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To study the impact of land-use factors on cross-line public transport commuter demand between Tongzhou and urban areas of Beijing,a spatial econometric model was used. First, public transport IC card data was used to obtain transport commuter demand. Second, the land-use types, transportation facilities and location factors were quantified based on the POI (point of interest) data of Beijing. Variable dimensions were reduced in the factor analysis method to eliminate redundant variables regarding land-use type, and eight comprehensive variables of land-use types are generated. Finally, The spatial auto regressive model, spatial error model and spatial Durbin model of travel demand and land-use were established for the trans-regional commuting origin O and destination D. Based on veritfing that travel demands was spatially relevant. Through comparison, the spatial Durbin model was selected for modeling the relationship between land-use and public transport demand. The results show that the global Moran's index of public cross-line commuting for O and D point is 0.385 and 0.503. Spatial econometric models are necessary for strong spatial correlations. The density of rail transit stations plays an active role in guiding travel demand for public cross-line commuting, yielding the largest influence coefficients of 11.56 and 9.82 for O and D point, respectively. The spatial lag variables for land-use mixing degrees has the greatest positive correlation to commuter the demand, with influence coefficients 0.51 and 0.68 for O and D point, respectively. That means that commuter demand of the district is improved when the land-use mixing degree is higher. The positive guidance of high-intensity land-use development and abundant public transport resources in transit travel has been verified from the perspective of spatial measurement. It provides a quantitative basis for the analysis of the interactive relationship between land-use and demand of public transport. 6 tabs, 11 figs, 25 refs. ©2018, Editorial Department of Journal of Chang'an University (Natural Science Edition). All right reserved.
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