Resumen
Many people in the world do not have enough physical activities to maintain good health, which has recently become a threat to public health. In addition to individual genetic and social factors, we considered the geographical environment of the city as a factor that affects these healthy physical activities. We used the location-based data in social media combined with the open geographic data to explore the impact mechanism of urban environmental factors on human running behaviors. This study collected nine urban environmental variables and preference tracks in Beijing?s main urban area. We used the Maximum Entropy Model (MaxEnt) to analyze the relationship between running behaviors and environmental variables and identify suitable areas for running in Beijing. The results showed that: firstly, the variables of attractions, sports and sidewalk density contributed the most to running suitability. Secondly, 47.5% of the main urban areas in Beijing are suitable for running, mainly in the main urban areas with better economic development. Thirdly, the distribution of suitable places for running is unfair in that some places with large populations do not have a matching running environment.