ارزیابی خطر بیابانزایی با استفاده از منطق تاپسیس فازی در محیط GIS
محورهای موضوعی :
مدیریت محیط زیست
محمد حسن صادقی روش
1
,
حسن خسروی
2
1 - دانشیارگروه محیط زیست، واحد تاکستان، دانشگاه آزاد اسلامی ، تاکستان، ایران. * (مسوول مکاتبات)
2 - دانشیار گروه احیاء مناطق خشک و کوهستانی، دانشکده منابع طبیعی دانشگاه تهران، تهران، ایران.
تاریخ دریافت : 1400/08/23
تاریخ پذیرش : 1401/01/31
تاریخ انتشار : 1401/03/01
کلید واژه:
منطق فازی,
روش بونیسون,
ساختار سلسله مراتبی,
مدلهای تصمیمگیری,
مقایسه زوجی,
چکیده مقاله :
زمینه و هدف: پدیده مخرب بیابان زایی یکی از بحران های جدی اکولوژیکی با اثرات گسترده و بلند مدت طبیعی و انسانی است. لذا اقدامات اجرایی در این زمینه باید متکی به شناخت وضعیت فعلی بیابانی شدن اراضی و شدت آن باشد. از طرفی ضعف روش های اندازه گیری شدت بیابان زایی، همواره نیاز به ارائه روش های نوین و کمی را ایجاب می کند. بنابراین لزوم پرداختن به روش هایی که بتواند پهنه بندی را بر مبنای منطق و اصول قوی و مبانی نظری مستدل ارایه دهد، ضروری به نظر می رسد. از این رو این پژوهش با هدف ارزیابی خطر بیابان زایی با استفاده از منطق تاپسیس فازی و به صورت موردی در دشت یزد- خضرآباد طی سال های 1399 تا 1400 به انجام رسید.
روش بررسی: در این پژوهش سعی شد پهنه بندی شدت بیابان زایی توسط روش تاپسیس فازی به انجام رسد. در این روش پس از تعیین و ارزش دهی شاخص های موثر از روش دلفی فازی و تهیه لایه واحدهای کاری، اقدام به فازی سازی داده ها از روش چن و هوانگ شد و در ادامه فرایند تحلیل فازی بر روی داده ها صورت گرفت و در نهایت ماتریس تصمیم گیری فازی موزون حاصل شد، که در چارچوب این ماتریس و از روش تاپسیس، برآورد شدت بیابان زایی به انجام رسید.
یافته ها: نتایج نشان داد که 34/9% درصد از کل منطقه مطالعاتی به صورت خیلی شدید، 71/7% درصد شدید و 57/%12 درصد به صورت نسبتاً شدیدی تحت فرایند بیابان زایی می باشد و بیابان زایی با شدت ناچیز (57/46%) و متوسط (81/23%) به ترتیب، بیشترین سهم را در منطقه مطالعاتی به خود اختصاص داده است. به طور کلی ارزش کمی شدت بیابان زایی برای کل منطقه از مجموع عوامل 262/0 (کلاس نسبتاً متوسط یا III) به دست آمد.
بحث و نتیجه گیری: مطالعه صورت گرفته نشان از کارایی و سهولت کاربرد منطق فازی در ارزیابی شدت بیابان زایی داشت. همچنین نتایج این پژوهش امکان برنامه ریزی را برای به حداقل رساندن بیابان زایی در اثر انجام طرح های توسعه فراهم می سازد و می تواند شرایطی را ایجاد کند که با توجه به اولویت ها و پهنه بندی آسیب پذیری منطقه مطالعاتی، تعادل بین طرح های توسعه و محیط امکان پذیرگردد.
چکیده انگلیسی:
Background and Objective The phenomenon of desertification is one of the serious ecological crises with extensive and long-term natural and human effects. Therefore, executive measures related to desertification control should be based on recognizing the current state of desertification of lands and its severity. On the other hand, the weakness of methods for measuring the intensity of desertification, always requires the need to provide new and quantitative methods. The need to address methods that can provide zoning based on strong logic and principles and rational theoretical foundations seems necessary in the field of desert management.
Material and Methodology: In this paper, it has been tried to do so by using the Fuzzy Topsis method. In this method, after determining and evaluating the effective indices by the fuzzy Delphi method and preparing the layer of work units, the data were fuzzy by the Chen and Huang methods. The fuzzy analysis process was performed on the data. Finally, a normalized fuzzy decision matrix was obtained, which within the framework of this matrix and by TOPSIS method, the intensity of desertification was estimated.
