3 (30 August 2004)
[article]
Titre : Mapping wildfire occurrence at regional scale Type de document : Article/Communication Auteurs : J. De La Riva, Auteur ; F. Perez-Cabello, Auteur ; et al., Auteur Année de publication : 2004 Article en page(s) : pp 363 - 369 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse diachronique
[Termes IGN] cartographie automatique
[Termes IGN] données maillées
[Termes IGN] estimation par noyau
[Termes IGN] incendie de forêt
[Termes IGN] interpolation
[Termes IGN] reconnaissance de surfaceRésumé : (Auteur) When assessing fire danger, interpolation of the dependent variable-historic fire occurrence-is required in order to statistically compare and analyze it with human factors, environmental parameters and census statistics. To confirm the compatibility between the distinct data types, occasionally, for this kind of spatial analysis, historical observations of the primary wildland fire (given as x and y coordinates) must be transformed either to continuous surfaces or to area data. The simple overlay approach converts single point observations to area data. However, this procedure assumes lack of spatial uncertainties that would otherwise result in serious errors caused by the positional inaccuracies of the original point observations.
Here, we used kernel density interpolation to convert the original data on wildland fire ignition into an expression of areal units, defined by a raster grid and, subsequently, by the administrative borders of the municipalities in two study areas in Spain. By overlaying a normal bivariate probability density function (kernel) over each point observation, each ignition point was considered an uncertain point location rather than an exact one.Numéro de notice : A2004-385 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2004.06.022 En ligne : https://doi.org/10.1016/j.rse.2004.06.022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26912
in Remote sensing of environment > vol 92 n° 3 (30 August 2004) . - pp 363 - 369[article]