Abstract: The evaluation of rural spatial vitality has become the focus of researches in recent years.However,the data traditionally used to quantify it are often subjective,costly,and laborious to procure.This study took the advantage of big data and adopted hourly Baidu heat map（BHM） data combined with field observation data as a proxy for portraying rural tourism vitality.It tested the density,convenience,accessibility of Point-of-Interest（POI）,and the walking accessibility of street networks and the impact of the quality of open space of Hongcun village on the density and stability of tourism space users,and used Bayesian-SEM to test five hypotheses of the relationship about the above five aspects and the vitality.The results show that：（1） the distribution of vitality of Hongcun village shows similar clustering characteristics on weekdays and holidays,and the core area of vitality is usually concentrated in important scenic spots and waterfront area;（2） POI convenience has the strongest positive impact on the vitality,while POI density has no significant impact;（3） in contrast to the urban environment,the normalized difference vegetation index （NDVI） of Hongcun village has a significant positive impact on the vitality.The findings can provide scientific basis and insights for the vitality-oriented spatial planning and redevelopment of rural tourism.

Key words: rural spatial vitality, built environment, big data, Bayesian-SEM, Hongcun village