首页|Dynamic Assessment of Spatiotemporal Population Distribution Based on Mobile Phone Data:A Case Study in Xining City,China
Dynamic Assessment of Spatiotemporal Population Distribution Based on Mobile Phone Data:A Case Study in Xining City,China
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
万方数据
High-resolution,dynamic assessments of the spatiotemporal distributions of populations are critical for urban planning and disaster management.Mobile phone big data have real-time collection,wide coverage,and high resolution advantages and can thus be used to characterize human activities and population distributions at fine spatiotemporal scales.Based on six days of mobile phone user-location signal(MPLS)data,we assessed the dynamic spatiotemporal distribution of the population of Xining City,Qinghai Province,China.The results show that strong temporal regularity exists in the daily activities of local residents.The spatiotemporal distribution of the local population showed a significant downtown-suburban attenuation pattern.Factors such as land use types,holidays,and seasons significantly affect the spatiotemporal patterns of the local population.By combining other spatiotemporal trajectory data,high-resolution and dynamic real-time population distribution evaluations based on mobile phone location signals could be better developed and improved for use in urban management and disaster assessment research.
ChinaHigh-resolution mobile phone dataSpatiotemporal population distributionUrban managementXining City
Benyong Wei、Guiwu Su、Fenggui Liu
展开 >
Institute of Geology,China Earthquake Administration,Beijing 100029,China
Key Laboratory of Seismic and Volcanic Hazards,China Earthquake Administration,Beijing 100029,China
Academy of Plateau Science and Sustainability,People's Government of Qinghai Province and Beijing Normal University,Xining 810008,China
School of Geography,Qinghai Normal University,Xining 810016,China
展开 >
National Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Key R&D Program of China
万方数据
