A spatiotemporal analysis of the effects of urbanization's socio-economic factors on landscape patterns considering operational scales

Pengyu Liu, Chao Wu, Miaomiao Chen, Xinyue Ye, Yunfei Peng, Sheng Li

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Landscape patterns are significantly affected during the urbanization process. Identifying the spatiotemporal impacts of urbanization's socio-economic factors on landscape patterns is very important and can provide scientific evidence to support urban ecological management and guide managers to establish appropriate sustainability policies. This article applies multiscale geographically weighted regression (MGWR) to reveal the relationships between landscape patterns and the socio-economic factors of urbanization in Shenzhen, China, from 2000 to 2015, in five-year intervals. MGWR is a powerful extension of geographically weighted regression (GWR) that can not only reveal spatial heterogeneity patterns but also measure the operational scale of covariates. The empirical results indicate that MGWR is superior to GWR. Furthermore, the changes in operational scale represented by the spatial bandwidth of MGWR in different years reflect temporal changes in the spatial relationships of given factors, which is significant information for urban studies. These multiscale relationships between landscape patterns and the socio-economic factors of urbanization, revealed via MGWR, are useful for strategic planning around urban dynamic development and land resource and ecological landscape management. The results can provide additional insight into landscape and urbanization studies from a multiscale perspective, which is important for local, regional, and global urban planning.

Original languageEnglish (US)
Article number2543
JournalSustainability (Switzerland)
Volume12
Issue number6
DOIs
StatePublished - Mar 1 2020

All Science Journal Classification (ASJC) codes

  • Geography, Planning and Development
  • Renewable Energy, Sustainability and the Environment
  • Environmental Science (miscellaneous)
  • Energy Engineering and Power Technology
  • Management, Monitoring, Policy and Law

Keywords

  • Landscape pattern
  • Scale
  • Shenzhen
  • Spatial heterogeneity
  • Urbanization

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