Dasymetric Population Mapping Using Building Data

References

• Bai, Z., J. Wang, M. Wang, M. Gao, and J. Sun. 2018. Accuracy assessment of multi-source gridded population distribution datasets in China. Sustainability 10 (5):1363. doi:10.3390/su10051363.
   Web of Science ®Google Scholar
• Bajat, B., N. Krunić, M. Samardžić Petrović, and M. Kilibarda. 2013. Dasymetric modeling of population dynamics in urban areas. Geodetski Vestnik 57 (4):777–92. doi:10.15292/geodetski-vestnik.2013.04.777-792.
   Web of Science ®Google Scholar
• Bao, W., A. Gong, T. Zhang, Y. Zhao, B. Li, and S. Chen. 2023. Mapping population distribution with high spatiotemporal resolution in Beijing using Baidu heat map data. Remote Sensing 15 (2):458. doi:10.3390/rs15020458.
   Web of Science ®Google Scholar
• Barrozo, L. V., R. P. Pérez-Machado, C. Small, and W. Cabral-Miranda. 2016. Changing spatial perception: Dasymetric mapping to improve analysis of health outcomes in a megacity. Journal of Maps 12 (5):1242–47. doi:10.1080/17445647.2015.1101403.
   Web of Science ®Google Scholar
• BDOT10k. 2012. (Topographic Objects Database), Head Office of Geodesy and Cartography. Accessed April 14, 2023. https://www.geoportal.gov.pl/dane/baza-danych-obiektow-topograficznych-bdot.
   Google Scholar
• Bian, R., and C. G. Wilmot. 2017. An analysis on transit pick-up points for vulnerable people during hurricane evacuation: A case study of New Orleans. International Journal of Disaster Risk Reduction 31:1143–51. doi:10.1016/j.ijdrr.2017.07.005.
   Web of Science ®Google Scholar
• Bielecka, E. 2005. A dasymetric population density map of Poland. Paper presented at Materiały XXII Międzynarodowego Kongresu Kartograficznego, La Coruna, Spain, July 11–16.
   Google Scholar
• Bielecka, E. 2015. Geographical data sets fitness of use evaluation. Geodetski Vestnik 59 (2):335–48. doi:10.15292/geodetskivestnik.2015.02.335-34.
   Web of Science ®Google Scholar
• Bielecka, E., A. Kuczyk, and E. Witkowska. 2005. Modelowanie powierzchni statystycznej przedstawiającej gęstość zaludnienia w Polsce przy pomocy metody dozymetrycznej [Modeling a statistical plot representing population density in Poland using the dasymetric method]. Roczniki Geomatyki 3 (2):9–16.
   Google Scholar
• Calka, B., and E. Bielecka. 2019. Reliability analysis of LandScan gridded population data: The case study of Poland. ISPRS International Journal of Geo-Information 8 (5):222. doi:10.3390/ijgi8050222.
   Web of Science ®Google Scholar
• Calka, B., E. Bielecka, and K. Zdunkiewicz. 2016. Redistribution population data across a regular spatial grid according to buildings characteristics. Geodesy and Cartography 65 (2):149–62. doi:10.1515/geocart-2016-0011.
   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):1440–55. doi:10.1080/19475705.2017.1345792.
   Web of Science ®Google Scholar
• Center for International Earth Science Information Network, Columbia University. 2018. Gridded population of the world, version 4.11 (GPWv4): Population count, revision 11. Palisades, NY: NASA Socioeconomic Data and Applications Center. doi:10.7927/H4JW8BX5.
   Google Scholar
• CLC2012. 2012. Instytut Geodezji i Kartografii [Institute of Geodesy and Cartography], Główny Inspektorat Ochrony Środowiska [Chief Inspectorate for Environmental Protection]. Accessed April 14, 2023. https://clc.gios.gov.pl/index.php/clc-2012/udostepnianie.
   Google Scholar
• Cockx, K., and F. Canters. 2015. Incorporating spatial non-stationarity to improve dasymetric mapping of population. Applied Geography 63:220–30. doi:10.1016/j.apgeog.2015.07.002.
