Construction of a refined population analysis unit based on urban forms and population aggregation patterns

References

• Bai, Zhongqiang, Juanle Wang, Mingming Wang, Mengxu Gao, and Jiulin Sun. 2018. “Accuracy Assessment of Multi-Source Gridded Population Distribution Datasets in China.” Sustainability 10 (5): 1363–1378. doi:10.3390/su10051363.
   Web of Science ®Google Scholar
• Bakillah, M., S. Liang, A. Mobasheri, J. Arsanjani, and A. Zipf. 2014. “Fine-resolution Population Mapping Using OpenStreetMap Points-of-Interest.” International Journal of Geographical Information Science 28 (9): 1940–1963. doi:10.1080/13658816.2014.909045.
   Web of Science ®Google Scholar
• Bertsekas, D. P. 1993. “A Simple and Fast Label Correcting Algorithm for Shortest Paths.” Networks 23 (8): 703–709. doi:10.1002/net.3230230808.
   Web of Science ®Google Scholar
• Calka, B., J. Nowak Da Costa, and E. Bielecka. 2017. “Fine Scale Population Density Data and its Application in Risk Assessment.” Geomatics, Natural Hazards and Risk 8 (2): 1440–1455. doi:10.1080/19475705.2017.1345792.
   Web of Science ®Google Scholar
• Chen, Jie, Tao Pei, Shih Lung Shaw, Feng Lu, Mingxiao Li, Shifen Cheng, Xiliang Liu, and Hengcai Zhang. 2018a. “Fine-grained Prediction of Urban Population Using Mobile Phone Location Data.” International Journal of Geographical Information Science 32 (9-10): 1770–1786. doi:10.1080/13658816.2018.1460753.
   Web of Science ®Google Scholar
• Chen, B., Y. M. Song, T. T. Jiang, Z. Chen, B. Huang, and B. Xu. 2018b. “Real-Time Estimation of Population Exposure to PM2.5 Using Mobile- and Station-Based Big Data.” International Journal of Environmental Research & Public Health 15 (4): 573–587. doi:10.3390/ijerph15040573.
   PubMed Web of Science ®Google Scholar
• Cheng, J., J. Liu, and Y. Gao. 2016. “Analyzing the Spatio-Temporal Characteristics of Beijing′s OD Trip Volume Based on Time Series Clustering Method.” Journal of Geo-Information Science 18 (9): 1227–1239.
   Google Scholar
• Chi, J., L. M. Jiao, T. Dong, Y. Y. Gu, and Y. L. Ma. 2016. “Quantitative Identification and Visualization of Urban Functional Area Based on POI Data.” Journal of Geomatics 41 (2): 68–73.
   Google Scholar
• Deville, P., C. Linard, S. Martin, M. Gilbert, F. R. Stevens, A. E. Gaughan, V. D. Blondel, and A. J. Tatem. 2014. “Dynamic Population Mapping Using Mobile Phone Data.” Proceedings of the National Academy of Sciences 111 (45): 15888–15893. doi:10.1073/pnas.1408439111.
   PubMed Web of Science ®Google Scholar
• Dong, G., L. Wolf, A. Alexiou, and D. Arribas-Bel. 2019. “Inferring Neighbourhood Quality with Property Transaction Records by Using a Locally Adaptive Spatial Multi-Level Model.” Computers, Environment and Urban Systems 73: 118–125. doi:10.1016/j.compenvurbsys.2018.09.003.
   Web of Science ®Google Scholar
• Gao, X. L., D. X. Wu, and B. Q. Yan. 2020. “Measure and Distribution of Urban Elderly in Poverty: An Empirical Study in Beijing.” Acta Geographica Sinica 75 (8): 1557–1571. doi:10.11821/DLXB202008001.
