• Journal of Geo-information Science
  • Vol. 22, Issue 2, 147 (2020)
Zhang LIU1、1、2、2, Jiale QIAN1、1、2、2, Yunyan DU1、1、2、2、*, Nan WANG1、1、2、2, Jiawei YI1、1、2、2, Yeran SUN3、3、4、4, Ting MA1、1、2、2, Tao PEI1、1、2、2, and Chenghu ZHOU1、1、2、2
Author Affiliations
  • 1State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
  • 1中国科学院地理科学与资源研究所 资源与环境信息系统国家重点实验室,北京 100101
  • 2University of Chinese Academy of Sciences, Beijing 100049, China
  • 2中国科学院大学,北京 100049
  • 3School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China
  • 3中山大学地理科学与规划学院,广州 510275
  • 4Department of Geography, Swansea University, Swansea SA28PP, United Kingdom
  • 4斯旺西大学地理系,斯旺西 SA28PP, 英国
  • show less
    DOI: 10.12082/dqxxkx.2020.200045 Cite this Article
    Zhang LIU, Jiale QIAN, Yunyan DU, Nan WANG, Jiawei YI, Yeran SUN, Ting MA, Tao PEI, Chenghu ZHOU. Multi-level Spatial Distribution Estimation Model of the Inter-regional Migrant Population Using Multi-source Spatio-temporal Big Data: A Case Study of Migrants from Wuhan during the Spread of COVID-19[J]. Journal of Geo-information Science, 2020, 22(2): 147 Copy Citation Text show less
    References

    [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).

    [29] 宫礼. 人民网评:疫情防控万万不可忽视农村[EB/OL]. http://opinion.people.com.cn/n1/2020/0124/c1003-31561897.html,2020-01-24. [ GongL. People's Online Review: The epidemic prevention and control must not be ignored in rural areas[EB/OL]. http://opinion.people.com.cn/n1/2020/0124/c1003-31561897.html, 2020-01-24.] [ Gong L. People's Online Review: The epidemic prevention and control must not be ignored in rural areas[EB/OL]. http://opinion.people.com.cn/n1/2020/0124/c1003-31561897.html, 2020-01-24. ] http://opinion.people.com.cn/n1/2020/0124/c1003-31561897.html

    Zhang LIU, Jiale QIAN, Yunyan DU, Nan WANG, Jiawei YI, Yeran SUN, Ting MA, Tao PEI, Chenghu ZHOU. Multi-level Spatial Distribution Estimation Model of the Inter-regional Migrant Population Using Multi-source Spatio-temporal Big Data: A Case Study of Migrants from Wuhan during the Spread of COVID-19[J]. Journal of Geo-information Science, 2020, 22(2): 147
    Download Citation