基于腾讯位置数据的中国城市居民航空出行时空特征

随着中国经济社会的快速发展,航空出行成为居民出行方式的重要组成部分,并影响着城市格局。本文基于2019年4月28日—5月10日国内215个机场的腾讯定位请求数据,分析中国城市居民在工作日和五一假日两个场景下的航空出行时空特征,进而探究其与城市格局的关系。结果表明：①中国城市居民航空出行在空间上,总体呈现东部沿海高于内陆地区,且中部地区相对较低的特点;②在时间上,多集中在工作日,且京津冀、长三角、粤港澳大湾区、成渝等经济发达地区的中心城市更偏向“工作日优势型”,而中部地区及西南部地区的非区域中心城市更偏向“假日优势型”,并呈现以24小时为周期的下降、上升和波动的日变化,与工作日相比,五一假日提前2小时进入波动期,且居民假日航班时间选择更偏向在下午3点和晚上8点前后;③在工作日和假日两类场景下,所呈现的聚类等级分化与其所在城市规模之间关联性较强,在一定程度上接近城市金字塔的规模等级分布特征。

ANALYSIS OF SPATIAL AND TEMPORAL CHARACTERISTICS OF RESIDENTS' AIR TRAVEL BASED ON TENCENT LOCATION BIG DATA IN CHINESE CITIES

With the rapid development of China's economy and society, air travel has become an important part of residents' travel mode, and affects the urban pattern. Based on the Tencent positioning request data of 215 domestic airports from April 28 to May 10, 2019, this paper analyzes the spatio-temporal characteristics of Chinese urban residents' air travel under the two scenarios of May Day holiday and working day, and further explores the relationship between them and urban pattern. The results show that:1) The spatial characteristics of air travel of urban residents in China are generally higher in the eastern coastal area than in the inland area, and lower in the central area; 2) The air travel choice of urban residents in China is mostly concentrated in working day, and the central cities in Beijing-Tianjin-Hebei region, Yangtze River Delta, Guangdong-Hong Kong-Macao Greater Bay Area, Chengdu-Chongqing area and other economically developed regions are more inclined to "working-day advantage type", while the non regional central cities in central and southwest regions are more inclined to "holiday advantage type", and residents' air travel shows a 24-hour cycle of decline, rise and fluctuation. Compared with working days, May Day holiday entered the fluctuation period 2 hours ahead of schedule, and residents preferred to choose the flight time around 3pm and 8pm. 3) In the two scenarios of working day and holiday, there is a strong correlation between the hierarchical differentiation of city cluster and the city scale. To some extent, the cluster distribution of cities is close to the pyramid of city scale.