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

Download statistics - Document (COUNTER):

Ying, Y.; Koeva, M.; Kuffer, M.; Asiama, K.O.; Li, X. et al.: Making the third dimension (3D) explicit in hedonic price modelling : A case study of Xi’an, China. In: Land 10 (2021), Nr. 1, 24. DOI:

Repository version

To cite the version in the repository, please use this identifier:

Selected time period:


Sum total of downloads: 65

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. © 2020 by the authors. Li-censee MDPI, Basel, Switzerland.
License of this version: CC BY 4.0 Unported
Document Type: article
Publishing status: publishedVersion
Issue Date: 2021
Appears in Collections:Fakultät für Bauingenieurwesen und Geodäsie

distribution of downloads over the selected time period:

downloads by country:

pos. country downloads
total perc.
1 image of flag of United States United States 22 33.85%
2 image of flag of Germany Germany 19 29.23%
3 image of flag of Ukraine Ukraine 6 9.23%
4 image of flag of China China 6 9.23%
5 image of flag of Morocco Morocco 5 7.69%
6 image of flag of United Kingdom United Kingdom 2 3.08%
7 image of flag of Netherlands Netherlands 1 1.54%
8 image of flag of Indonesia Indonesia 1 1.54%
9 image of flag of France France 1 1.54%
10 image of flag of Canada Canada 1 1.54%
    other countries 1 1.54%

Further download figures and rankings:


Zur Erhebung der Downloadstatistiken kommen entsprechend dem „COUNTER Code of Practice for e-Resources“ international anerkannte Regeln und Normen zur Anwendung. COUNTER ist eine internationale Non-Profit-Organisation, in der Bibliotheksverbände, Datenbankanbieter und Verlage gemeinsam an Standards zur Erhebung, Speicherung und Verarbeitung von Nutzungsdaten elektronischer Ressourcen arbeiten, welche so Objektivität und Vergleichbarkeit gewährleisten sollen. Es werden hierbei ausschließlich Zugriffe auf die entsprechenden Volltexte ausgewertet, keine Aufrufe der Website an sich.

Search the repository