   Web of Science ®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. Proceedings of the National Academy of Sciences of the United States of America 111 (45):15888–93. doi:10.1073/pnas.1408439111.
   PubMed Web of Science ®Google Scholar
• Eicher, C. L., and C. A. Brewer. 2001. Dasymetric mapping and areal interpolation: Implementation and evaluation. Cartography and Geographic Information Science 28 (2):125–38. doi:10.1559/152304001782173727.
   Google Scholar
• Estonian National Topographic Database. 2006. Tallinn: Estonian Land Board.
   Google Scholar
• Everitt, B. S., and A. Skrondal. 2010. The Cambridge dictionary of statistics. Cambridge, UK: Cambridge University Press.
   Google Scholar
• Freire, S., A. Florczyk, and S. Ferri. 2015. Modeling day- and nighttime population exposure at high resolution: Application to volcanic risk assessment in Campi Flegrei. Paper presented at ISCRAM 2015, Kristiansand, Norway, 25-27 May.
   Google Scholar
• Fricker, T., J. B. Elsner, and T. H. Jagger. 2017. Population and energy elasticity of tornado casualties. Geophysical Research Letters 44 (8):3941–49. doi:10.1002/2017GL073093.
   Web of Science ®Google Scholar
• Gallego, F. J., and S. Peedell. 2001. Using CORINE Land Cover to map population density: Towards agri-environmental indicators. EEA Topic Report 6:94–105.
   Google Scholar
• Hamza, M. H., A. S. Al-Thubaiti, M. Dhieb, A. Bel Haj Ali, M. S. Garbouj, and M. Ajmi. 2016. Dasymetric mapping as a tool to assess the spatial distribution of population in Jeddah City (Kingdom of Saudi Arabia). Current Urban Studies 4 (3):329–42. doi:10.4236/cus.2016.43022.
   Google Scholar
• Harvey, J. 2002. Estimating census district populations from satellite imagery: Some approaches and limitation. International Journal of Remote Sensing 23 (10):2071–95. doi:10.1080/01431160110075901.
   Web of Science ®Google Scholar
• Horanont, T., and R. Shibasaki. 2010. Estimate ambient population density: Discovering the current flow of the city. https://www.academia.edu/2004297/ estimate_ambient_population_density_discovering_the_current_flow_of_the_city.
   Google Scholar
• Hościło, A., and M. Tomaszewska. 2014. CORINE Land Cover 2012 - 4th CLC inventory completed in Poland. Geoinformation Issues 6 (1):49–58.
   Google Scholar
• Kang, J., M. Körner, Y. Wang, H. Taubenböck, and X. X. Zhu. 2018. Building instance classification using street view images. ISPRS Journal of Photogrammetry and Remote Sensing 145:44–59. doi:10.1016/j.isprsjprs.2018.02.006.
   Web of Science ®Google Scholar
• Kotz, S., C. B. Read, N. Balakrishnan, and B. Vidakovic, eds. 2006. Encyclopedia of statistical sciences. Hoboken, NJ: Wiley.
   Google Scholar
• Kunze, C., and R. Hecht. 2015. Semantic enrichment of building data with volunteered geographic information to improve mappings of dwelling units and population. Computers, Environment and Urban Systems 53:4–18. doi:10.1016/j.compenvurbsys.2015.04.002.
   Web of Science ®Google Scholar
• LandScan Global Population Database, high-resolution population distribution data. 2023. EastView. Accessed April 14, 2023. https://www.eastview.com/resources/e-collections/landscan/.
   Google Scholar
• Leyk, S., A. E. Gaughan, S. B. Adamo, A. de Sherbinin, D. Balk, S. Freire, A. Rose, F. R. Stevens, B. Blankespoor, C. Frye, et al. 2019. The spatial allocation of population: A review of large-scale gridded population data products and their fitness for use. Earth System Science Data 11 (3):1385–1409. doi:10.5194/essd-11-1385-2019.
   Web of Science ®Google Scholar
• Lin, J., and R. G. Cromley. 2015. Evaluating geo-located Twitter data as a control layer for areal interpolation of population. Applied Geography 58:41–47. doi:10.1016/j.apgeog.2015.01.006.
