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A statistical approach to estimates of geomorphological-morphotectonic diversity for evaluating the scientific value of geosites: a case study from the southeastern Lut desert, Iran Cover

A statistical approach to estimates of geomorphological-morphotectonic diversity for evaluating the scientific value of geosites: a case study from the southeastern Lut desert, Iran

Open Access
|May 2020

Abstract

The present study aims to investigate the diversity index (dv-index) of morphotectonic and geomorphological land-forms as one of the scientific value indices for evaluation of the geotouristic potential of the southeastern Lut desert using topographic statistical analysis. Scientific index scoring in most models is based on descriptive assessment by geotourists and experts. Statistical analysis of the dv-index in the present study helps experts to base their scoring on scientific methods. The dv-index is controlled by several items. In the present study, we analyse two of these, including the classification of topographic continuity pattern (TCP) and topographic slope position correlation (TSPC). For this purpose, a network of section lines is used to analyse slope continuity. The TSPC analysis is performed by using two parameters of absolute value and slope position. Results for these two evaluated items indicate a score of 1.46 (out of 2) for the dv-index. Given a rating of 5, the score obtained for the two items is a high one. Therefore, an initial estimate of the dv-index indicates a significant scientific value of the study area.

DOI: https://doi.org/10.2478/logos-2020-0006 | Journal eISSN: 2080-6574 | Journal ISSN: 1426-8981
Language: English
Page range: 75 - 86
Submitted on: Jun 20, 2019
Accepted on: Feb 15, 2020
Published on: May 16, 2020
Published by: Adam Mickiewicz University
In partnership with: Paradigm Publishing Services
Publication frequency: 3 issues per year

© 2020 Pouya Sadeghi-Farshbaf, Mohammad Mahdi Khatib, Naser Rezaei, published by Adam Mickiewicz University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.