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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)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 23 n° 1-2 (january 2009) . - pp 7 - 32 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 données Résumé : (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 [article]

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