   Web of Science ®Google Scholar
• Liu, L., Z. Peng, H. Wu, H. Jiao, and Y. Yu. 2018. Exploring urban spatial feature with dasymetric mapping based on mobile phone data and LUR-2SFCAe method. Sustainability 10 (7):2432. doi:10.3390/su10072432.
   Web of Science ®Google Scholar
• Liu, X. 2005. Uncertainty assessment in dasymmetric mapping. Paper presented at ICC2005: International Cartographic Conference, La Coruña, Spain, July 9–16.
   Google Scholar
• Local Data Bank (LDB), Statistics Poland (GUS). 2023. Accessed April 14. https://bdl.stat.gov.pl/bdl/start.
   Google Scholar
• Lwin, K., and Y. Murayama. 2009. A GIS approach to estimation of building population for micro-spatial analysis. Transactions in GIS 13 (4):401–14. doi:10.1111/j.1467-9671.2009.01171.x.
   Web of Science ®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. doi:10.3390/ijgi6050128.
   Web of Science ®Google Scholar
• MAPE. 2023. Working with planning. Accessed April 14, 2023. https://docs.oracle.com/en/cloud/saas/planning-budgeting-cloud/pfusu/insights_metrics_MAPE.html.
   Google Scholar
• Municipal Spatial Information System (MSIP). 2023. Department of Geodesy, Municipality of Cracow, Poland. Accessed April 14, 2023. https://msip.um.krakow.pl.
   Google Scholar
• Murshed, S. M. 2009. Disaggregation of regional population data for residential hot water demand assessment. Paper presented at 24th ICC/ICA Cartographic Conference, Santiago de Chile, Chile, November 15–21.
   Google Scholar
• Nagle, N. N., B. P. Buttenfield, S. Leyk, and S. Speilman. 2014. Dasymetric modeling and uncertainty. Annals of the Association of American Geographers 104 (1):80–95. doi:10.1080/00045608.2013.843439.
   PubMed Web of Science ®Google Scholar
• National Land Survey of Finland. 2013. National topographic database. Accessed April 14, 2023. https://asiointi.maanmittauslaitos.fi/karttapaikka/tiedostopalvelu?lang=en.
   Google Scholar
• National Population and Housing Census 2012 (NSP2012). 2023. Geostatistics portal, Statistics Poland (GUS). Accessed April 14, 2012. https://geo.stat.gov.pl/start/-/asset_publisher/jNfJiIujcyRp/ content/id/36734.
   Google Scholar
• National Topographic Database. 1995. 1:50 000, map code 31H/12, version 3.10. Natural Resources Canada, Geomatics, Minister of Natural Resources, Ottawa, ON, Canada.
   Google Scholar
• Pajares, E., R. Muñoz Nieto, L. Meng, and G. Wulfhorst. 2021. Population disaggregation on the building level based on outdated census data. ISPRS International Journal of Geo-Information 10 (10):662. doi:10.3390/ijgi10100662.
   Web of Science ®Google Scholar
• Pavía, J. M., and I. Cantarino. 2017. Dasymetric distribution of votes in a dense city. Applied Geography 86:22–31. doi:10.1016/j.apgeog.2017.06.021.
   Web of Science ®Google Scholar
• Pirowski, T., and K. Bartos. 2018. Detailed mapping of the distribution of a city population based on information from the national database on buildings. Geodetski vestnik 62 (3):458–71. doi:10.15292/geodetski-vestnik.2018.03.458-471całka.
   Web of Science ®Google Scholar
• Pirowski, T., and K. Berka. 2019. Analysis of land use and land cover maps suitability for estimating population density in urban areas—Exclusion of the equifinality phenomenon on population maps developed from CLC, UA and OBIA data. Geoinformatica Polonica 18:45–55. doi:10.4467/21995923GP.19.003.10887.
   Google Scholar
• Pirowski, T., and W. Drzewiecki. 2012. Mapa gęstości zaludnienia Krakowa, propozycja metodyki opracowania oraz przykładowe zastosowania [Population density map of Krakow, proposal of the study methodology and example applications]. Roczniki Geomatyki 10 (3):95–106.
