Sensing urban poverty: From the perspective of human perception-based greenery and open-space landscapes

Yuan Meng, Hanfa Xing, Yuan Yuan, Man Sing Wong, Kaixuan Fan

Research output: Journal article publicationJournal articleAcademic researchpeer-review

3 Citations (Scopus)

Abstract

Greenery and open spaces play significant roles in environmentally sustainable societies, providing urban ecosystem services and economic benefits that reduce urban poverty. Current urban poverty research has solely focused on top-down observations or direct human exposure to greenery and open spaces and has failed to sense landscape characteristics, including occupation and inequality, representing the social attributes of urban poverty. This paper demonstrates the potential to better understand certain social characteristics, including occupation and inequality between urban greenery and open spaces, and to further investigate their relationship with urban poverty. Percentage and aggregation indicators are proposed based on street view images to estimate the occupation and inequality between human perception-based greenery and open spaces. The relationship between human perception and urban poverty is accordingly analysed using geographically weighted regression (GWR). The GWR model results attain an R-squared value of 0.583 and further reveal that the relationships between human perception-based landscapes and urban poverty are spatially non-stationary, indicating varying relationships across space. This implication leads to an improved understanding of the relationship between greenery and open-space landscapes and living conditions and to further allowing effective policies to help identify deprived areas.

Original languageEnglish
Article number101544
JournalComputers, Environment and Urban Systems
Volume84
DOIs
Publication statusPublished - Nov 2020

Keywords

  • Greenery
  • Human perception
  • Landscape
  • Open space
  • Street view
  • Urban poverty

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Ecological Modelling
  • Environmental Science(all)
  • Urban Studies

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