Gypsum Factory Site Selection in Qom Province using Different Multi-Criteria Decision Making Methods and Remote Sensing Techniques

Document Type : Research Article

Authors

1 Department of Environment, Faculty of Natural Resources and Earth Sciences, University of Kashan, Kashan, Iran

2 Department of Mining Engineering, University of Kashan, Kashan, Iran

Abstract

The purpose of this research is the site selection of the gypsum factory in Qom province by considering the effective criteria using different multi-criteria decision making methods and remote sensing techniques. Satellite images processing methods such as the false color composite method, band ratio method, and selective principal component analysis (CROSTA) method were used to find the possible location of the presence of minerals related to gypsum industries and the possible locations of the presence of the desired minerals were determined. Then, the location map of open pit mines was formed by their geographical coordinates, which were entered into the GIS along with other layers of criteria in a similar format and standardized by fuzzy logic. Then the criteria were weighted using the analytic hierarchy process method. According to the results of weighting using the analytic hierarchy process method, it was determined that the distance from gypsum mines and distance from industries were introduced as the most important (0.231) and least important (0.021) criteria, respectively. After applying the minimum required area, 4 regions with an area of 203 hectares were identified in the southern parts of Qom, Kahak, and Salafchegan cities. Also, by prioritizing 4 suitable options for the establishment of the industry using the fuzzy TOPSIS method, option 1 with an area of 23886 hectares in the Salafchagan sector was determined as the best option. The methods used in this study can provide decision-makers with possible options and prevent the complications of the inappropriate establishment of the relevant industries.

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References

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Environmental Energy and Economic Research
Volume 7, Issue 2
May 2023
Pages 1-17

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