nástroj regionální politiky cestovního ruchu (Destination Management as an instrument for Regional Tourism Policy). Brno: Masaryk University. Hudman, L. E., & Jacskon, R. H. (2003). Geography of Travel Tourism. New York: Cengage Learning. Jackson, R. H. & Murphy, P. (2006). Cluster In Regional Tourism An Australian Case. Annals of Tourism Research, 33(4), 1018-1035. DOI: 10.1016/j.annals.2006.04.005 Kasagranda, A. & Cakoci, R. (2015). Priestorova diferenciacia a navštevnosť Slovenska občanmi Českej republiky (The SpatialDifferentiation and the Visit Rate of Slovakia
Wind energy research is dominated by studies of local acceptance (or not) of wind farms and comparative studies at a national level. Research on the spatial differentiation of wind energy developments at the regional level is still insufficient, however. This study provides new empirical evidence for the extent to which regional differences in the deployment of wind energy are related to specific environmental and socioeconomic factors, by a statistical analysis of data for districts in the Czech Republic. Unlike previous studies, we found that the installed capacity of wind energy cannot be well predicted by wind potential, land area and population density in an area. In the Czech Republic, wind farms more likely have been implemented in more urbanised, environmentally deprived coal-mining areas that are affected by economic depression. It seems that in environmentally deprived areas, wind energy is more positively accepted as an alternative source to coal, and the economic motivation (financial benefits for municipalities) can have a greater effect on local acceptance, while public opposition is less efficient due to lower social capital and involvement in political matters. Based on these results, some implications for the planning and spatial targeting of new wind farms are discussed.
The demographic transformations in Russia have led to changes in the country’s urban population (population of cities and urban-type settlements), which declined by 3.3% in the years 1989-2010. However, the population of cities as such increased over the same period by 1.5%, mainly as a result of the huge growth in the population of Moscow. Population changes in Russian cities vary depending on the size of the city. The greatest change was observed, above all, in small peripheral cities, which lost as much as half of their population. However, even more alarming are the trends observed in the smaller cities of the historical heart of Russia, which fall within the catchment area of Moscow (and its aglomeration) and cities of supraregional importance. Such cities have been depopulating as fast as Siberian cities.
-137. Lovacka, S., 2008: The Use of the Voronoi Tessellation for Purposes of Service Distribution District Delimitation (the Example of the Prešov Nodal Region). In: Acta Facultatis Studorium Humanitatis et Naturae Universitatis Prešoviensis: Prírodné vedy: Folia Geographica 12: special issue for the 31th Congress, Tunis, Vol. XLVII, No. 12, pp. 163-171. Maceškova, M., Ouředniček, M. and Temelova, J., 2009: Sociálně prostorová diferenciace v České republice: implikace pro veřejnou (regionální) politiku (Socio-spatialDifferentiation in the Czech Republic: Implications for
of the “Zwischenstadt” or ‘in-between city’ has found some recognition in the international community since then ( Keil/Addie 2015 ). Our approach is guided by three perspectives that have not been part of the standard repertoire of empirical suburban studies to date. Firstly, we pursue an analysis which is not predetermined by normative, and thus primarily negative, claims about suburbia. Secondly, besides spatialdifferentiation, this study focuses also on investigating the temporal variation in the development trajectory of suburbia, thus taking up a claim
and physical decay in urban environment, arguing that ‘segregation is not a simple consequence of social inequality, but a product of both social and spatialdifferentiation’ ( Skifter Andersen 2003 : 125-126). Based on the analysis of case material collected from two Finnish suburban neighbourhoods, the aim of this article is to demonstrate that while the changes in urban population have increased the attention to urban environment with a demand for more varied urban residential areas, urban planning and design currently seem to lack tools to form adequate
brightening: A reviev, J. Geophys. Res., 114, D00D16, doi: 10.1029/2008JD011470. Wojkowski J., 2007, Modelowanie dopływu promieniowania słonecznego przy użyciu GIS na przykładzie obszaru Ojcowskiego Parku Narodowego, Annales Univer. M. Curie-Skłodowska, B, LXI, Geographia, 468-478. Wojkowski J., Skowera B., 2011, Spatialdifferentiation in absorbed solar radiation in the Ojców National Park, [in:] Středová W.H., Rožnovský J., Litschmann T. (eds.) Mikroklima a mezoklima krajinných struktur a antropogenních prostředí, Skalní mlýn, 2-4.2.2011, 3-11. Wójcik G., 1983
] Kościelniak P., Szewczyk M.W., Tokarski T., Taksonomiczne wskaźniki rozwoju ekonomicznego województw i powiatów, Wiadomości ststytyczne, 9, pp. 75-97, 2014.  Dziekański P., SpatialDifferentiation of the Financial Condition of the Świętokrzyskie Voivodship Counties, Barometr Regionalny, Tom 14 nr 3, pp. 79-91, 2016.  Zeliaś A., Malina A., O budowie taksonomicznej miary jakości życia. Syntetyczna miara rozwoju jest narzędziem statystycznej analizy porównawczej, Taksonomia z. 4, 1997.  Sobczyk A., Finansowanie rozwoju gminy z dochodów własnych, ZN SGGW, Ekonomika i
An important determinant of the level of development of each country and the whole Europe is the care about an adequate level of well-being and quality of life of all citizens, above all those to whom the future belongs - our children. In the times of demographic changes it is particularly important to understand specific needs and rights of the youngest generation of Europeans. Investing in children is investing in our future, the shape of which will depend precisely on whether the youngest generation will be healthy, well educated and able to participate in the development of their societies. The aim of this study is to identify territorial differentiation of children’s well-being in Europe at the end of the first decade of the 21st century using the methods of multivariate data analysis. The study was based on data published by Eurostat (among others EU-SILC), OECD (PISA), UNICEF, WORLD BANK and WHO (HBSC) for the years 2009 and 2010.