{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T02:10:05Z","timestamp":1789006205339,"version":"build-2803163510"},"reference-count":63,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2017,4,26]],"date-time":"2017-04-26T00:00:00Z","timestamp":1493164800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>The accurate estimation of the dynamic changes in population is a key component in effective urban planning and emergency management. We developed a model to estimate hourly dynamic changes in population at the community level based on subway smart card data. The hourly population of each community in six central districts of Beijing was calculated, followed by a study of the spatiotemporal patterns and diurnal dynamic changes of population and an exploration of the main sources and sinks of the observed human mobility. The maximum daytime population of the six central districts of Beijing was approximately 0.7 million larger than the night-time population. The administrative and commercial districts of Dongcheng and Xicheng had high values of population ratio of day to night of 1.35 and 1.22, respectively, whereas Shijingshan, a residential district, had the lowest value of 0.84. Areas with a high population ratio were mainly concentrated in Dongcheng, Xicheng, West Chaoyang, and Southeast Haidian. The daytime population distribution showed a hierarchical spatial pattern of planar centers and second scattered centers as opposed to multiple scattered centers during the night-time. This was because most people moved inward from the areas with a low\u2013high to high\u2013low population ratio of day to night from night-time to daytime, which can be explained by the process of commuting between residential areas and workplaces. Several distinctive phenomena (e.g., the distribution of new industrial parks, the so-called old residential areas, and colleges and universities) in the development of China are reflected by the spatiotemporal pattern of the distribution of population. The general consistency of the population ratios of day to night, population distribution, population variation of typical communities, and population mobility pattern with previous research suggests that the subway smart card data has potential in analyzing dynamic diurnal variations of urban population. This method can be easily duplicated to calculate hourly dynamic changes in population at the community level. These results can be used to estimate the potential hourly number of evacuees under different temporal scenarios of disasters and to support future urban planning in Beijing.<\/jats:p>","DOI":"10.3390\/ijgi6050128","type":"journal-article","created":{"date-parts":[[2017,4,26]],"date-time":"2017-04-26T13:42:06Z","timestamp":1493214126000},"page":"128","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":48,"title":["Modeling the Hourly Distribution of Population at a High Spatiotemporal Resolution Using Subway Smart Card Data: A Case Study in the Central Area of Beijing"],"prefix":"10.3390","volume":"6","author":[{"given":"Yunjia","family":"Ma","sequence":"first","affiliation":[{"name":"Key Laboratory of Environmental Change and Natural Disaster of Ministry of Education, Beijing Normal University, Beijing 100875, China"},{"name":"Academy of Disaster Reduction and Emergency Management, Ministry of Civil Affairs &amp; Ministry of Education, Beijing Normal University, Beijing 100875, China"},{"name":"Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Xu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Environmental Change and Natural Disaster of Ministry of Education, Beijing Normal University, Beijing 100875, China"},{"name":"Academy of Disaster Reduction and Emergency Management, Ministry of Civil Affairs &amp; Ministry of Education, Beijing Normal University, Beijing 100875, China"},{"name":"Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiujuan","family":"Zhao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Environmental Change and Natural Disaster of Ministry of Education, Beijing Normal University, Beijing 100875, China"},{"name":"Academy of Disaster Reduction and Emergency Management, Ministry of Civil Affairs &amp; Ministry of Education, Beijing Normal University, Beijing 100875, China"},{"name":"Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ying","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Environmental Change and Natural Disaster of Ministry of Education, Beijing Normal University, Beijing 100875, China"},{"name":"Academy of Disaster Reduction and Emergency Management, Ministry of Civil Affairs &amp; Ministry of Education, Beijing Normal University, Beijing 100875, China"},{"name":"Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2017,4,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"779","DOI":"10.1038\/nature06958","article-title":"Understanding individual human mobility patterns","volume":"453","author":"Gonzalez","year":"2008","journal-title":"Nature"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1007\/s10708-007-9105-9","article-title":"LandScan USA: A high-resolution geospatial and temporal modeling approach for population distribution and dynamics","volume":"69","author":"Bhaduri","year":"2007","journal-title":"GeoJournal"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Yu, C., and Chang, H. (2009, January 1\u20134). Personalized location-based recommendation services for tour planning in mobile tourism applications. Proceedings of the International Conference on Electronic Commerce and Web Technologies, Linz, Austria.","DOI":"10.1007\/978-3-642-03964-5_5"},{"key":"ref_4","unstructured":"McPherson, T.N., and Brown, M. (2004, January 10\u201312). Estimating daytime and nighttime population distributions in US cities for emergency response activities. Proceedings of the Symposium on Planning, Nowcasting, and Forecasting in the Urban Zone, Seattle, WA, USA."