This study utilizes bus ridership data from Beijing,integrating multi-source data such as points of interest(POI)and land use.Six districts within Beijing's central urban area are selected as the study area.The multi-scale geographically weighted regression(MGWR)model is applied to investigate the spatial heterogeneity of the built environment's impact on bus ridership around bus stops,with comparative analysis against other models.The findings reveal that:① Local models accounting for spatial heterogeneity(MGWR and GWR)outperform the global model(OLS)in analyzing variations in bus ridership,with MGWR providing the best fit;②Bus ridership is influenced by multiple factors and exhibits significant spatial clustering;③The influence of each variable shows spatial heterogeneity,with commercial services and transportation facilities positively correlated with bus ridership.Enhancing the construction of these facilities not only contributes to public transportation development but also improves the adaptability and recovery capacity of the urban transportation system in response to emergencies or changes,thereby strengthening urban transportation resilience.
关键词
公共交通/建成环境/公交客流/多尺度地理加权回归模型/GIS
Key words
public transport/built environment/public transit flows/MGWR/GIS
维普
万方数据