List of Articles tourism climate

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  1 - Monitoring seasonal tourism at the northwest of Iran using Tourism Climate Index (T.C.I)
  Behroz Sobhani Vahid Safarian Zengir
  10.22034/jest.2018.13790
  Abstract Background and Objective: Recognizing the climatic potentias, as a basis for human activities, provides the predominant foundation for environmental and land use plannning. Most of the tourists follow climate considerations to choose the destination. The aim of More

  Abstract Background and Objective: Recognizing the climatic potentias, as a basis for human activities, provides the predominant foundation for environmental and land use plannning. Most of the tourists follow climate considerations to choose the destination. The aim of this study was to evaluate and render the zoning of seasonal tourism at the northwest of Iran using tourism climatic index (T.C.I). Method: In this study, to assess the climatic conditions from the tourism perspective, the climatic data from 22 synoptic stations in the northwest Iran for a period of 20 years (1990-2010) were collected. In this model, a 7-parameter system was used. These parameters included mean maximum temperature, average temperature, average minimum relative humidity, mean relative humidity, total monthly precipitation, sunshine hours and daily average wind speed. The TCI index was used for data analysis and the tourism climate maps were drawn for four seasons using GIS. Findings: The results show that the TCI index has a large variety of topography in the northwest because of conflicts over the years. Summer with the conditions as infinite ideal: 7, ideal condition: 10, excellent quality: 3, acceptable: 1 and very good condition: 1 ranked the first among other three seasons. Autumn with the conditions as perfect: 4, very good: 11, good: 3 and acceptable: 4 ranked the second. Spring season with the spesifications as very good: 2, good: 2, acceptable: 11 and insignifcant: 7 ranked. Winter with the conditions as acceptable: 1, insignificant: 14, poor: 5 and very poor: 2 ranked the fourth place and the most unfavorable condition among the other seasons. Discussion and Conclusion: Northwest of Iran with great tourist attraction can be pioneer in local and foreign tourism. Beautiful scenery and unique and varied climate conditions in all seasons can greatly contribute to the development of this industry and lead to great benefits. Manuscript profile
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  2 - The Role of Tourism Climate Index with the emphasis on climate is A case study in north of Iran (Gilan province)
  Ayoub Badraghnejad Hossein Mousazadeh Hosein Kor
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  3 - Determining the appropriate ecotourism calendar in the west of the country using the PET index
  Ali Hanafi
  Weather is considered as one of the most important factors shaping tourism, and tourism centers owe their existence and values to many factors, especially suitable weather conditions. In this research, in order to evaluate and zoning the ecotourism calendar in Kurdistan More

  Weather is considered as one of the most important factors shaping tourism, and tourism centers owe their existence and values to many factors, especially suitable weather conditions. In this research, in order to evaluate and zoning the ecotourism calendar in Kurdistan, Kermanshah and Hamadan provinces, Riemann model and Physiological Equivalent Temperature Index (PET) have been used. The comfort conditions of the tourism climate and heat and cold stresses in different days and months of the year were evaluated using the PET index and then zoned in the GIS environment by considering the altitude. The results of the research showed that in most parts of the western region of the country, such as the cities of Sanandaj, Hamedan and Kermanshah, the time of climatic comfort for tourism activities occurs in two separate periods. From the end of May to the middle of October, heat stress is observed and from the beginning of December to the end of March, cold stress is observed in the border areas of Kermanshah.Finally, tourism climate maps of the western region of the country were prepared based on altitude changes and taking into account the relationship between the physiological temperature index and altitude, and by analyzing these maps, suitable times for activities such as mountain climbing in the important heights of the region such as Alvand, Chihel Cheshme, Peru and Shahu were identified. Manuscript profile
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  4 - Evaluation and Analysis of Tourism Climate Comfort Index of East Azarbaijan Province Using the Tourism Climate Index (TCI), Physiological Equivalent Temperature (PET) By Applying GIS
  Sakineh Sojoodi Firouz Aghazadeh Nagizadeh Fahimeh Leila Akhavan
  In this research in order to evaluate the tourism Climate Comfort Index, using the Tourism Climate Index (TCI), Physiological Equivalent Temperature (PET) and climate data gathered from 13 synoptic stations of the state, the state’s comfort condition is explained More

  In this research in order to evaluate the tourism Climate Comfort Index, using the Tourism Climate Index (TCI), Physiological Equivalent Temperature (PET) and climate data gathered from 13 synoptic stations of the state, the state’s comfort condition is explained through one year. In this way, first the climate data related to the studied stations are gathered from Meteorological Organization of the State. After analyzing and processing in Excel and preparing information banks for each one of the indexes with the separation of the each month of the year for every station was calculated. Later, in order to find TCI index, information about this indicator was transferred to the TCI_Calculator software and PET index was transferred to the RayMan Software, Then, using the technique of GIS, Maps of studied indexes were prepared for each month of the year and for each of the stations. The result of studying these indexes showed that, the tourism’s conditions of comfort in the studied stations over the year, based on TCI indicator on January, February, April, July, August, March, May, October, November and December (with three classifications of, marginal, acceptable and good) were the worst in terms of comfort, other months (with three classifications of, very good, excellent and ideal) had the best condition in terms of Tourism comfort. Based on PET indicators June, July, August, May and September had better comforting conditions for tourists, the rest of the year was chosen to have the worst comfort condition for tourists. Manuscript profile
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  5 - Explaining the Tourism Climate of the East of Guilan Province Using the Physiological Equivalent Temperature
  Naser Khoshdel Parviz Rezaei Sadraldin Sadraldin GholamReza JanbazGhobadi
  In this research, the tourism climate of the east of Guilan province during the statistical period 1996 to 2015 (20 years) was investigated by PET and TCI methods, and was interpolated with the Kriging method. Also, by using factor analysis (PCA) and cluster analysis, t More

  In this research, the tourism climate of the east of Guilan province during the statistical period 1996 to 2015 (20 years) was investigated by PET and TCI methods, and was interpolated with the Kriging method. Also, by using factor analysis (PCA) and cluster analysis, they categorized their values from the spatial dimension. Factor analysis of PET values from spatial dimension showed that the PET value of this area was classified into two groups and 52.59% and 46.87% of the variance of the data in rotational state respectively. The first component consists of Roudsar, Kyashahr, Lahijan, Ramsar, Masouleh, Anzali and Rasht stations, and the second component includes the Manjil, Dylaman, Jirandeh and MoalemKalayeh stations. Also, the cluster analysis of the amount of PET divided the East Guilan stations into two groups, with Kyashahr, Roudsar, Lahijan, Ramsar, Rasht and Anzali stations in the first group and Masouleh, Manjil, Dylaman, MoalemKalayeh and Jirandeh stations in the second group. In this regard, the number of detected factors of the TCI value from spatial dimension showed that the two components explained 56.51 and 37.54 percent of the variance of the data in rotational state, the first component is comprised Ramsar, Anzali, Rasht, Kyashahr, Lahijan, Roudsar and Manjil stations, and the second component is the Masouleh, Dyelaman, Jirandeh and MoalemKalayeh stations. Also, using cluster analysis, two independent groups were identified based on the similarity of TCI values. Manuscript profile