},{"key":"ref_5","first-page":"48","article-title":"Introducing a temporal component in spatial vulnerability analysis","volume":"5","author":"Aubrecht","year":"2012","journal-title":"Disaster Adv."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1038\/nature02541","article-title":"Modelling disease outbreaks in realistic urban social networks","volume":"429","author":"Eubank","year":"2004","journal-title":"Nature"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1016\/j.atmosenv.2016.02.011","article-title":"A dynamic urban air pollution population exposure assessment study using model and population density data derived by mobile phone traffic","volume":"131","author":"Gariazzo","year":"2016","journal-title":"Atmos. Environ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1086\/217913","article-title":"Urbanism as a way of life","volume":"44","author":"Wirth","year":"1938","journal-title":"Am. J. Soc."},{"key":"ref_9","unstructured":"Breese, G.W. (1949). The Daytime Population of the Central Business District of Chicago: With Particular Reference to the Factor of Transportation, University of Chicago Press."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"827","DOI":"10.2307\/2086635","article-title":"The daytime population of the central business district of Chicago","volume":"15","author":"Quinn","year":"1950","journal-title":"Am. Soc. Rev."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"538","DOI":"10.2307\/2088219","article-title":"The daily movement of population into central business districts","volume":"17","author":"Foley","year":"1952","journal-title":"Am. Soc. Rev."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"323","DOI":"10.2307\/2574113","article-title":"Urban daytime population: A field for demographic-ecological analysis","volume":"32","author":"Foley","year":"1954","journal-title":"Soc. Forces"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/BF01580360","article-title":"The urban household pattern of daytime population change","volume":"29","author":"Akkerman","year":"1995","journal-title":"Ann. Reg. Sci."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1080\/0308106042000263078","article-title":"The origin-destination matrix as an indicator of intrahousehold travel allocation","volume":"27","author":"Akkerman","year":"2004","journal-title":"Transp. Plan Techn."},{"key":"ref_15","first-page":"25","article-title":"Estimating the daytime population with the urban transportation planning package","volume":"981","author":"Fulton","year":"1984","journal-title":"Transp. Res. Rec."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"102","DOI":"10.3141\/1625-13","article-title":"Construction of daytime activity profiles from household travel survey data","volume":"1625","author":"Roddis","year":"1998","journal-title":"Transp. Res. Rec. J. Transp. Res. Board"},{"key":"ref_17","unstructured":"(2016, March 22). Statistics Bureau Home Page\/Daytime Population, Available online: http:\/\/www.stat.go.jp\/english\/data\/kokusei\/2000\/jutsu1\/00\/01.htm."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Bhaduri, B. (2008). Population Distribution during the Day, Springer.","DOI":"10.1007\/978-0-387-35973-1_1005"},{"key":"ref_19","first-page":"49","article-title":"The regional structure of Beijing","volume":"5","author":"Huang","year":"2003","journal-title":"Chin. J. Popul. Sci."},{"key":"ref_20","unstructured":"Langford, M., and Harvey, J.T. (2001, January 8\u20139). The use of remotely sensed data for spatial disaggregation of published census population counts. Proceedings of the IEEE\/ISPRS Joint Workshop on Remote Sensing and Data Fusion over Urban Areas, Roma, Italy."},{"key":"ref_21","first-page":"1181","article-title":"Population estimation models based on individual TM pixels","volume":"68","author":"Harvey","year":"2002","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1023\/B:POEN.0000015562.88915.01","article-title":"Numerical simulation of population distribution in China","volume":"25","author":"Yue","year":"2003","journal-title":"Popul. Environ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"461","DOI":"10.1016\/j.ecolmodel.2004.06.042","article-title":"Surface modelling of human population distribution in China","volume":"181","author":"Yue","year":"2005","journal-title":"Ecol. Model"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"756","DOI":"10.1007\/s11442-015-1200-0","article-title":"Modeling the spatial distribution of urban population during the daytime and at night based on land use: A case study in Beijing, China","volume":"25","author":"Qi","year":"2015","journal-title":"J. Geogr. Sci."