Sensing urban poverty: From the perspective of human perception-based greenery and open-space landscapes. (November 2020)

• Record Type: Journal Article
• Authors: Meng, Yuan; Xing, Hanfa; Yuan, Yuan; Wong, Man Sing; Fan, Kaixuan
• Is Part Of: Computers, environment and urban systems. Volume 84(2020)
• Publication Date: 2020-11
• Subjects: Human perception -- Greenery -- Open space -- Landscape -- Urban poverty -- Street view; City planning -- Data processing -- Periodicals; Regional planning -- Data processing -- Periodicals; 303.4834
• DOI: 10.1016/j.compenvurbsys.2020.101544
• Languages: English
• ISSNs: 0198-9715

Abstract

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. Highlights: Human perception-based greenery and open-space landscapes are understood from the perception of occupation and inequality. A geographically weighted regression model is applied to investigate human perception-based landscapes and urban poverty. The relationships between human perception-based landscapes and urban poverty are spatially non-stationary.