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• Climate as a risk factor for tourism

  113-125

  Ákos Németh

  János Mika

  Views:

  135

  Weather and climate risk factors for tourism are surveyed and illustrated with regard to the expected climate changes in Hungary. These changes are not at all advantageous and which affect the business in question both directly and indirectly. These are the summer resort tourism (characterised by bioclimatic indices). Green tourism is the next one to characterise, including skiing, mountain climbing and eco-tourism, as well. Here both day-to-day weather extremes and long-lasting effects on the biota (e.g. drought, or inundation for plain-area eco-tourism). Last, but not least the urban (cultural- and shopping-) tourism is presented, since the large towns exhibit their special climate and different risks. The paper intends to specify these meteorological factors and effects also in terms of the different types of touristic activities. The general statements on the effect of weather and climate on tourism are illustrated by a few individual parameters and also by the so called Physiologically Equivalent Temperature. Annual and diurnal course of this parameter are presented, together with various trends in this variable at different sites and in different (hot and cold) extremities of the occurring values. Other examples, helping the tourism industry are presented in various climate conditions of the country. They include high precipitation and high relative humidity information. The paper also lists the possible adaptation measures to extreme events and also their likely changes in time.

• Environmental objective analysis, ranking and clustering of Hungarian cities

  91-108

  László Makra

  Zoltán Sümeghy

  Views:

  34

  The aim of the study was to rank and classify Hungarian cities and counties according to their environmental quality and level of environmental awareness. Ranking of the Hungarian cities and counties are represented on their „Green Cities Index” and „Green Counties Index” values. According to the methodology shown in Part 1, cities and counties were grouped on different classification techniques and efficacy of the classification was analysed. However, they did not give acceptable results either for the cities, or for the counties. According to the parameters of the here mentioned three algorithms, reasonable structures were not found in any clustering. Clusters received applying algorithm fanny, though having weak structure, indicate large and definite regions in Hungary, which can be circumscribed by clear geographical objects.