   Google Scholar
• Gong, Y. X., Y. Y. Lin, and Z. Y. Duan 2017. “Exploring the Spatiotemporal Structure of Dynamic Urban Space Using Metro Smart Card Records - ScienceDirect.” Computers, Environment and Urban Systems 64: 169–183. doi:10.1016/J.COMPENVURBSYS.2017.02.003.
   Web of Science ®Google Scholar
• Kubíček, P., M. Konečný, Z. Stachoň, J. Shen, L. Herman, Tomáš Řezník, K. Staněk, Radim Štampach, and Šimon Leitgeb. 2019. “Population Distribution Modelling at Fine Spatio-Temporal Scale Based on Mobile Phone Data.” International Journal of Digital Earth 12 (11): 1319–1340. doi:10.1080/17538947.2018.1548654.
   Web of Science ®Google Scholar
• Langford, M. 2006. “Obtaining Population Estimates in non-Census Reporting Zones: An Evaluation of the 3-Class Dasymetric Method.” Computers Environment & Urban Systems 30 (2): 161–180. doi:10.1016/j.compenvurbsys.2004.07.001.
   Web of Science ®Google Scholar
• Li, Z., Q. Huang, and C. Emrich. 2019. “Introduction to Social Sensing and big Data Computing for Disaster Management.” International Journal of Digital Earth 12 (11): 1198–1204. doi:10.1080/17538947.2019.1670951.
   Web of Science ®Google Scholar
• Li, Q., X. Q. Zheng, and Y. Chao. 2020. “Research On Function Identification and Distribution Characteristics of Wuhan Supported by big Data.” Science of Surveying and Mapping 45 (5): 120–125.
   Google Scholar
• Liu, X., Y. Liu, F. Cai, and W. Fan. 2019. “Selection Method for Urban Emergency Medical Institutions Considering Spatiotemporal Accessibility.” Journal of Geo-Information Science 21 (9): 1411–1419.
   Google Scholar
• Lwin, K. K., and Y. Murayama. 2011. “Estimation of Building Population from LIDAR Derived Digital Volume Model.” GeoJournal Library 6: 87–98. doi:10.1007/978-94-007-0671-2_6.
   Google Scholar
• Ma, Y., W. Xu, X. Zhao, and Y. Li. 2017. “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.” ISPRS International Journal of Geo-Information 6 (5): 128–146. doi:10.3390/ijgi6050128.
   Web of Science ®Google Scholar
• Mao, S., L. Jiao, Gang Xu, and Zehui Li. 2019. “Identification of the Polycentric Spatial Structure in Wuhan City Based on Multisource Data.” Progress in Geography 38 (11): 1675–1683. doi:10.18306/dlkxjz.2019.11.003.
   Google Scholar
• Mayaud, J. R., M. Tran, and R. Nuttall. 2019. “An Urban Data Framework for Assessing Equity in Cities: Comparing Accessibility to Healthcare Facilities in Cascadia.” Computers, Environment and Urban Systems 78: 101401–101413. doi:10.1016/j.compenvurbsys.2019.101401.
   Web of Science ®Google Scholar
• Mennis, J. 2009. “Dasymetric Mapping for Estimating Population in Small Areas.” Geography Compass 3 (2): 727–745. doi:10.1111/J.1749-8198.2009.00220.X.
   Google Scholar
• Myers, E. W. 1986. “An O(ND) Difference Algorithm and Its Variations.” Algorithmica 1 (1): 251–266. doi:10.1007/BF01840446.
   Web of Science ®Google Scholar
• Nowak Da Costa, J., B. Calka, and E. Bielecka. 2021. “Urban Population Flood Impact Applied to a Warsaw Scenario.” Resources 10 (6): 62–79. doi:10.3390/resources10060062.
   Google Scholar
• Patel, N. N., F. R. Stevens, Z. Huang, A. E. Gaughan, I. Elyazar, and A. J. Tatem. 2017. “Improving Large Area Population Mapping Using Geotweet Densities.” Transactions in Gis 21 (2): 317–331. doi:10.1111/tgis.12214.
