Identification of climatic comfort areas Khuzestan province using multivariate analysis and spatial autocorrelation pattern with emphasis on architecture
Abstract In the history of humanity, human always has suffered all difficulties with effort to reach to comfort and well-being until the human provides a way to achieve the comfort. In the viewpoint of climate four elements have significant role in formation of human comfort and discomfort conditio...
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Kharazmi University
2023-06-01
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| Series: | تحقیقات کاربردی علوم جغرافیایی |
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| Online Access: | http://jgs.khu.ac.ir/article-1-3848-en.pdf |
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| author | Shahla Qasemi Reza Borna Faredeh Asadian |
| author_facet | Shahla Qasemi Reza Borna Faredeh Asadian |
| author_sort | Shahla Qasemi |
| collection | DOAJ |
| description | Abstract
In the history of humanity, human always has suffered all difficulties with effort to reach to comfort and well-being until the human provides a way to achieve the comfort. In the viewpoint of climate four elements have significant role in formation of human comfort and discomfort conditions that according to the climatic conditions in different areas, the type and effect of these elements on individuals are also different. The aim of this research is to determine the areas of climatic comfort. For this purpose, temperature, precipitation and humidity data were derived from database of Esfazari for Khuzestan province during statistical period 1965 to 2014. In this process, at first discomfort climate has been defined using temperature, precipitation and humidity based on distribution probability conditional. This research is to determine the areas of climatic comfort in Khuzestan province using multivariate analysis (Cluster analysis and Discriminant analysis) and spatial autocorrelation pattern (Hot Spot index and Moran index) with emphasis on architecture. The results showed that the areas with climatic comfort are included in north and east parts of Khuzestan province. However, the areas of climatic comfort by spatial method have been limited somewhat. Results further indicated that the areas of climatic comfort have decreased significantly towards recent periods especially in cluster analysis and discriminant analysis that a trend of reduction has been remarkable in cluster analysis (from 23.60% in the first period to 17.60% in the fifth period) and discriminant analysis (from 26.97% in the first period to 14.98% in the fifth period). |
| format | Article |
| id | doaj-art-f8070d47e3f24d6ab87910341068724c |
| institution | Kabale University |
| issn | 2228-7736 2588-5138 |
| language | fas |
| publishDate | 2023-06-01 |
| publisher | Kharazmi University |
| record_format | Article |
| series | تحقیقات کاربردی علوم جغرافیایی |
| spelling | doaj-art-f8070d47e3f24d6ab87910341068724c2025-01-31T17:29:56ZfasKharazmi Universityتحقیقات کاربردی علوم جغرافیایی2228-77362588-51382023-06-012369403424Identification of climatic comfort areas Khuzestan province using multivariate analysis and spatial autocorrelation pattern with emphasis on architectureShahla Qasemi0Reza Borna1Faredeh Asadian2 Mahshahr university Science and Ahvaz university Science and research branch,Islamic azad university Abstract In the history of humanity, human always has suffered all difficulties with effort to reach to comfort and well-being until the human provides a way to achieve the comfort. In the viewpoint of climate four elements have significant role in formation of human comfort and discomfort conditions that according to the climatic conditions in different areas, the type and effect of these elements on individuals are also different. The aim of this research is to determine the areas of climatic comfort. For this purpose, temperature, precipitation and humidity data were derived from database of Esfazari for Khuzestan province during statistical period 1965 to 2014. In this process, at first discomfort climate has been defined using temperature, precipitation and humidity based on distribution probability conditional. This research is to determine the areas of climatic comfort in Khuzestan province using multivariate analysis (Cluster analysis and Discriminant analysis) and spatial autocorrelation pattern (Hot Spot index and Moran index) with emphasis on architecture. The results showed that the areas with climatic comfort are included in north and east parts of Khuzestan province. However, the areas of climatic comfort by spatial method have been limited somewhat. Results further indicated that the areas of climatic comfort have decreased significantly towards recent periods especially in cluster analysis and discriminant analysis that a trend of reduction has been remarkable in cluster analysis (from 23.60% in the first period to 17.60% in the fifth period) and discriminant analysis (from 26.97% in the first period to 14.98% in the fifth period).http://jgs.khu.ac.ir/article-1-3848-en.pdfkeywords: climatic comfort areacluster analysisdiscriminant analysishot spot and moran indiceskhuzestan |
| spellingShingle | Shahla Qasemi Reza Borna Faredeh Asadian Identification of climatic comfort areas Khuzestan province using multivariate analysis and spatial autocorrelation pattern with emphasis on architecture تحقیقات کاربردی علوم جغرافیایی keywords: climatic comfort area cluster analysis discriminant analysis hot spot and moran indices khuzestan |
| title | Identification of climatic comfort areas Khuzestan province using multivariate analysis and spatial autocorrelation pattern with emphasis on architecture |
| title_full | Identification of climatic comfort areas Khuzestan province using multivariate analysis and spatial autocorrelation pattern with emphasis on architecture |
| title_fullStr | Identification of climatic comfort areas Khuzestan province using multivariate analysis and spatial autocorrelation pattern with emphasis on architecture |
| title_full_unstemmed | Identification of climatic comfort areas Khuzestan province using multivariate analysis and spatial autocorrelation pattern with emphasis on architecture |
| title_short | Identification of climatic comfort areas Khuzestan province using multivariate analysis and spatial autocorrelation pattern with emphasis on architecture |
| title_sort | identification of climatic comfort areas khuzestan province using multivariate analysis and spatial autocorrelation pattern with emphasis on architecture |
| topic | keywords: climatic comfort area cluster analysis discriminant analysis hot spot and moran indices khuzestan |
| url | http://jgs.khu.ac.ir/article-1-3848-en.pdf |
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