The impact of landscape views and storey levels on property prices

Chi Man Hui, Jia Wei Zhong, Ka Hung Yu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

51 Citations (Scopus)

Abstract

The relationship between a property's transaction price and its landscape views has attracted scholarly attention over the years. The Spatial Durbin model, which can provide an unbiased estimate in all types of true spatial data-generation, is introduced in this study to discuss the impact of these landscape view factors on property prices. The emphasis of this paper is on various landscape view influences on different submarkets (i.e. storeys) of high-rise buildings in a compact city such as Hong Kong. The findings indicate that while the availability of garden view is found to be positively correlated with transaction prices of flats in all three submarkets, varying degrees of differences are observed as to the impact of landscape attributes (such as seaview and proximity to avenue/street) and of the spatial lag effect on transaction prices of flats in these submarkets. In particular, contrary to popular beliefs, the availability of seaview is not considered a positive attribute to the transaction prices of high-storey flats. These differences indicate the importance of vertical spatial influence which has not been considered in conventional spatial models, but is useful in studying the situations in other cities which are also compact and consist mainly of high-rise buildings.
Original languageEnglish
Pages (from-to)86-93
Number of pages8
JournalLandscape and Urban Planning
Volume105
Issue number1-2
DOIs
Publication statusPublished - 30 Mar 2012

Keywords

  • Landscape view effect
  • Spatial Durbin model
  • Storey
  • Submarket

ASJC Scopus subject areas

  • Ecology
  • Nature and Landscape Conservation
  • Management, Monitoring, Policy and Law

Fingerprint

Dive into the research topics of 'The impact of landscape views and storey levels on property prices'. Together they form a unique fingerprint.

Cite this