Green gentrification in Beijing's large urban parks:A multi-source spatiotemporal data analysis
As China progresses towards high-quality development,gentrification—especially green gentrification—has become increasingly influential in urban areas,necessitating a comprehensive investigation.Previous studies on green gentrification primarily utilized socio-economic data for their indicator systems,leading to two significant issues:A lack of localization and low spatiotemporal precision.This research aims to develop a more tailored indicator system for the domestic context using multi-source spatiotemporal data.Employing this system,the study examines six large urban parks within Beijing's Sixth Ring Road to explore their spatial patterns and distribution characteristics,offering new perspectives for understanding green gentrification in China and providing preliminary planning recommendations.This study begins by constructing a spatial data-based indicator system through a literature review and theoretical derivation,encompassing three main categories:land use,road networks,and points of interest(POI).Multi-year satellite imagery of Beijing from Google Maps is analyzed and classified into different types of land use,while multi-year road network and POI data are sourced from Gaode Map(Amap).Based on the collected data,the study undertakes three primary tasks.First,validation:The presence of green gentrification around Beijing's parks is assessed using the spatial difference-in-differences(SDID)model,which isolates the effects of large park development from other urban factors.Second,measurement:The extent of green gentrification is quantified by deriving a composite index from the three indicators through principal component analysis(PCA).Third,analysis:The spatial distribution of green gentrification is examined through multi-scale spatial analysis in ArcGIS,identifying its distribution patterns.After controlling for external influences,green gentrification is confirmed around the six large urban parks in Beijing.Results also indicate that the degree of gentrification is generally higher in parks located in the northern part of the city compared to those in the south,aligning with the distinct developmental strategies of different districts in Beijing.Furthermore,the spatial distribution of green gentrification exhibits two distinct patterns:a central-radiating distribution and a peripheral-dominant distribution.Additionally,there are two common trends:the simultaneous increase in green space and the rise in construction intensity.This study introduces a spatial data-based evaluation system,which expands the dimensions of assessment and enables a high-precision spatial perspective to study green gentrification.The findings partially align with traditional socioeconomic indicators,such as the presence of green gentrification around parks.New insights are also uncovered.For instance,the peripheral-dominant distribution arises from ecological or historical protections that create buffer zones around parks.This type of distribution has been rarely mentioned in previous research.Based on the research findings,future large urban park developments could be optimized in several ways,such as differentiated park development strategies,flexible reservation of park buffer zones,and coordinated green space initiatives.
green gentrificationlarge urban parksspatiotemporal dataspatial difference-in-differencesland use
NETL
NSTL
万方数据
