Making the third dimension (3D) explicit in hedonic price modelling: A case study of Xi’an, China

Yue Ying, M. Koeva, M. Kuffer, K.O. Asiama, Xia Li, J. Zevenbergen

Research output: Contribution to journalArticleAcademicpeer-review

12 Citations (Scopus)
76 Downloads (Pure)


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 R2 (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 R2 (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.
Original languageEnglish
Article number24
Pages (from-to)1-26
Number of pages26
Issue number1
Publication statusPublished - Jan 2021




Dive into the research topics of 'Making the third dimension (3D) explicit in hedonic price modelling: A case study of Xi’an, China'. Together they form a unique fingerprint.

Cite this