   Google Scholar
• Pirowski, T., and J. Pomietłowska. 2017. Distribution of Krakow’s population by dasymetric modeling method using urban atlas and publicly available statistical data. Geomatics and Environmental Engineering 11 (4):83–95. doi:10.7494/geom.2017.11.4.83.
   Google Scholar
• Pirowski, T., and M. Timek. 2019. Analysis of the Usefulness Land Use And Land Cover Maps For Estimating the Population Of Urban Areas – Valorisation of Multi-Variant Population Maps Based On the GUS Kilometre Network. Geoinformatica Polonica 18:57–69. doi:10.4467/21995923GP.19.004.10888.
   Google Scholar
• Ratajski, L. 1989. Metodyka kartografii społeczno-gospodarczej [Methodology of socio-economic cartography]. Warsaw, Poland: PPWK im. E. Romera.
   Google Scholar
• Robinson, A. H., R. D. Sale, and J. L. Morrison. 1988. Podstawy Kartografii. Warsaw, Poland: PWN. (Elements of Cartography). 623 p
   Google Scholar
• Rose, A. N., and N. N. Nagle. 2017. Validation of spatiodemographic estimates produced through data fusion of small area census records and household microdata. Computers, Environment and Urban Systems 63:38–49. doi:10.1016/j.compenvurbsys.2016.07.006.
   Web of Science ®Google Scholar
• Schiavina, M., M. Melchiorri, M. Pesaresi, P. Politis, S. Freire, L. Maffenini, P. Florio, D. Ehrlich, K. Goch, P. Tommasi, et al. 2022. Data package 2022. Luxembourg: Publications Office of the European Union. doi:10.2760/19817.
   Google Scholar
• Schug, F., D. Frantz, S. van der Linden, and P. Hostert. 2021. Gridded population mapping for Germany based on building density, height and type from Earth observation data using census disaggregation and bottom-up estimates. PLoS ONE 16 (3):e0249044. doi:10.1371/journal.pone.0249044.
   PubMed Web of Science ®Google Scholar
• Sims, K., A. Reith, E. Bright, J. Kaufman, J. Pyle, J. Epting, J. Gonzales, D. Adams, E. Powell, M. Urban, et al. 2023. LandScan global 2022 [Data set]. Oak Ridge, TN: Oak Ridge National Laboratory. doi:10.48690/1529167.
   Google Scholar
• Smith, A., A. Newing, N. Quinn, D. Martin, S. Cockings, and J. Neal. 2015. Assessing the impact of seasonal population fluctuation on regional flood risk management. ISPRS International Journal of Geo-Information 4 (3):1118–41. doi:10.3390/ijgi4031118.
   Web of Science ®Google Scholar
• Sridharan, H., and F. Qiu. 2013. A spatially disaggregated areal interpolation model using light detection and ranging-derived building volumes. Geographical Analysis 45 (3):238–58. doi:10.1111/gean.12010.
   Web of Science ®Google Scholar
• StatKrak. 2012. Department of Strategy and City Development, Municipality of Cracow. Accessed April 14, 2023. http://msip2.um.krakow.pl/statkrak/.
   Google Scholar
• Stevens, F. R., A. E. Gaughan, J. J. Nieves, A. King, A. Sorichetta, C. Linard, and A. J. Tatem. 2020. Comparisons of two global built area land cover datasets in methods to disaggregate human population in eleven countries from the Global South. International Journal of Digital Earth 13 (1):78–100. doi:10.1080/17538947.2019.1633424.
   Web of Science ®Google Scholar
• Stofan, K. 2008. Estimating Pashtun sub-tribal populations in Mizan District, Zabul Province, Afghanistan using Quickbird satellite imagery and dasymetric mapping. Geographic Information Systems for the Geospatial Intelligence Professional Summer, Capstone Project, Hohenfels, Germany.
   Google Scholar
• Su, M. D., M. C. Lin, H. I. Hsieh, B. W. Tsai, and C. H. Lin. 2010. Multi-layer multi-class dasymetric mapping to estimate population distribution. The Science of the Total Environment 408 (20):4807–16. doi:10.1016/j.scitotenv.2010.06.032.
