Quantifying the degree of urban function mix has great signifi cance to both urban planning practices and studies. This paper, fi rst of all, based on the data of points of interest(POIs), analyzes the spatial distrib...Quantifying the degree of urban function mix has great signifi cance to both urban planning practices and studies. This paper, fi rst of all, based on the data of points of interest(POIs), analyzes the spatial distribution patterns of urban functions in Beijing. Then according to the taxi GPS data with the origin and destination points(taxi-ODs), we identify the spatial and temporal pattern of the degree of urban function mix in Beijing. Finally, based on the information entropy model of the POIs and taxi-ODs, we establish a spatial entropy and a temporal entropy to quantitatively assess the degree of urban function mix, confirming by virtue of correlation analysis and regression analysis that the spatial entropy of POIs is closely associated with the temporal entropy of taxi-ODs, which proves that it is reasonable to assess the degree of urban function mix via these two entropies. As a result, the degree of urban function mix in Beijing is characterized by slowly decreasing from its core area along the 3rd and 4th Ring Roads to its periphery. In detail, there is the highest degree of urban function mix in Beijing's traditional core areas, including Zhongguancun, CBD(Central Business District), the Old Dongcheng District, the Old Xicheng District, and the area within the 2nd Ring Road; a higher degree in Wangjing area; and a low degree in Tiantongyuan and Huilongguan communities. The analytical results have initially achieved a more accurate identifi cation and quantitative evaluation on the degree of urban function mix, and can be taken as a supporting tool to analyze the comprehensiveness of urban functions.展开更多
文摘Quantifying the degree of urban function mix has great signifi cance to both urban planning practices and studies. This paper, fi rst of all, based on the data of points of interest(POIs), analyzes the spatial distribution patterns of urban functions in Beijing. Then according to the taxi GPS data with the origin and destination points(taxi-ODs), we identify the spatial and temporal pattern of the degree of urban function mix in Beijing. Finally, based on the information entropy model of the POIs and taxi-ODs, we establish a spatial entropy and a temporal entropy to quantitatively assess the degree of urban function mix, confirming by virtue of correlation analysis and regression analysis that the spatial entropy of POIs is closely associated with the temporal entropy of taxi-ODs, which proves that it is reasonable to assess the degree of urban function mix via these two entropies. As a result, the degree of urban function mix in Beijing is characterized by slowly decreasing from its core area along the 3rd and 4th Ring Roads to its periphery. In detail, there is the highest degree of urban function mix in Beijing's traditional core areas, including Zhongguancun, CBD(Central Business District), the Old Dongcheng District, the Old Xicheng District, and the area within the 2nd Ring Road; a higher degree in Wangjing area; and a low degree in Tiantongyuan and Huilongguan communities. The analytical results have initially achieved a more accurate identifi cation and quantitative evaluation on the degree of urban function mix, and can be taken as a supporting tool to analyze the comprehensiveness of urban functions.
