Making the Third Dimension (3D) Explicit in Hedonic Price Modelling: A Case Study of Xi’an, China

authored by: Yue Ying, Mila Koeva, Monika Kuffer, Kwabena Asiama, X Li, Jaap Zevenbergen
Abstract: Recent rapid population growth and increasing urbanisation have led to fast vertical developments in urban areas. Therefore, in the context of the dynamic property market, factors related to the third dimension (3D) need to be considered. Current hedonic price modelling (HPM) studies have little explicit consideration for the third dimension, which may have a significant influence on modelling property values in complex urban environments. Therefore, our research aims to narrow the cognitive gap of the missing third dimension by assessing both 2D and 3D HPM and identifying important 3D factors for spatial analysis and visualisation in the selected study area, Xi’an, China. The statistical methods we used for 2D HPM are ordinary least squares (OLS) and geographically weighted regression (GWR). In 2D HPM, they both have very low R ² (0.111 in OLS and 0.217 in GWR), showing a very limited generalisation potential. However, a significant improvement is observed when adding 3D factors, namely view quality, sky view factor (SVF), sunlight and property orientation. The obtained higher R ² (0.414) shows the importance of the third dimension or—3D factors for HPM. Our findings demonstrate the necessity to include such factors into HPM and to develop 3D models with a higher level of details (LoD) to serve more purposes such as fair property taxation.
Organisation(s): Geodetic Institute
External Organisation(s): University of Twente
Chang'an University
Type: Article
Journal: Land Use Policy
Volume: 10
No. of pages: 26
ISSN: 0264-8377
Publication date: 01.2021
Publication status: Published
Peer reviewed: Yes
ASJC Scopus subject areas: Global and Planetary Change, Ecology, Nature and Landscape Conservation
Sustainable Development Goals: SDG 11 - Sustainable Cities and Communities
Electronic version(s): https://doi.org/10.3390/land10010024 (Access: Open)
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