Abstract
This paper outlines a methodology used to disaggregate a census population in order to more accurately determine the population distribution over a regional area or a state scale. Data regarding population distributions are usually accessible at the level of individual census designation places and are usually mapped as aggregated polygons by the choropleth method with the assumption of a homogeneous distribution of population within a cartographic unit. In contrast, dasymetric mapping provides a more reliable view into the allocation of inhabitants, which can be of significant importance when estimating population distributions. Coupling this methodology with the GIS environment and a free open access database of soil sealing facilitates the acquisition of population surface models for human and urban geography applications.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsNotes
- 1.
- 2.
- 3.
References
Bajat B, Krunić N, Kilibarda M, Samardžić-Petrović M (2011a) Spatial prediction of human population change. In: CD proceedings of 14th AGILE international conference on geographic information science, Utrecht, Netherlands, 18–21 April 2011
Bajat B, Krunić N, Kilibarda M, Samardžić-Petrović M (2011b) Spatial modelling of population concentration using geographically weighted regression method. Zbornik radova Geografskog Instituta ‘‘Jovan Cvijić’’, 61:151–167
Bajat B, Krunić N, Kilibarda M (2011c) Dasymetric mapping of spatial distribution of population in Timok region. In: Proceedings of international scientific conference professional practice and education in geodesy and related fields, Kladovo, Serbia, pp 30–34, 24–26 Jun 2011
Bajat B, Krunić N, Samardžić Petrović M, Kilibarda M (2013) Dasymetric modelling of population dynamics in urban areas. Geodetski Vestnik 57(4):777–792
Balk D, Yetman G (2004) The global distribution of population: evaluating the gains in resolution refinement, documentation for GPWv3. CIESIN, Columbia, Palisades, NY
Bengtsson M, Shen Y, Oki T (2006) A SRES-based gridded global population dataset for 1990–2100. Popul Environ 28(2):113–131
Burghardt W (2006) Soil sealing and soil properties related to sealing. Geol Soc Lond Spec Publ 266:117–124
CIESIN, CIAT (2005). Gridded population of the world, VERSION 3 (GPWv3). In: Socioeconomic data and applications center (SEDAC), Columbia University, Palisades, NY. Available at http://sedac.ciesin.columbia.edu/gpw
Deichmann U, Balk D, Yetman G (2001) Transforming population data for interdisciplinary usages: from census to grid. Available at: http://sedac.ciesin.org/gpw-v2/GPWdocumentation.pdf
DeMers MN (1999) Fundamentals of geographic information systems, 2nd edn. John Wiley, New York
Dobson JE, Bright EA, Coleman PR, Durfee R, Worley BA (2000) Landscan: a global population database for estimating populations at risk. Photogram Eng Rem S 66:849–857
Eicher CL, Brewer CA (2001) Dasymetric mapping and areal interpolation: implementation and evaluation. Cartography Geogr Inf Sci 28:125–138
Gallego FJ (2010) A population density grid of the European Union. Popul Environ 31:460–473
Harvey F (2008) A primer of GIS: fundamental geographic and cartographic concepts. The Guilford Press, New York
Kilibarda M, Bajat B (2012) PlotGoogleMaps: the R-based web-mapping tool for thematic spatial data. Geomatica 66:37–49
Krunić N, Bajat B, Kilibarda M, Tošić D (2011) Modelling the spatial distribution of vojvodina’s population by using dasymetric method. Spatium 24:45–50
Leyk S, Buttenfield BP, Ruther M (2014) Dasymetric refinement for improved temporal small area analysis. In: Extended abstract proceedings of the GIScience 2014, Vienna, Austria, pp 42–46, 23–26 Sept
Maantay JA, Maroko AR, Herrmann C (2007) Mapping population distribution in the urban environment: the cadastral-based expert dasymetric system (CEDS). Cartogr Geogr Inf Sci 34(2):77–102
Mennis J (2003) Generating surface models of population using dasymetric mapping. Prof Geogr 55(1):31–42
Mennis J (2009) Dasymetric mapping for estimating population in small areas. Geogr Compass 3(2):727–745
Nestorov I, Protić D (2009) CORINE land cover mapping in Serbia. Građevinska knjiga, Beograd
ORNL (2003) Integrated analysis of mitigation and adaptation as responses to concerns about impacts of global climate change, ORNL Working paper, June 2003
Statistical Office of the Republic of Serbia (SORS) (2012) Natural changes of population in the Republic of Serbia. Statistical Office of the Republic of Serbia, Belgrade
Tobler WR (1979) Smooth pycnophylactic interpolation for geographical regions. J Am Stat Assoc 74:519–530
Zandbergen PA, Ignizio DA (2010) Comparison of dasymetric mapping techniques for small-area population estimates. Cartogr Geogr Inf Sci 37(3):199–214
Zandbergen PA (2011) Dasymetric mapping using high resolution address point datasets. Trans GIS 15(s1):5–27
Acknowledgments
The paper represents the result of research carried out on projects No. III 47014 “The role and implementation of the National spatial plan and regional development in renewal of strategic research, thinking and governance in Serbia”, TR 36036 “Sustainable spatial development of Danube area in Serbia” and TR 36035 “Spatial, ecological, energy and social aspects of settlements’ development and climate changes—interrelationships” financed by the Ministry of Education and Science of the Republic of Serbia.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Krunić, N., Bajat, B., Kilibarda, M. (2015). Dasymetric Mapping of Population Distribution in Serbia Based on Soil Sealing Degrees Layer. In: Růžičková, K., Inspektor, T. (eds) Surface Models for Geosciences. Lecture Notes in Geoinformation and Cartography. Springer, Cham. https://doi.org/10.1007/978-3-319-18407-4_12
Download citation
DOI: https://doi.org/10.1007/978-3-319-18407-4_12
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-18406-7
Online ISBN: 978-3-319-18407-4
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)