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An Analysis of Recreational and Leisure Areas in Polish Counties with the Use of Geographically Weighted Regression

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  • Marta Nalej

    (Faculty of Geographical Sciences, University of Lodz, 90-136 Łódź, Poland)

  • Elżbieta Lewandowicz

    (Faculty of Geoengineering, University of Warmia and Mazury in Olsztyn, 10-719 Olsztyn, Poland)

Abstract

Recreational and leisure areas play a special role. These areas mitigate or eliminate the disadvantages of living in large cities, enhance the quality of life in small towns, and support sustainability. The aim of this study was to analyze the share of recreational and leisure areas in Polish counties in 2022. In Poland, recreational and leisure areas constitute a separate land-use category in cadastral registers. Annual cadastral data from the Land and Building Register at county level (in tabular form) were the main source of data for the study. The analysis revealed that the share of recreational and leisure areas was higher in counties situated in western and south-western Poland, as well as in cities. The spatially varied influence of socioeconomic factors on the share of recreational and leisure areas in Polish counties in 2002 was determined with the use of the local Moran’s I statistic and geographically weighted regression (GWR). The study confirmed that population density was significantly related to the share of recreational and leisure areas in Polish counties. The impact of the remaining socioeconomic factors associated with spatial and economic development varied across regions. The study also revealed that, in addition to the current socioeconomic determinants, the share of recreational and leisure areas in Polish counties was also influenced by historical factors and the counties’ development since their establishment.

Suggested Citation

  • Marta Nalej & Elżbieta Lewandowicz, 2023. "An Analysis of Recreational and Leisure Areas in Polish Counties with the Use of Geographically Weighted Regression," Sustainability, MDPI, vol. 16(1), pages 1-26, December.
    • Handle: RePEc:gam:jsusta:v:16:y:2023:i:1:p:380-:d:1311471
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    References listed on IDEAS

    as
    1. Kyung Hee Lee, 2020. "Mental Health and Recreation Opportunities," IJERPH, MDPI, vol. 17(24), pages 1-15, December.
    2. Sonja Kivinen, 2017. "Sustainable Post-Mining Land Use: Are Closed Metal Mines Abandoned or Re-Used Space?," Sustainability, MDPI, vol. 9(10), pages 1-18, September.
    3. A. Szczepańska & M. Zagroba & K. Pietrzyk, 2022. "Participatory Budgeting as a Method for Improving Public Spaces in Major Polish Cities," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 162(1), pages 231-252, July.
    4. Iwona Kantor-Pietraga & Robert Krzysztofik & Maksymilian Solarski, 2023. "Planning Recreation around Water Bodies in Two Hard Coal Post-Mining Areas in Southern Poland," Sustainability, MDPI, vol. 15(13), pages 1-25, July.
    5. Jinwon Kim & Sarah Nicholls, 2018. "Access for all? Beach access and equity in the Detroit metropolitan area," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 61(7), pages 1137-1161, June.
    6. A. Stewart Fotheringham & Taylor M. Oshan, 2016. "Geographically weighted regression and multicollinearity: dispelling the myth," Journal of Geographical Systems, Springer, vol. 18(4), pages 303-329, October.
    7. Koenker, Roger, 1981. "A note on studentizing a test for heteroscedasticity," Journal of Econometrics, Elsevier, vol. 17(1), pages 107-112, September.
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