Document Type : Origional Article
Authors
1
Associate Professor , Department of Geography and Urban and Rural Planning, University of Mohaghegh Ardabili, Faculty of Social Sciences, Department of Geography (Ardabil, Iran
2
Bachelor's student, University of Mohaghegh Ardabili, Faculty of Social Sciences, Department of Geography (Ardabil, Iran)
3
PhD student, Department of Physical Geography, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran
Abstract
Background and Objective: Geotourism is a type of sustainable tourism that emphasizes education and protection of geological and geomorphological attractions in addition to them. Geotourism is one of the important aspects of ecotourism with a responsible and conservation-oriented approach; which emphasizes popularizing earth sciences and the cultural, social, and economic development of the local community. The purpose of this study is to assess the ecotourism potential of natural areas of the tourist village Shtibin is in East Azerbaijan Province.
Methodology: The method of this research is the use of two quantitative models: Kobalikva and Feulet. Kobalikva's method, which emphasizes scientific, educational, economic, conservation and cultural criteria, and Feulet's model, which examines geotourism areas based on four criteria: origin of formation, geographical distribution, tourism and accessibility, was also used.
Results and findings: The results showed that based on the evaluation of the Kobalikva model, the Aras tourist region, with the highest score of 4.5, has a high potential among the studied areas. The results also showed that terraced houses, with a total score of 2.5, have the least development among the studied areas. The results of the national park model showed that among the studied areas, Arasbaran forests have the highest score of 10.25. Therefore, it is concluded that, based on the aforementioned models, the Aras and Arasbaran forests have a high potential for tourism development in East Azerbaijan Province. Finally, it is suggested that artificial intelligence tools be used in future studies to assess the ecotourism potential of the regions.
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