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<p>Urban environments shape residents’ emotions, yet most studies ignore spatial heterogeneity. This study aims to quantify how environmental attributes jointly influence positive emotion across urban mosaic. We extracted a Positive Emotion Index from geotagged Weibo posts, screened eight candidate variables with correlation and stepwise regression, and modelled the retained five factors with Geographically Weighted Regression (adjusted R² = 0.685). Monthly coordination analysis and bivariate local Moran’s I further assessed dynamic and static influences. Weather factors exerted the strongest positive effects (mean standardized coefficients: visibility = 15.13; wind speed = 16.16); airquality concern persisted beyond the heating season; wind speed generally uplifted emotions but less so in parks; high vegetation cover most benefited parks, while a high landuse mix improved emotion only where daily amenities were adequate; citycenter residents preferred high POI density, whereas suburbanites favored lower densities. Mapping where and when environmental drivers matter most provides actionable evidence for humancentered planning and demonstrates how volunteered geographic information can enrich psychological research on emotion.</p>

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Geospatial Variations in the Influence of Urban Environmental Attributes on Positive Emotions

  • 期刊论文

  • 发表日期：

    2025年8月26日

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  • Huijun Zhou,
  • Junlei Yuan,
  • Yuxin Zhao,
  • Jing Zhang

摘要

Urban environments shape residents’ emotions, yet most studies ignore spatial heterogeneity. This study aims to quantify how environmental attributes jointly influence positive emotion across urban mosaic. We extracted a Positive Emotion Index from geotagged Weibo posts, screened eight candidate variables with correlation and stepwise regression, and modelled the retained five factors with Geographically Weighted Regression (adjusted R² = 0.685). Monthly coordination analysis and bivariate local Moran’s I further assessed dynamic and static influences. Weather factors exerted the strongest positive effects (mean standardized coefficients: visibility = 15.13; wind speed = 16.16); airquality concern persisted beyond the heating season; wind speed generally uplifted emotions but less so in parks; high vegetation cover most benefited parks, while a high landuse mix improved emotion only where daily amenities were adequate; citycenter residents preferred high POI density, whereas suburbanites favored lower densities. Mapping where and when environmental drivers matter most provides actionable evidence for humancentered planning and demonstrates how volunteered geographic information can enrich psychological research on emotion.