   PubMed Web of Science ®Google Scholar
• Swamidass, P. M., ed. 2000. Encyclopedia of production and manufacturing management. Boston: Springer.
   Google Scholar
• Swanwick, R. H., Q. D. Read, S. M. Guinn, M. A. Williamson, K. L. Hondula, and A. J. Elmore. 2022. Dasymetric population mapping based on US census data and 30-m gridded estimates of impervious surface. Scientific Data 9 (1):523. doi:10.1038/s41597-022-01603-z.
   PubMed Web of Science ®Google Scholar
• Tapp, A. 2010. Areal interpolation and dasymetric mapping methods using local ancillary data sources. Cartography and Geographic Information Science 37 (3):215–28. doi:10.1559/152304010792194976.
   Web of Science ®Google Scholar
• Tenerelli, P., J. F. Gallego, and D. Ehrlich. 2015. Population density modelling in support of disaster risk assessment. International Journal of Disaster Risk Reduction 13:334–41. doi:10.1016/j.ijdrr.2015.07.015.
   Web of Science ®Google Scholar
• Tobler, R. T. 1979. Smooth pycnophylactic interpolation for geographic regions. Journal of the American Statistical Association 74 (367):519–30. doi:10.1080/01621459.1979.10481647.
   PubMed Web of Science ®Google Scholar
• Tomás, L., L. Fonseca, C. Almeida, F. Leonardi, and M. Pereira. 2016. Urban population estimation based on residential buildings volume using IKONOS-2 images and LiDAR data. International Journal of Remote Sensing 37 (Suppl. 1):1–28. doi:10.1080/01431161.2015.1121301.
   Google Scholar
• Upegui, E., and J. F. Viel. 2012. GeoEye imagery and Lidar technology for small-area population estimation: An epidemiological viewpoint. Photogrammetric Engineering & Remote Sensing 78 (7):693–702. doi:10.14358/PERS.78.7.693.
   Web of Science ®Google Scholar
• Urban Atlas LCLU. (2012). Denmark: European Environment Agency. doi:10.2909/debc1869-a4a2-4611-ae95-daeefce23490.
   Google Scholar
• Weber, E. M., V. Y. Seaman, R. N. Stewart, T. J. Bird, A. J. Tatem, J. J. McKee, B. L. Bhaduri, J. J. Moehl, and A. E. Reith. 2018. Census-independent population mapping in northern Nigeria. Remote Sensing of Environment 204:786–98. doi:10.1016/j.rse.2017.09.024.
   PubMed Web of Science ®Google Scholar
• Wei, C., and T. Blaschke. 2018. Pixel-wise vs. object-based impervious surface analysis from remote sensing: Correlations with land surface temperature and population density. Urban Science 2 (1):2. doi:10.3390/urbansci2010002.
   Google Scholar
• Xie, Y., A. Weng, and Q. Weng. 2015. Population estimation of urban residential communities using remotely sensed morphologic data. IEEE Geoscience and Remote Sensing Letters 12 (5):1111–15. doi:10.1109/LGRS.2014.2385597.
   Web of Science ®Google Scholar
• Xie, Z. 2006. A framework for interpolating the population surface at the residential-housing-unit level. GIScience & Remote Sensing 43 (3):233–51. doi:10.2747/1548-1603.43.3.233.
   Web of Science ®Google Scholar
• Ye, T., N. Zhao, X. Yang, Z. Ouyang, X. Liu, Q. Chen, K. Hu, W. Yue, J. Qi, Z. Li, et al. 2019. Improved population mapping for China using remotely sensed and points-of-interest data within a random forests model. The Science of the Total Environment 658:936–46. doi:10.1016/j.scitotenv.2018.12.276.
   PubMed Web of Science ®Google Scholar
• Zandbergen, P. A., and D. A. Ignizio. 2010. Comparison of dasymetric mapping techniques for small-area population estimates. Cartography and Geographic Information Science 37 (3):199–214. doi:10.1559/152304010792194985.
   Web of Science ®Google Scholar
• Żukowska, M. 2005. Wybrane metody tematycznej wizualizacji kartograficznej [Selected methods of thematic cartographic visualization]. Geodezja 11 (2):271–79.
   Google Scholar