The delimitation and classification of peripheral settlements using multivariate statistical methods is presented in this article, with a case study of Hungary. A combination of four different methods provided the basis for the delimitation of settlements defined as peripheral. As significant overlapping was detected between the results of the different methods, peripheries – more than one-fifth of the Hungarian settlements – were identified in a common set of the results. The independence of the results from the applied methods points to the fact that peripherisation is multi-faceted, and the peripheries of Hungary are stable and well-discernible from other regions. After the identification of peripheral areas, we classified these settlements into groups based on their specific features. Multiple steps specifying the relevant variables resulted in selecting the most appropriate 10 indicators and these served as the basis for a hierarchical cluster analysis, through which 7 clusters (types of peripheries) were identified. Five of them comprised enough cases to detect the most important dimensions and specific features of the backwardness of these groups. These clusters demonstrated a spatial pattern and their socioeconomic and infrastructural features highlighted considerable disparities. These differences should be taken into consideration when development policies are applied at regional levels or below.
a b s t r a c tHern ad Valley is one of the most underdeveloped areas of Hungary in social, infrastructural and economic aspects. At the same time, there are significant reserves regarding the bio-energy sector, energy investments and local raw material production. The biomass potential of the underdeveloped areas is tremendous (125,000 t/year, its energy value 25e28 M EUR/year), but quite difficult to exploit since the implementation of efficient energetic procedures is made very difficult by the indifference or resistance of the local population or the lack of capital (either on the part of the local authorities or the investors) which would be necessary to finance the improvements.During our three-year-long research, we collected the most significant social, economic and fitomass production data of the examined settlements based on statistical resources and our own personal research. Based on the size and location of biomass data, we recommended sample projects which most probably could be operated economically, could produce the highest added value and could retain most of the produced value in the area. Based on a statistically reliable amount of data, we present the awareness and acceptance of the biomass energetic procedures and how much these factors would affect the implementation of the recommended projects.
Abstract. Nowadays more and more attention is devoted to the spatial development of the location of sports facilities within cities. The main aim of our paper is to observe the most important spatial characteristics of their development in Hungarian cities of county rank. In these cities three main periods of development of sports facilities can be observed. Larger sports facilities were constructed especially on the edge of cities or in the suburbs, while in the case of smaller facilities a bigger role was played by locations within the city boundaries. As regards the factors influencing the location of sports facilities, the most important role was played by the location of available land areas, besides accessibility and from the mid-1960s links to existing facilities can be mentioned as well.
Methods of functional regional taxonomy and concrete definitions of functional regions based on prevailing population flows have been discussed in many regional studies. The resulting regions have been given various names (travel-to-work areas, local labour market areas, housing market areas, etc.) based on the character of the input data and the method of their definition. However, in most cases only one country (or part thereof) at a time has been analysed. The paper brings a unique definition of functional regions with comparable parameters suitable for international comparisons. Three Central European countries with different settlement and regional structures are analysed. The functional regions in all countries are objectivised through the operation with the constraint function, which estimates natural and non-normative values for the self-containment and size parameters. Two interaction measures are used in the regionalisation algorithm. Besides the methodological contribution, the role of spatial behaviour is briefly discussed, and an interpretation of the results and a proposal for the possible application of functional regions in regional planning and regional analysis in international research tasks is given. K E Y W O R D SCentral Europe, daily travel-to-work flows, functional regions, regional analysis, regional planning, spatial behaviour ---
An increasing amount of CO2 emissions from the household sector of Iran led us to analyze the inequality and understand the possible driving force behind the CO2 emissions. The study of inequality provides information to policy-makers to point policies in the right direction. By considering the differences in the socio-economic factors of provinces, the study aims to analyze the inequality in CO2 emissions and different kinds of energy consumption, including oil, gas and electricity, for the household sector of Iran’s provinces between 2000 and 2017. For this aim, the Theil index and Kaya factor, as a simple and common method, were considered to evaluate the inequality in both CO2 emissions and energy consumption, and determine the driving factor behind CO2 emissions. According to the results, inequality in oil and natural gas consumption were increasing, electricity was almost constant; however, CO2 emissions experienced a decreasing trend for the study period. The Theil index changed from 0.4 to 0.65 for oil, from 0.18 to 0.22 for natural gas, from 0.17 to 0.15 for electricity, and from 0.2 to 0.14 for CO2 emissions between 2001 and 2017. In addition, the results of the inequality study indicated that most of the inequalities belong to within-group inequalities in energy consumption and CO2 emissions. The results of the Kaya factor indicate that the second factor, energy efficiency, with a 0.21 value was the main driving factor of inequalities in CO2 emissions; however, the first factor, energy consumption, can be a potential factor for inequality in the following years, as it increased from 0.00 to 0.11 between 2001 and 2017. It seems that by removing the energy subsidy policy in 2010 and 2013, low-standard and energy-wasting old vehicles were the most effective factors of energy inefficiency in the household sector, which need more accurate policy-making.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.