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      Industrial park land capability assessment and post-evaluation in Markazi province

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          Abstract

          Markazi province in Central Iran is a highly attractive area for the development of industrial centers; however, over the last few decades, unregulated development has led to environmental and socioeconomic issues. The purpose of this research is to evaluate the existing industrial parks and identify potential areas for appropriate development. An industrial land capability assessment utilized 14 main criteria and 10 constraint parameters of socioeconomic, infrastructural, biological, and physical aspects using a geographic information system-based analytical network process model. Results show that Markazi province has 14.27% of highly suitable and 11.32% of extremely suitable area for industrial development; contrariwise, 60.14% of the province has no potential or is classified as an exclusion zone. Moreover, 44.4% (i.e., 8 parks) of the province’s industrial parks are located in unsuitable zones. According to the land capability of Markazi province, the need to organize existing industrial parks and integrate industrial units alongside existing centers and potential areas should be considered in the industrial development policies of the province. The results of the sensitivity analysis also support the research findings.

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          Investigating the environmental Kuznets curve (EKC) hypothesis by utilizing the ecological footprint as an indicator of environmental degradation

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            GIS-based land-use suitability analysis: a critical overview

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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Applied Geomatics
                Appl Geomat
                Springer Science and Business Media LLC
                1866-9298
                1866-928X
                March 2022
                December 21 2021
                March 2022
                : 14
                : 1
                : 105-118
                Article
                10.1007/s12518-021-00415-x
                1614c670-aa45-4823-8669-8a313edb8d45
                © 2022

                https://creativecommons.org/licenses/by/4.0

                https://creativecommons.org/licenses/by/4.0

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