BazEkon - Biblioteka Główna Uniwersytetu Ekonomicznego w Krakowie

BazEkon home page

Meny główne

Bačík Vladimír (University in Bratislava, Slovakia), Klobučník Michal (University in Bratislava, Slovakia)
Population Distribution by Selected Road Network Elements - Comparison of Centroids, Geocoded Addresses, Built-up Areas and Total Areas on the Example of Slovak Communes
Bulletin of Geography. Socio-economic Series, 2015, No. 28, s. 7-20, rys., wykr., bibliogr. 19 poz.
Słowa kluczowe
Ludność, Procesy ludnościowe, Społeczeństwo, Sieć drogowa
Population, Population processes, Society, Road network
Slovak Republic
Two research objectives can be identified in the presented paper. The first one was the development of a point layer, which would abstract from the position of a central point depending on the shape of the territory of the respective spatial unit (commune), and would express the position of a commune as regards the location of the point in the area of the commune built-up area. For such purpose, a geocoding algorithm from Google was used, for which it was possible to prepare a final dot map layer without any terrain layout, as the geocoding algorithm processes only simple text addresses of the relevant spatial units. Such an obtained dot layer was compared with the layer of centroids and the achieved differences were visualised. Another objective was to compare different methods of population distribution interpretation from the selected road network elements at the commune level. Point layers in the form of centroids and geocodes were compared with the spatial population distribution on the basis of the total area and built-up area of a commune. It is more suitable to use geocodes as the holder of statistical information in comparison with commune centroids, in particular in the areas with marked vertical division of the terrain. In assessing population distribution, the obtained values are much closer to the expression of the identical indicator calculated for the built-up area of a commune that we consider most accurate, which is also documented by the average percentage deviations between particular interpretations of population distribution. (original abstract)
Pełny tekst
  1. Davis, C.A. and Alencar, O.R., 2011: Evaluation of the quality of an online geocoding resource in the context of a large Brazilian city. In: Transactions in GIS, Vol. 15, Issue 6, pp. 851-868. DOI: http://dx.doi. org/10.1111/j.1467-9671.2011.01288.x
  2. Doherty, P., Guo, Q., Liu, Y. and Wieczorek, J., 2011: Georeferencing Incidents from Locality Descriptions and its Applications: a Case Study from Yosemite National Park Search and Rescue. In: Transactions in GIS, 15(6), pp. 775-793. DOI: http://dx.doi. org/10.1111/j.1467-9671.2011.01290.x
  3. Duncan, D.T., Castro, M.C., Blossom, J.C., Bennett, G.G. and Gortmaker, S.L., 2011: Evaluation of the positional difference between two common geocoding methods. In: Geospatial Health, Vol. 5, Issue 2, pp. 265-273.
  4. Chi, G., 2010: The Impacts of Highway Expansion on Population Change: An Integrated Spatial Approach. In: Rural Sociology, Vol. 75, Issue 1, pp. 58-89. DOI:
  5. Jacquez, G.M., 2012: A research agenda: Does geocoding positional error matter in health GIS studies? In: Spatial and Spatio-temporal Epidemiology, Vol. 3, Issue 1, pp. 7-16. DOI: sste.2012.02.002
  6. Jenelius, E., 2009: Network structure and travel patterns: explaining the geographical disparities of road network vulnerability. In: Journal of Transport Geography, Vol. 17, Issue 3, pp. 234-244. DOI: http://dx.doi. org/10.1016/j.jtrangeo.2008.06.002
  7. Karimi, H.A., Sharker M.H. and Roongpiboonsopit, D., 2011: Geocoding Recommender: An Algorithm to Recommend Optimal Online Geocoding Services for Applications. In: Transactions in GIS, Vol. 15, Issue 6, pp. 869-886. DOI: j.1467-9671.2011.01293.x
  8. Klobučník, M. and Bačík, V., 2013: Spatial autocorrelation of communes websites: A case study of the region Stredné Považie in Slovak Republic. In: Szymańska, D. and Biegańska, J. editors, Bulletin of Geography. Socio-economic Series, No. 22, Toruń: Nicolaus Copernicus University Press, pp. 65-80. DOI: http://
  9. Kotavaara, O., Antikainen, H. and Rusanen, J., 2011: Population change and accessibility by road and rail networks: GIS and statistical approach to Finland 1970-2007. In: Journal of Transport Geography, Vol. 19, Issue 4, pp. 926-935. DOI: http://dx.doi. org/10.1016/j.jtrangeo.2010.10.013
  10. Liu, Ch. and Yu, R., 2012: Spatial Accessibility of Road Network in Wuhan Metropolitan Area Based on Spatial Syntax. In: Journal of Geographic Information System, Issue 4, pp. 128-135. DOI: http://dx.doi. org/10.4236/jgis.2012.42017
  11. Mclafferty, S., Freeman, V.L., Barrett, R.E., Luo, L. and Shockley, A., 2012: Spatial error in geocoding physician location data from the AMA Physician Masterfile: Implications for spatial accessibility analysis. In: Spatial and Spatio-temporal Epidemiology, Vol. 3, Issue 1, pp. 31-38.
  12. Morency, C., Paez, A., Roorda, M.J., Mercado, R. and Farber, S., 2011: Distance traveled in three Canadian cities: Spatial analysis from the perspective of vulnerable population segments. In: Journal of Transport Geography, Vol. 19, Issue 1, pp. 39-50. DOI: http://dx.
  13. Murray, A.T., Grubesic, T.H., Wei, R. and Mack, E.A., 2011: A Hybrid Geocoding Methodology for Spatio- Temporal Data. In: Transactions in GIS, Vol. 15, Issue 6, pp. 795-809. DOI: j.1467-9671.2011.01289.x
  14. Pantha, B.R., Yatabe, R. and Bhandary N.P., 2010: GIS-based highway maintenance prioritization model: an integrated approach for highway maintenance in Nepal mountains. In: Journal of Transport Geography, Vol. 18, Issue 3, pp. 426-433. DOI: http://dx.doi. org/10.1016/j.jtrangeo.2009.06.016
  15. Pejic, A., Pletl, S. and Pejic, B., 2009: An expert system for tourists using Google Maps API, Intelligent Systems and Informatics, 2009. SISY '09. 7th International Symposium on, pp. 317-322. DOI: http://dx-
  16. Weiping, H. and Chi, W., 2010: Urban Road Network Accessibility Evaluation Based on GIS Spatial Analysis Techniques. In: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. 38, Part II, pp. 114-117.
  17. Zandbergen, P.A., 2008: A comparison of address point, parcel and street geocoding techniques. In: Computers, Environment and Urban Systems, Vol. 32, Issue 3, pp. 214-232. DOI: 2007.11.006
  18. Zhang, J.Y and Shi, H., 2007: Geospatial Visualization using Google Maps: A Case Study on Conference Presenters. In: Computer and Computational Sciences, 2007. IMSCCS 2007. Second International Multi- Symposiums on; 09/2007, pp. 472-476.
Cytowane przez
Udostępnij na Facebooku Udostępnij na Twitterze Udostępnij na Google+ Udostępnij na Pinterest Udostępnij na LinkedIn Wyślij znajomemu