   PubMed Web of Science ®Google Scholar
• Qiu, F., H. Sridharan, and Y. Chun. 2010. “Spatial Autoregressive Model for Population Estimation at the Census Block Level Using LIDAR-Derived Building Volume Information.” American Cartographer 37 (3): 239–257. doi:10.1559/152304010792194949.
   Google Scholar
• Řezník, T., B. Horáková, and R. Szturc. 2015. “Advanced Methods of Cell Phone Localization for Crisis and Emergency Management Applications.” International Journal of Digital Earth 8 (4): 259–272. doi:10.1080/17538947.2013.860197.
   Web of Science ®Google Scholar
• Sinha, P., A. E. Gaughan, F. R. Stevens, J. J. Nieves, A. Sorichetta, and A. J. Tatem. 2019. “Assessing the Spatial Sensitivity of a Random Forest Model: Application in Gridded Population Modeling.” Computers, Environment and Urban Systems 75 (5): 132–145. doi:10.1016/j.compenvurbsys.2019.01.006.
   Google Scholar
• Sun, B., and X. Wei. 2014. “Spatial Distribution and Structure Evolution of Employment and Population in Shanghai Metropolitan Area.” Acta Geographica Sinica 69 (6): 747–758.
   Google Scholar
• Tahmasbi, B., and H. Haghshenas. 2019. “Public Transport Accessibility Measure Based on Weighted Door to Door Travel Time.” Computers, Environment and Urban Systems 76 (7): 163–177. doi:10.1016/j.compenvurbsys.2019.05.002.
   Google Scholar
• Teh, B. T., M. Shinozaki, L. W. Chau, and C. S. Ho. 2019. “Using Building Floor Space for Station Area Population and Employment Estimation.” Urban Science 3 (1): 12–31. doi:10.3390/urbansci3010012.
   Google Scholar
• Ural, S., E. Hussain, and S. Jie. 2011. “Building Population Mapping with Aerial Imagery and GIS Data.” International Journal of Applied Earth Observation & Geoinformation 13 (6): 841–852. doi:10.1016/j.jag.2011.06.004.
   Web of Science ®Google Scholar
• Wang, L., H. Fan, and Y. Wang. 2019. “Fine-Resolution Population Mapping from International Space Station Nighttime Photography and Multisource Social Sensing Data Based on Similarity Matching.” Remote Sensing 11 (16): 1900–1925. doi:10.3390/rs11161900.
   Web of Science ®Google Scholar
• Webster, C. 1996. “Population and Dwelling Unit Estimates from Space.” Third World Planning Review 18 (2): 155–176. doi:10.3828/twpr.18.2.ul31w6q4447g120r.
   PubMedGoogle Scholar
• Wesolowski, A., W. P. O. Meara, A. J. Tatem, S. Ndege, N. Eagle, and C. O. Buckee. 2015. “Quantifying the Impact of Accessibility on Preventive Healthcare in Sub-Saharan Africa Using Mobile Phone Data.” Epidemiology 26 (2): 223–228. doi:10.1097/ede.0000000000000239.
   PubMed Web of Science ®Google Scholar
• Wilson, R., E. Z. Erbach-Schoenberg, M. Albert, D. Power, S. Tudge, M. Gonzalez, S. Guthrie, G. Chamerlain, C. Brooks, and C. Hughes. 2016. “Rapid and Near Real-Time Assessments of Population Displacement Using Mobile Phone Data Following Disasters: The 2015 Nepal Earthquake.” Plos Currents 8: 1–25. doi:10.1371/currents.dis.d073fbece328e4c39087bc086d694b5c.
   Google Scholar
• Wong, D. W. 2009. “Modifiable Areal Unit Problem.” International Encyclopedia of Human Geography 105: 169–174. doi:10.1016/B978-008044910-4.00475-2.
   Google Scholar
• Wu, W. Y., and X. Y. Ma. 2006. “Polycentric Population Density Functions and Modeling:The Case of Shanghai.” Modern Urban Research 12: 39–44.