},{"key":"ref_25","unstructured":"Sleeter, R., and Wood, N. (2006, January 26\u201329). Estimating daytime and nighttime population density for coastal communities in Oregon. Proceedings of the Urban and Regional Information Systems Association Annual Conference, Vancouver, BC, Canada."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"547","DOI":"10.1016\/j.futures.2004.10.012","article-title":"Location based services\u2014New challenges for planning and public administration?","volume":"37","author":"Ahas","year":"2005","journal-title":"Futures"},{"key":"ref_27","first-page":"443","article-title":"Fine grid dynamic features of population distribution in Shenzhen","volume":"65","author":"Mao","year":"2010","journal-title":"Acta Geogr. Sin."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1376","DOI":"10.1038\/srep01376","article-title":"Unique in the crowd: The privacy bounds of human mobility","volume":"3","author":"Hidalgo","year":"2013","journal-title":"Sci. Rep."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Wesolowski, A., Buckee, C.O., Pindolia, D.K., Eagle, N., Smith, D.L., Garcia, A.J., and Tatem, A.J. (2013). The use of census migration data to approximate human movement patterns across temporal scales. PLoS ONE, 8.","DOI":"10.1371\/journal.pone.0052971"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Yang, X., Fang, Z., Xu, Y., Shaw, S., Zhao, Z., Yin, L., Zhang, T., and Lin, Y. (2016). Understanding spatiotemporal patterns of human convergence and divergence using mobile phone location data. ISPRS Int. J. Geoinf., 5.","DOI":"10.3390\/ijgi5100177"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Lu, S., Fang, Z., Zhang, X., Shaw, S., Yin, L., Zhao, Z., and Yang, X. (2017). Understanding the representativeness of mobile phone location data in characterizing human mobility indicators. ISPRS Int. J. Geoinf., 6.","DOI":"10.3390\/ijgi6010007"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Yuan, J., Zheng, Y., and Xie, X. (2012, January 12\u201316). Discovering regions of different functions in a city using human mobility and POIs. Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, New York, NY, USA.","DOI":"10.1145\/2339530.2339561"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1016\/j.physa.2015.06.032","article-title":"Uncovering urban human mobility from large scale taxi GPS data","volume":"438","author":"Tang","year":"2015","journal-title":"Phys. Stat. Mech. Appl."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Vazquez-Prokopec, G.M., Bisanzio, D., Stoddard, S.T., Paz-Soldan, V., Morrison, A.C., Elder, J.P., Ramirez-Paredes, J., Halsey, E.S., Kochel, T.J., and Scott, T.W. (2013). Using GPS technology to quantify human mobility, dynamic contacts and infectious disease dynamics in a resource-poor urban environment. PLoS ONE, 8.","DOI":"10.1371\/journal.pone.0058802"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Zhang, F., Zhu, X., Guo, W., Ye, X., Hu, T., and Huang, L. (2016). Analyzing urban human mobility patterns through a thematic model at a finer scale. ISPRS Int. J. Geoinf., 5.","DOI":"10.3390\/ijgi5060078"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Lenormand, M., Louail, T., Cant\u00fa-Ros, O.G., Picornell, M., Herranz, R., Arias, J.M., Barthelemy, M., Miguel, M.S., and Ramasco, J.J. (2015). Corrigendum: Influence of sociodemographic characteristics on human mobility. Sci. Rep., 5.","DOI":"10.1038\/srep12188"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Sobolevsky, S., Sitko, I., Tachet Des Combes, R., Hawelka, B., Murillo Arias, J., and Ratti, C. (July, January 27). Money on the move: Big data of bank card transactions as the new proxy for human mobility patterns and regional delineation. The case of residents and foreign visitors in spain. Proceedings of the 2014 IEEE International Congress on Big Data, Anchorage, AK, USA.","DOI":"10.1109\/BigData.Congress.2014.28"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"304","DOI":"10.1007\/s10955-012-0645-0","article-title":"Spatiotemporal patterns of urban human mobility","volume":"151","author":"Hasan","year":"2013","journal-title":"J. Stat. Phys."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Roth, C., Kang, S.M., Batty, M., and Barth\u00e9lemy, M. (2011). Structure of urban movements: Polycentric activity and entangled hierarchical flows. PLoS ONE, 6.","DOI":"10.1371\/journal.pone.0015923"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1016\/j.compenvurbsys.2017.02.003","article-title":"Exploring the spatiotemporal structure of dynamic urban space using metro smart card records","volume":"64","author":"Gong","year":"2017","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.compenvurbsys.2015.05.003","article-title":"Where is also about time: A location-distortion model to improve reverse geocoding using behavior-driven temporal semantic signatures","volume":"54","author":"McKenzie","year":"2015","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"336","DOI":"10.1016\/j.compenvurbsys.2015.10.002","article-title":"How where is when? On the regional variability and resolution of geosocial temporal signatures for points of interest","volume":"54","author":"McKenzie","year":"2015","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Wu, L., Zhi, Y., Sui, Z., and Liu, Y. (2014). Intra-urban human mobility and activity transition: Evidence from social media check-in data. PLoS ONE, 9.","DOI":"10.1371\/journal.pone.0097010"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Jurdak, R., Zhao, K., Liu, J., AbouJaoude, M., Cameron, M., and Newth, D. (2015). Understanding human mobility from Twitter. