[1] 约500多万人离开了武汉[online](2020). http://news.china.com.cn/2020-01/26/content_75650784.htm
[2] et alMigration patterns in China extracted from mobile positioning data[J]. Habitat International, 86, 71-80(2019).
[3] Visualizing the largest annual human migration during the Spring Festival travel season in China[J]. Environment and Planning A: Economy and Space, 51, 1618-1621(2019).
[4] et alThe rich-club phenomenon of China's population flow network during the country's spring festival[J]. Applied Geography, 96, 77-85(2018).
[5] et alSpatial-temporal analysis on Spring Festival travel rush in China based on multisource big data[J]. Sustainability, 8, 1184(2016).
[6] et alInferring spatial interaction patterns from sequential snapshots of spatial distributions[J]. International Journal of Geographical Information Science, 32, 783-805(2018).
[7] et alTracing the largest seasonal migration on earth[J]. arXiv preprint arXiv: 1411.0983(2014).
[8] Urban population mobility patterns in Spring Festival Transportation: Insights from Weibo data[C]. 2017 International Conference on Service Systems and Service Management. IEEE, 1-6(2017).
[9] et alDifference of urban development in China from the perspective of passenger transport around Spring Festival[J]. Applied Geography, 87, 85-96(2017).
[10] et alThe spatial allocation of population: A review of large-scale gridded population data products and their fitness for use[J]. Earth System Science Data, 11, 3(2019).
[11] et alSpatially disaggregated population estimates in the absence of national population and housing census data[J]. Proceedings of the National Academy of Sciences, 115, 3529-3537(2018).
[12] et alMapping fine-scale population distributions at the building level by integrating multisource geospatial big data[J]. International Journal of Geographical Information Science, 31, 1220-1244(2017).
[13] et alImproving large area population mapping using geotweet densities[J]. Transactions in GIS, 21, 317-331(2017).
[14] Urban phenology: Toward a real-time census of the city using Wi-Fi data[J]. Computers, Environment and Urban Systems, 64, 144-153(2017).
[15] et alPopulation distribution modelling at fine spatio-temporal scale based on mobile phone data[J]. International Journal of Digital Earth, 12, 1319-1340(2019).
[16] et alModeling the hourly distribution of population at a high spatiotemporal resolution using subway smart card data: A case study in the central area of Beijing[J]. ISPRS International Journal of Geo-information, 6, 128(2017).
[17] et alEstimating hourly population distribution change at high spatiotemporal resolution in urban areas using geo-tagged tweets, land use data, dasymetric maps[J]. arXiv preprint arXiv: 1810.06554(2018).
[18] et alDynamic population mapping using mobile phone data[J]. Proceedings of the National Academy of Sciences, 111, 15888-15893(2014).
[19] et alMapping hourly dynamics of urban population using trajectories reconstructed from mobile phone records[J]. Transactions in GIS, 22, 494-513(2018).
[20] et alEstimation of static and dynamic urban populations with mobile network metadata[J]. IEEE Transactions on Mobile Computing, 18, 2034-2047(2018).
[21] et alA Bimodal Model to Estimate Dynamic Metropolitan Population by Mobile Phone Data[J]. Sensors, 18, 3431(2018).
[22] et alPopulation estimation from mobile network traffic metadata[C]. 2016 IEEE 17th international symposium on a world of wireless, mobile and multimedia networks (WOWMOM). IEEE, 1-9(2016).
[23] et alDeepDPM: Dynamic Population Mapping via Deep Neural Network[C]. Proceedings of the AAAI Conference on Artificial Intelligence, 33, 1294-1301(2019).
[24] et alFine-grained prediction of urban population using mobile phone location data[J]. International Journal of Geographical Information Science, 32, 1770-1786(2018).
[25] et alDownscaling census data for gridded population mapping with geographically weighted area-to-point regression Kriging[J]. IEEE Access, 7, 149132-149141(2019).
[26] et alAre all cities with similar urban form or not? Redefining cities with ubiquitous points of interest and evaluating them with indicators at city and block levels in China[J]. International Journal of Geographical Information Science, 32, 2447-2476(2018).
[27] 40-Year (1978-2017) human settlement changes in China reflected by impervious surfaces from satellite remote sensing[J]. Science Bulletin, 64, 756-763(2019).
[28] et alAn estimate of rural exodus in China using location-aware data[J]. PLoS one, 13, e0201458(2018).