چكيده لاتين :
Introduction
Tourism, as the largest and fast growing economic activity in many countries around the world, is an important sector of the world economy (Grillakis et al, 2015). This economic activity strongly influenced by many factors, including culture, economy, environmental potentials and climate of the places that host the activity. However, climate as an important environmental component of a given region profoundly impacts tourism because it is very much dependent on climate conditions. Undoubtedly, a comfortable climate for recreational activities in any given destination is the main factor in tourist attraction, but an unsatisfactory climate or adverse weather conditions substantially reduce the number of tourists. in the past few decades, climatic factors played an important role in the process and trends of world tourism and, the tourism planners and operators, indigenous communities of tourism destinations and tourists, and all of the factors and components of the tourism system have a special focus at the climate factor at their tourism decisions. In this prospective Iran, as a country with a diverse climate is considered at tourism decision making. In recent years, climate tourism researches is based on survey data and measuring tourist’s satisfaction about climatic conditions because of differences between tourism destinations and variety cultural, economic, political and social conditions. Iran country is one of the most country in the world based on climate and tourism capabilities. Iran’s south coasts has high potentials about tourism and climate tourism. The paper try to survey climate tourism based on surveying data and tourists interviews and presenting improvement in tourism climate indexes.
Materials and Methods
In order to surveying tourism climate in Qeshm Island, it is used tourism climate indexes involved CIT, PET and PMV indexes. In order to evaluate the climatological condition of Qeshm district for tourism, the TCI, PMV, and CIT climatic indices were computed for Qeshm station as the representative of the coastal areas of southeastern Iran. These three indices were selected as they consider the climatic and environmental conditions, the human thermal condition and the degree of satisfaction of the tourists previously visited the target area CIT rates the climate resource for activities that are highly climate/weather sensitive, specifically, beach “sun, sea and sand” (3S) holidays. CIT integrates thermal (T), aesthetic (A) and physical (P) facets of weather, which are combined in a weather typology matrix to determine a climate satisfaction rating that ranges from very poor (1 = unacceptable) to very good (7 = optimal). Parameter A refers to sky condition and P to rain or high wind. T is the body-atmosphere energy balance that integrates the environmental and physiological thermal variables, such as solar heat load, heat loss by convection (wind) and by evaporation (sweating), long wave radiation exchange and metabolic heat (activity level). The second index used in this research is the predicted mean vote index (PMV) developed by Fanger (1972) to defining the thermal comfort of the environment, using the heat balance equations and empirical studies of skin temperature. The PMV and the predicted percentage dissatisfied (PPD) index were developed to help air-conditioning engineers to create a thermally comfortable indoor climateThe Predicted Mean Vote (PMV) model stands among the most recognized thermal comfort models. It was developed using principles of heat balance and experimental data collected in a controlled climate chamber under steady state conditions. The adaptive model, on the other hand, was developed based on hundreds of field studies with the idea that occupants dynamically interact with their environment. Occupants control their thermal environment by means of clothing, operable windows, fans, personal heaters, and sun shades. The PMV model can be applied to air conditioned buildings, while the adaptive model can be generally applied only to buildings where no mechanical systems have been installed. There is no consensus about which comfort model should be applied for buildings that are partially air conditioned spatially or temporally. The Munich energy balance model for individuals is one of the thermo physiological heat balance models. It is the basis for the calculation of the physiologically equivalent temperature (PET). Data period is 2003-2013 in Qeshm coastal synoptic station.
One of the largest islands in the world, Qeshm boasts numerous natural, historical, religious and trade attractions. The beautiful nature of Qeshm has not only made the island an ideal vacation spot, but also an intriguing place for academic research. Qeshm Island is located a few kilometers off the southern coast of Iran (Persian Gulf), opposite the port cities of Bandar Abbas and Bandar Khamir. The island, at its widest point, located near the center of the island, spans 40 kilometers.
Results and Discussion
The results shows important points. Although tourism climate in Qeshm station is suitable in cold months and night hours but when tourism climate in Qeshm assess by CIT index, all of the months in a long year and all of the daily hours (except daily hours in months of summer) is suitable and acceptable that it is incompatible with the Qeshm island condition. There are many differences between tourism destinations and between tourists according to natural, human, cultural and social condition. Therefore. The CIT index is improved by the paper. In order to improvement, PMV index is compound with data of tourism satisfactions in completing questionnaire from tourist in Qesh coasts. PMV multiplied with tourism data. New values is from -28 to 28. Values -2 to 2 is very good climate condition for tourism and values -6 to 6 is acceptable. Results of the improvement CIT shows that Qeshm Island is unsuitable in six months (from May to October) in year and all of the daily night hours in the same period.
Conclusions
This paper try to esurveying tourism climate index in differences condition and different places and destinations and involving tourism satisfaction data in results of tourism climate. It is concluded CIT index is presented in spatial condition and it shouldn’t exclusively in all of the world. Because, tourists has different emotions and interests and perceived climate also is variety. Tourists is different with resident people. New and improved CIT shows actual results and compatibles with space conditions.