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0131469"},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Yin, J., and Du, Z. (2016). Exploring multi-scale spatiotemporal twitter user mobility patterns with a visual-analytics approach. ISPRS Int. J. Geoinf., 5.","DOI":"10.3390\/ijgi5100187"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Li, Y., Li, Q., and Shan, J. (2017). Discover patterns and mobility of Twitter users\u2014A study of four US college cities. ISPRS Int. J. Geoinf., 6.","DOI":"10.3390\/ijgi6020042"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.apgeog.2016.03.001","article-title":"Explore spatiotemporal and demographic characteristics of human mobility via Twitter: A case study of Chicago","volume":"70","author":"Luo","year":"2015","journal-title":"Appl. Geogr."},{"key":"ref_48","first-page":"81","article-title":"Exploring millions of footprints in location sharing services","volume":"2011","author":"Cheng","year":"2011","journal-title":"ICWSM"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1080\/15230406.2013.777139","article-title":"Spatial, temporal, and socioeconomic patterns in the use of Twitter and Flickr. Cartogr","volume":"40","author":"Li","year":"2013","journal-title":"Geogr. Inf. Sci."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Arai, A., Fan, Z., Matekenya, D., and Shibasaki, R. (2016). Comparative perspective of human behavior patterns to uncover ownership bias among mobile phone users. ISPRS Int. J. Geoinf., 5.","DOI":"10.3390\/ijgi5060085"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1080\/10630732.2012.715479","article-title":"Towards estimating urban population distributions from mobile call data","volume":"19","author":"Kang","year":"2012","journal-title":"J. Urban Technol."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Wesolowski, A., Eagle, N., Noor, A.M., Snow, R.W., and Buckee, C.O. (2012). Heterogeneous mobile phone ownership and usage patterns in Kenya. PLoS ONE, 7.","DOI":"10.1371\/journal.pone.0035319"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"20120986","DOI":"10.1098\/rsif.2012.0986","article-title":"The impact of biases in mobile phone ownership on estimates of human mobility","volume":"10","author":"Wesolowski","year":"2013","journal-title":"J. R. Soc. Interf."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"15888","DOI":"10.1073\/pnas.1408439111","article-title":"Dynamic population mapping using mobile phone data","volume":"111","author":"Deville","year":"2014","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_55","unstructured":"(2016, April 17). The Traffic Trip Proporion of Public Transportation of Beijing in 2013. Available online: http:\/\/www.baogaochina.com\/News\/2014\u201302\/2013NianBeiJingDeGongGongJiaoTon.html."},{"key":"ref_56","unstructured":"(2016, April 06). Beihang Interest Group on SmartCity (BIGSCity). Available online: http:\/\/www.smartcity-buaa.org\/."},{"key":"ref_57","unstructured":"(2016, May 24). Mapinfo Daytime Population Canada. Available online: http:\/\/www.pitneybowes.com\/us\/location-intelligence\/gis-data-sets\/daytime-population-canada.html."},{"key":"ref_58","first-page":"116","article-title":"An estimate of the day-time population of London","volume":"38","author":"Menzler","year":"1952","journal-title":"J. Town Plan. Inst."},{"key":"ref_59","first-page":"19","article-title":"Population redistribution in the context of urbanization in Beijing since 1980s","volume":"29","author":"Huang","year":"2005","journal-title":"Popul. Res."},{"key":"ref_60","unstructured":"Kang, W. (2006). On the Character of Downtown Daytime Population and Its\u2019 Impacts on Regional Development: A Case Study in Luwan District, Shanghai, East China Normal University."},{"key":"ref_61","first-page":"1339","article-title":"Identifying commuting pattern of Beijing using bus smart card data","volume":"67","author":"Long","year":"2012","journal-title":"Acta Geogr. Sin."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"1936","DOI":"10.3390\/ijgi4041936","article-title":"Reviews of geospatial information technology and collaborative data delivery for disaster risk management","volume":"4","author":"Miyazaki","year":"2015","journal-title":"ISPRS Int. J. Geoinf."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"3533","DOI":"10.5194\/nhess-12-3533-2012","article-title":"Integratig population dynamics into mapping human exposure to seismic hazard","volume":"12","author":"Freire","year":"2012","journal-title":"Nat. Hazards Earth Sys. Sci."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/6\/5\/128\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T18:33:53Z","timestamp":1760207633000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/6\/5\/128"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,4,26]]},"references-count":63,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2017,5]]}},"alternative-id":["ijgi6050128"],"URL":"https:\/\/doi.org\/10.3390\/ijgi6050128","relation":{},"ISSN":["2220-9964"],"issn-type":[{"value":"2220-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,4,26]]}}}