Developing a comprehensive understanding of inter-city interactions is crucial for regional planning.We therefore examined spatiotemporal patterns of population migration across the Qinghai-Tibet Plateau(QTP)using mig...Developing a comprehensive understanding of inter-city interactions is crucial for regional planning.We therefore examined spatiotemporal patterns of population migration across the Qinghai-Tibet Plateau(QTP)using migration big data from Tencent for the period between 2015 and 2019.We initially used decomposition and breakpoint detection methods to examine time-series migration data and to identify the two seasons with the strongest and weakest population migration levels,between June 18th and August 18th and between October 8th and February 15th,respectively.Population migration within the former period was 2.03 times that seen in the latter.We then used a variety of network analysis methods to examine population flow directions as well as the importance of each individual city in migration.The two capital cities on the QTP,Lhasa and Xining,form centers for population migration and are also transfer hubs through which migrants from other cities off the plateau enter and leave this region.Data show that these two cities contribute more than 35%of total population migration.The majority of migrants tend to move within the province,particularly during the weakest migration season.We also utilized interactive relationship force and radiation models to examine the interaction strength and the radiating energy of each individual city.Results show that Lhasa and Xining exhibit the strongest interactions with other cities and have the largest radiating energies.Indeed,the radiating energy of the QTP cities correlates with their gross domestic product(GDP)(Pearson correlation coefficient:0.754 in the weakest migration season,WMS versus 0.737 in the strongest migration season,SMS),while changes in radiating energy correlate with the tourism-related revenue(Pearson correlation coefficient:0.685).These outcomes suggest that level of economic development and level of tourism are the two most important factors driving the QTP population migration.The results of this analysis provide critical clarification guidance regarding huge QTP development differences.展开更多
Human migration between cities is one important aspect of spatial interaction that not only reflects urban attractiveness but also denotes interactions amongst agglomerations.We therefore implemented a web-based visua...Human migration between cities is one important aspect of spatial interaction that not only reflects urban attractiveness but also denotes interactions amongst agglomerations.We therefore implemented a web-based visualization system to analyze and interactively explore local and distant population flow patterns between cities on the Qinghai-Tibet Plateau(QTP).We utilized 2017 Tencent population flow data from which we initially constructed inbound and outbound vectors for cities on the QTP.We then used multidimensional scaling to examine and visualize migration patterns and similarities between cities.Results reveal the presence of six local and three distant human mobility patterns on the QTP as well as average summer monthly migrations more than twice the level of those in the winter.展开更多
基金National Natural Science Foundation of China(41590845)Strategic Priority Research Program of the Chinese Academy of Sciences(XDA19040501)+2 种基金Strategic Priority Research Program of the Chinese Academy of Sciences(XDA20040401)National Key Research and Development Program of China(2017YFB0503605)National Key Research and Development Program of China(2017YFC1503003)。
文摘Developing a comprehensive understanding of inter-city interactions is crucial for regional planning.We therefore examined spatiotemporal patterns of population migration across the Qinghai-Tibet Plateau(QTP)using migration big data from Tencent for the period between 2015 and 2019.We initially used decomposition and breakpoint detection methods to examine time-series migration data and to identify the two seasons with the strongest and weakest population migration levels,between June 18th and August 18th and between October 8th and February 15th,respectively.Population migration within the former period was 2.03 times that seen in the latter.We then used a variety of network analysis methods to examine population flow directions as well as the importance of each individual city in migration.The two capital cities on the QTP,Lhasa and Xining,form centers for population migration and are also transfer hubs through which migrants from other cities off the plateau enter and leave this region.Data show that these two cities contribute more than 35%of total population migration.The majority of migrants tend to move within the province,particularly during the weakest migration season.We also utilized interactive relationship force and radiation models to examine the interaction strength and the radiating energy of each individual city.Results show that Lhasa and Xining exhibit the strongest interactions with other cities and have the largest radiating energies.Indeed,the radiating energy of the QTP cities correlates with their gross domestic product(GDP)(Pearson correlation coefficient:0.754 in the weakest migration season,WMS versus 0.737 in the strongest migration season,SMS),while changes in radiating energy correlate with the tourism-related revenue(Pearson correlation coefficient:0.685).These outcomes suggest that level of economic development and level of tourism are the two most important factors driving the QTP population migration.The results of this analysis provide critical clarification guidance regarding huge QTP development differences.
基金Strategic Priority Research Program of Chinese Academy of Sciences,Pan-Third Pole Environment Study for a Green Silk Road(Pan-TPE)(XDA20040401)National Natural Science Foundation of China(41525004)+1 种基金National Natural Science Foundation of China(41771477)National Natural Science Foundation of China(42071376)。
文摘Human migration between cities is one important aspect of spatial interaction that not only reflects urban attractiveness but also denotes interactions amongst agglomerations.We therefore implemented a web-based visualization system to analyze and interactively explore local and distant population flow patterns between cities on the Qinghai-Tibet Plateau(QTP).We utilized 2017 Tencent population flow data from which we initially constructed inbound and outbound vectors for cities on the QTP.We then used multidimensional scaling to examine and visualize migration patterns and similarities between cities.Results reveal the presence of six local and three distant human mobility patterns on the QTP as well as average summer monthly migrations more than twice the level of those in the winter.
