Analyzing the geotourism and geomorphological capabilities of pristine natural areas of East Azerbaijan Province using quantitative indicators

Document Type : Origional Article

Authors

1 MSc student, Ecotourism, Faculty of Social Sciences,University of Mohaghegh ardabili, Ardabil, Iran.

2 Professor of Geomorphology, University of Social Sciences,University of Mohaghegh Ardabili,Ardabil, Iran.

3 BAc student in Geography, Faculty of Social Sciences,University of Mohaghegh Ardabili,Ardabil, Iran,

4 PhD student in Geomorphology, Faculty of Social Sciences,University of Mohaghegh Ardabili,Ardabil, Iran.

Abstract
Background and Objective: Tourism as a modern phenomenon has an economic nature and has a special role and importance for countries that have this capacity. Geotourism is a combination of the words "geo" meaning earth and "tourism" meaning tourism. The purpose of this research is to evaluate geotourism potentials and its management in the tourist area of ​​East Azerbaijan province.
Methodology: The research method in this study is based on three models: Kobalikova, Kirchner and GEM. In the Kobalikova and Kirchner model, the criteria are classified into five groups: scientific and intrinsic values, educational values, economic values, conservation values ​​and other values, which cover almost all features of geotourism. The GAM model is a method of physical evaluation of primary geomorphosites to assess the sustainable planning and management of natural heritage sites and their transformation into tourism destinations. This method consists of two main and complementary values. The main values ​​include scientific and educational values, aesthetic and scenic values, and conservation values, and the complementary values ​​include performance values ​​and tourism values.
Results and Findings: The results of the evaluation based on the Kobalikva and Kirchner model showed that the geomorphosites of Arasbaran forests and the village of Shtebin received the highest score and the Aladagh region received the lowest score. Therefore, based on the validation of the models, it can be concluded that the forests of Arasbaran and the village of Shtebin received the highest score and have great potential for development. Finally, it is suggested that artificial intelligence be used in future studies to evaluate the geotourism areas under study and achieve more accurate results.

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Volume 6, Issue 4 - Serial Number 22
Winter 2025
Pages 309-324

  • Receive Date 01 April 2025
  • Revise Date 20 May 2025
  • Accept Date 31 May 2025
  • First Publish Date 04 June 2025
  • Publish Date 20 February 2026