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Embedding road networks and travel time into distance metrics for urban modelling / Henry Crosby in International journal of geographical information science IJGIS, Vol 33 n° 3-4 (March - April 2019)  

Public [article]  inInternational journal of geographical information science IJGIS > Vol 33 n° 3-4 (March - April 2019) . - pp 512 - 536 Titre : Embedding road networks and travel time into distance metrics for urban modelling Type de document : Article/Communication Auteurs : Henry Crosby, Auteur ; theodore Damoulas, Auteur ; Stephen A. Jarvis, Auteur Année de publication : 2019 Article en page(s) : pp 512 - 536 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] covariance [Termes IGN] distance euclidienne [Termes IGN] durée de trajet [Termes IGN] espace-temps [Termes IGN] géostatistique [Termes IGN] isométrie [Termes IGN] krigeage [Termes IGN] logement [Termes IGN] modèle de simulation [Termes IGN] réseau routier [Termes IGN] trafic routier [Termes IGN] urbanisme [Termes IGN] variogramme Résumé : (auteur) Urban environments are restricted by various physical, regulatory and customary barriers such as buildings, one-way systems and pedestrian crossings. These features create challenges for predictive modelling in urban space, as most proximity-based models rely on Euclidean (straight line) distance metrics which, given restrictions within the urban landscape, do not fully capture spatial urban processes. Here, we argue that road distance and travel time provide effective alternatives, and we develop a new low-dimensional Euclidean distance metric based on these distances using an isomap approach. The purpose of this is to produce a valid covariance matrix for Kriging. Our primary methodological contribution is the derivation of two symmetric dissimilarity matrices (B+ and B2+), with which it is possible to compute low-dimensional Euclidean metrics for the production of a positive definite covariance matrix with commonly utilised kernels. This new method is implemented into a Kriging predictor to estimate house prices on 3,669 properties in Coventry, UK. We find that a metric estimating a combination of road distance and travel time, in both R2 and R3, produces a superior house price predictor compared with alternative state-of-the-art methods, that is, a standard Euclidean metric in RN and a non-restricted road distance metric in R2 and R3. F Numéro de notice : A2019-024 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1547386 Date de publication en ligne : 06/12/2018 En ligne : https://doi.org/10.1080/13658816.2018.1547386 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91952 [article]

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