The Library
Embedding road networks and travel time into distance metrics for urban modelling
Tools
Tools
Tools
Crosby, Henry James, Damoulas, Theodoros and Jarvis, Stephen A. (2018) Embedding road networks and travel time into distance metrics for urban modelling. International Journal of Geographical Information Science, 33 (3). pp. 512-536. doi:10.1080/13658816.2018.1547386 ISSN 1365-8816.
|
PDF
WRAP-embedding-road-networks-travel-time-distance-metrics-urban-modelling-Jarvis-2018.pdf - Published Version - Requires a PDF viewer. Available under License Creative Commons Attribution 4.0. Download (2759Kb) | Preview |
Official URL: https://doi.org/10.1080/13658816.2018.1547386
Abstract
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 predic- tive 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 spa- tial 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 (Bþ and B2þ), 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 R 2 and R 3 , 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 dis- tance metric in R2 and R3.
| Item Type: | Journal Article | ||||||
|---|---|---|---|---|---|---|---|
| Alternative Title: | |||||||
| Subjects: | G Geography. Anthropology. Recreation > GA Mathematical geography. Cartography H Social Sciences > HE Transportation and Communications |
||||||
| Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||||
| Library of Congress Subject Headings (LCSH): | City traffic -- Mathematical models, Urban transportation -- Mathematical models | ||||||
| Journal or Publication Title: | International Journal of Geographical Information Science | ||||||
| Publisher: | Taylor & Francis | ||||||
| ISSN: | 1365-8816 | ||||||
| Official Date: | 6 December 2018 | ||||||
| Dates: |
|
||||||
| Volume: | 33 | ||||||
| Number: | 3 | ||||||
| Page Range: | pp. 512-536 | ||||||
| DOI: | 10.1080/13658816.2018.1547386 | ||||||
| Status: | Peer Reviewed | ||||||
| Publication Status: | Published | ||||||
| Access rights to Published version: | Open Access (Creative Commons) | ||||||
| Date of first compliant deposit: | 29 March 2019 | ||||||
| Date of first compliant Open Access: | 1 April 2019 | ||||||
| RIOXX Funder/Project Grant: |
|
||||||
| Open Access Version: |
Request changes or add full text files to a record
Repository staff actions (login required)
 |
View Item |
Downloads
Downloads per month over past year
