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

Show simple item record

dc.identifier.uri http://dx.doi.org/10.15488/10561
dc.identifier.uri https://www.repo.uni-hannover.de/handle/123456789/10638
dc.contributor.author Ying, Yue
dc.contributor.author Koeva, Mila
dc.contributor.author Kuffer, Monika
dc.contributor.author Asiama, Kwabena Obeng
dc.contributor.author Li, Xia
dc.contributor.author Zevenbergen, Jaap
dc.date.accessioned 2021-03-17T13:48:24Z
dc.date.available 2021-03-17T13:48:24Z
dc.date.issued 2021
dc.identifier.citation 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: https://doi.org/10.3390/land10010024
dc.description.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 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. eng
dc.language.iso eng
dc.publisher Basel : MDPI AG
dc.relation.ispartofseries Land 10 (2021), Nr. 1
dc.rights CC BY 4.0 Unported
dc.rights.uri https://creativecommons.org/licenses/by/4.0/
dc.subject 3D modelling eng
dc.subject China eng
dc.subject Hedonic price model eng
dc.subject Property value eng
dc.subject Remote sensing eng
dc.subject.ddc 630 | Landwirtschaft, Veterinärmedizin ger
dc.title Making the third dimension (3D) explicit in hedonic price modelling : A case study of Xi’an, China
dc.type article
dc.type Text
dc.relation.essn 2073-445X
dc.relation.doi https://doi.org/10.3390/land10010024
dc.bibliographicCitation.issue 1
dc.bibliographicCitation.volume 10
dc.bibliographicCitation.firstPage 24
dc.description.version publishedVersion
tib.accessRights frei zug�nglich


Files in this item

This item appears in the following Collection(s):

Show simple item record

 

Search the repository


Browse

My Account

Usage Statistics