基于腾讯迁徙大数据的长三角城市群春运人口流动时空特征

开展城市群人口流动研究对促进区域人口有序流动和城市群协同发展具有重要的理论和实践指导意义。本文基于腾讯迁徙大数据，运用GIS空间统计和K-shell分解等方法，从人口流动总量、位序、时序和网络层级等方面，对我国长三角城市群2018年春运期间的人口流动特征进行系统研究。结果表明：①长三角城市群春运期间大规模的“返乡流”和“返城流”呈现明显的对称性，并分别于除夕和第一个工作日达到最高峰。②经济发展水平相对较高的上海、苏州、杭州等为劳动力输入型城市，而经济发展水平相对较低的盐城、安庆和滁州等为劳动力输出型城市。③长三角城市群内部人口流动网络具有明显的层级特征，其中上海和杭州是人口辐射核心城市，上海-合肥、上海-南京、上海-杭州等是人口流动的主体路径；空间上东部-西部横向人口流动最为频繁，大体呈现“Z”字形。     

RAPID REGIONAL ENLARGEMENT IN SWEDEN: A PHENOMENON MISSING AN EXPLANATION

According to Swedish register data, regional size and the extent of commuting have both increased rapidly in recent decades. From the perspective of policy-making authorities, this would indicate good prospects for regional development, as small regions could be integrated into larger ones resulting in increased economic growth. However, there are few concrete manifestations of such regional enlargement, and alternative datasets give other impressions of the effects of commuting. Here we argue that this apparent growth might stem from several problems inherent in a register-based way of measuring changes in commuting patterns. Thus, regional enlargement and the extent of commuting may be exaggerated when measured conventionally, and the high hopes of using such enlargement to lever regional development might be misplaced. More generally, this study considers the problems arising as census or other enquiry and interview based data are replaced by register data.