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Volume 38, Issue 3 (2023)
GeoRes 2023, 38(3): 411-422 |
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Received: 2023/08/20 | Accepted: 2023/09/18 | Published: 2023/10/2
Received: 2023/08/20 | Accepted: 2023/09/18 | Published: 2023/10/2
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Miri E, Amirahmadi A, Akbari E. Developing an Integrated Decision-Making Model Based on RS and GIS to Identify the Geomorphotourist Capabilities of Tajnood Valley and Hemmatabad Desert. GeoRes 2023; 38 (3) :411-422
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1- Department of Geomorphology and Climatology, Faculty of Geography and Environmental Sciences, Hakim Sabzevari University, Sabzevar, Iran
2- Department of Remote Sensing and GIS, Faculty of Geography and Environmental Sciences, Hakim Sabzevari University, Sabzevar, Iran
2- Department of Remote Sensing and GIS, Faculty of Geography and Environmental Sciences, Hakim Sabzevari University, Sabzevar, Iran
Abstract (1043 Views)
Aims: Identifying the geomorphotourism capabilities of a region can lead to attracting tourists, planning for sustainable geotourism, and improving infrastructure. The primary objective of the current study was to develop a comprehensive decision-making framework that incorporates remote sensing (RS) and geographic information systems (GIS) in order to identify the geomorphotourism potentials of Tajnood Valley and Hemmatbad Desert in Zirkuh County.
Methodology: This is a quantitative survey carried out in 2022-2023. In the present investigation, after the identification of landforms, geomorphological characteristics, and geosites using RS techniques, the Fassoulas, GAM, and Comanescu models were utilized to prioritize and assess the potentials of geotourism, which included geosites, geomorphosites, as well as economic and cultural sites. Subsequently, in order to address the limitations of each individual model and capitalize on the strengths of all models, the Fassoulas-GAM-Comanescu integrated model (FA-CO-GM) was employed, employing the Analytical Hierarchy Process (AHP). By doing so, it becomes possible to combine multiple factors that are typically treated separately in each model, and effectively utilize the advantages offered by each model.
Findings: The conclusive representation of the decision-making model based on Remote Sensing and Geographic Information Systems (RS and GIS) that was developed by Comanescu, Fassoulas, and GAM exhibits that 36% of the region in question is situated within a zone of high potential. This particular zone is characterized by the presence of geomorphological landforms, appropriate access, an expansive perspective, and elevated viewpoints. Furthermore, 51% of the region resides in a zone of very high potential due to its demonstrativeness, diverse array of geomorphological features, rarity, state of being intact, and overall integrity in terms of geosites. To validate the accuracy of the models developed by Comanescu, Fascilos, GAM, and Analytic Hierarchy Process (AHP), a sample t-test was employed. The significance level of this particular test is less than 0.05, thereby falling within the confines of the standard and significant test limit.
Conclusion: During the process of identifying and assessing the geomorphosite potential of Tajnood Valley and Hemmatabad Desert, located in the arid region of Zirkuh County, it was discovered that by utilizing multiple valuation models and employing a specific multi-criteria decision-making approach within the framework of Geographic Information Systems (GIS), it is feasible to rectify these shortcomings and generate a well-suited zoning map for the geosite by amalgamating the outcomes of various models.
Methodology: This is a quantitative survey carried out in 2022-2023. In the present investigation, after the identification of landforms, geomorphological characteristics, and geosites using RS techniques, the Fassoulas, GAM, and Comanescu models were utilized to prioritize and assess the potentials of geotourism, which included geosites, geomorphosites, as well as economic and cultural sites. Subsequently, in order to address the limitations of each individual model and capitalize on the strengths of all models, the Fassoulas-GAM-Comanescu integrated model (FA-CO-GM) was employed, employing the Analytical Hierarchy Process (AHP). By doing so, it becomes possible to combine multiple factors that are typically treated separately in each model, and effectively utilize the advantages offered by each model.
Findings: The conclusive representation of the decision-making model based on Remote Sensing and Geographic Information Systems (RS and GIS) that was developed by Comanescu, Fassoulas, and GAM exhibits that 36% of the region in question is situated within a zone of high potential. This particular zone is characterized by the presence of geomorphological landforms, appropriate access, an expansive perspective, and elevated viewpoints. Furthermore, 51% of the region resides in a zone of very high potential due to its demonstrativeness, diverse array of geomorphological features, rarity, state of being intact, and overall integrity in terms of geosites. To validate the accuracy of the models developed by Comanescu, Fascilos, GAM, and Analytic Hierarchy Process (AHP), a sample t-test was employed. The significance level of this particular test is less than 0.05, thereby falling within the confines of the standard and significant test limit.
Conclusion: During the process of identifying and assessing the geomorphosite potential of Tajnood Valley and Hemmatabad Desert, located in the arid region of Zirkuh County, it was discovered that by utilizing multiple valuation models and employing a specific multi-criteria decision-making approach within the framework of Geographic Information Systems (GIS), it is feasible to rectify these shortcomings and generate a well-suited zoning map for the geosite by amalgamating the outcomes of various models.
Keywords:
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