Road distance and travel time for an improved house price Kriging predictor

Henry Crosby*, Theo Damoulas, Alex Caton, Paul Davis, João Porto de Albuquerque, Stephen A. Jarvis

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

The paper designs an automated valuation model to predict the price of residential property in Coventry, United Kingdom, and achieves this by means of geostatistical Kriging, a popularly employed distance-based learning method. Unlike traditional applications of distance-based learning, this papers implements non-Euclidean distance metrics by approximating road distance, travel time and a linear combination of both, which this paper hypothesizes to be more related to house prices than straight-line (Euclidean) distance. Given that–to undertake Kriging–a valid variogram must be produced, this paper exploits the conforming properties of the Minkowski distance function to approximate a road distance and travel time metric. A least squares approach is put forth for variogram parameter selection and an ordinary Kriging predictor is implemented for interpolation. The predictor is then validated with 10-fold cross-validation and a spatially aware checkerboard hold out method against the almost exclusively employed, Euclidean metric. Given a comparison of results for each distance metric, this paper witnesses a goodness of fit (r2) result of 0.6901 ± 0.18 SD for real estate price prediction compared to the traditional (Euclidean) approach obtaining a suboptimal r2 value of 0.66 ± 0.21 SD.

Original languageEnglish
Pages (from-to)185-194
Number of pages10
JournalGeo-Spatial Information Science
Volume21
Issue number3
DOIs
Publication statusPublished - 3 Jul 2018

Bibliographical note

Funding Information:
This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) Centre for Doctoral Training in Urban Science: [Grant Number EP/L016400/1] and Assured Property Group. This work was also supported by The Alan Turing Institute: [Grant Number EP/ N510129/1] and the Lloyd’s Register Foundation programme on Data Centric Engineering.

Publisher Copyright:
©, © 2018 Wuhan University. Published by Informa UK Limited, trading as Taylor & Francis Group.

Keywords

  • Kriging
  • Minkowski
  • real-estate valuation
  • road distance
  • travel time

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Computers in Earth Sciences

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