Explaining the Tourism Climate of the East of Guilan Province Using the Physiological Equivalent Temperature

Subject Areas : Natural geography and human settlements

Naser  Khoshdel ¹ (Ph.D. student of Climatology, Islamic Azad university of Nour, Mazandaran, Iran)
Parviz  Rezaei ² (دانشیار گروه جغرافیا، واحد رشت، دانشگاه آزاد اسلامی، رشت، ایران)
Sadraldin  Sadraldin ³ (Department of Physical Geography, Islamic Azad university of Nour)
GholamReza  JanbazGhobadi ⁴ (Department of Physical Geography, Islamic Azad university of Nour, Mazandaran, Iran)

Received: 2019-07-17 Accepted : 2019-09-22 Published : 2021-01-20

Keywords: tourism climate, ", " Physiological equivalent temperature, " Tourism climate index, " Guilan province,

Abstract :

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.

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