   Google Scholar
• Xu, Y., S. Jiang, R. Li, J. Zhang, Jinhua Zhao, Sofian Abbar, and M. C. González. 2019. “Unraveling Environmental Justice in Ambient PM2.5 Exposure in Beijing: A big Data Approach.” Computers, Environment and Urban Systems 75: 12–21. doi:10.1016/j.compenvurbsys.2018.12.006.
   Web of Science ®Google Scholar
• Yao, Y., X. Liu, X. Li, J. Zhang, Z. Liang, K. Mai, and Y. Zhang. 2017. “Mapping Fine-Scale Population Distributions at the Building Level by Integrating Multisource Geospatial big Data.” International Journal of Geographical Information Science 31 (5-6): 1220–1244.
   Web of Science ®Google Scholar
• Yao, Y., Y. Zhang, Q. Guan, K. Mai, and U. Kh. 2019. “Sensing Multi-Level Urban Functional Structures by Using Time Series Taxi Trajectory Data.” Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University 44 (6): 875–884.
   Google Scholar
• Ye, T., N. Zhao, X. Yang, Z. Ouyang, X. Liu, Q. Chen, K. Hu, W. Yue, J. Qi, and Z. Li. 2019. “Improved Population Mapping for China Using Remotely Sensed and Points-of-Interest Data Within a Random Forests Model.” Science of The Total Environment 658: 936–946. doi:10.1016/j.scitotenv.2018.12.27.
   PubMed Web of Science ®Google Scholar
• Yuan, J., Y. Zheng, and X. Xie. 2012. “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 - KDD 12: 186–194. doi:10.1145/2339530.2339561.
   Google Scholar
• Zhang, L., T. Ma, Y. Du, P. Tao, and P. Hui. 2018. “Mapping Hourly Dynamics of Urban Population Using Trajectories Reconstructed from Mobile Phone Records.” Transactions in GIS 22 (3): 494–513.
   Google Scholar
• Zhao, W., Q. Li, and B. Li. 2011. “Extracting Hierarchical Landmarks from Urban POI Data.” Journal of Remote Sensing 15 (5): 973–988.
   Google Scholar
• Zhao, Y., Li, and Q., Y. Zhang, and X. Du. 2019. “Improving the Accuracy of Fine-Grained Population Mapping Using Population-Sensitive POIs.” Remote Sensing 11 (21): 2502–2522. doi:10.3390/rs11212502.
   Web of Science ®Google Scholar
• Zhao P, X., and M. Zhao S. 2016. “Understanding Urban Traffic Flow Characteristics from the Network Centrality Perspective at Different Granularities.” International Archives of the Photogrammetry Remote Sensing & Spatial Information Sciences XLI-B XLI-B2: 263–268. doi:10.5194/isprs-archives-XLI-B2-263-2016.
   Google Scholar
• Zheng, Yu. 2015. “Introduction to Urban Computing.” Geomatics and Information Science of Wuhan University 40 (1): 1–13.
   Google Scholar
• Zhu, D., N. Wang, L. Wu, and Y. Liu. 2017. “Street as a big geo-Data Assembly and Analysis Unit in Urban Studies: A Case Study Using Beijing Taxi Data.” Applied Geography 86: 152–164. doi:10.1016/j.apgeog.2017.07.001.
   Web of Science ®Google Scholar
• Zoraghein, H., S. Leyk, M. Ruther, and B. P. Buttenfield. 2016. “Exploiting Temporal Information in Parcel Data to Refine Small Area Population Estimates.” Computers, Environment and Urban Systems 58: 19–28. doi:10.1016/j.compenvurbsys.2016.03.004.
   Web of Science ®Google Scholar
• Zou, Y. J. 2020. “Research on Population Spatialization Based on Multi-Source Data.” China University of Mining and Technology (In Chinese).
   Google Scholar