Findings: The obtained results showed that, 9.34%, 7.71% and 12.57% of the total study area are in the very high, high and relatively high class of desertification, and Desertification with low (46.57%) and medium (23.81%) has the highest share in the study area, respectively. The quantitative value of desertification intensity for the whole region was 0.262 located in relatively medium or III class.
Discussion and Conclusion: The study showed the efficiency and ease of application of fuzzy logic in assessing the intensity of desertification. The results of this study provide the possibility of planning to minimize desertification as a result of development projects, and can create conditions where a balance between development plans and the environment is possible based on the priorities and vulnerability zoning of the study area.
منابع و مأخذ:
Li, W., Yu, G., Shouyu, C., Huicheng, Z., 2006. Use of variable fuzzy sets methods for desertification evaluation. Computational intelligence, theory and applications. Polish Academy of Sciences, Vol 38, pp. 721-731.
Jafari, M., Hayati, J., Zargham, N. A., Azarniuond, H., Sofi, M., 2004. Review and assessment of desertification projects in Lamard plain. Geographical Research, Vol 50(36), pp.199-214. (In Persian)
UN (United Nations), 1994. United Nations Convention to Combat Desertification in Those Countries Experiencing Serious Drought and/ or Desertification, Particularly in Africa, UNEP/IPA, Nairobi,
Wang, X. D., Zhong, X. H., Liu, S. Z., Wang, Z. Y., Li, M. H., 2008. Regional assessment of environmental vulnerability in the Tibetan Plateau: Development and application of a new method, Journal of Arid Environment, Vol 72(10), pp. 1929-1939.
FAO-UNEP, 1984. Provisional Methodology for Assessment and Mapping of Desertification, Food and Agriculture Organization (FAO) Press, Rome, Italy.
European commission, 1999, Mediteranean Desertification and Land use (MEDALUS), MEDALUS office. London. UK.
Ekhtesasi, M. R., Mohajeri, S., 1996. Classification of the type and severity of desertification in Iran. The second national conference on desertification and desertification control methods, August 22-23, Kerman, Iran.
Ahmadi, H., Abrisham, E., Ekhtesasi, M. R., Jafari, M., Gokarian, A., 2005. Evaluation and mapping of desertification condition in FAKHRABAD-MEHRIZ region with the ICD and MICD models, BIABAN, Vol 10(1-1), pp. 37-50. (In Persian)
Abrisham, E., 2004. Evaluation and mapping of desertification condition in Fakhrabad--Mehriz region with the FAO-UNEP and MICD models, M.Sc Thesis. Faculty of Natural Resources, University of Tehran. Tehran, Iran. (In Persian)
Koohafkan, A. P., Lantieri, D., Nachtergaele, F., 2003. Land Degradation Assessment in Drylands (LADA) guidelines for a methodological approach. Food and Agriculture Organization (FAO), Rome, Italy. fao.org/ag/agl/agll/lada/bckgrdocs.stm
Ahmadi, H., Zehtabian, G. H., Jafari, M., Azarnivand, H., 2006. Iranian model of potential desertification assessment. Faculty of Natural Resources, University of Tehran, Tehran, Iran. (In Persian)
Sadeghiravesh, M. H., Ahmadi, H., Zehtabian, G. R., Rehayi Khoram, M., 2009. Development of the Numerical Taxonomy (MNT) model to assess desertification: an example of modeling intensity in central Iran, Philippine Agricultural Scientist, Vol 92(2), pp. 213- 227.
Sadeghiravesh, M. H., Khosravi, H., 2012. Zoning wind erosion potential risk in central Iran using modified numerical taxonomy model. American-Eurasian Journal of Agricultural & Environmental Sciences, 2012, Vol. 12 (1), pp. 91-99.
Sadeghiravesh, M. H., Ahmadi, H., 2014. Zoning desertification Potential risk in Abozydabad region by using modified numerical taxonomy model, Geographical Space, Vol 14(47), pp. 83-99. (In Persian)
Sadeghiravesh, M. H., Zehtabian, G. H., Tahmores, T., 2012. A vulnerability assessment of environmental issue to desertification risk (case study: Khezrabad region, Yazd). Journal of Watershed Management Research, Vol. 96 (1), pp. 75-87. (In Persian)
Sadeghiravesh, M. H., 2014. Zoning the potential of desertification hazard using the MADM approach and Shannon entropy model in the Khezrabad region, Yazd province. Iranian Journal of Soil Research, Vol. 28(3), pp. 572-588. (In Persian)
Sadeghiravesh, M. H., 2016. Zoning the potential of desertification hazard using the principal component analysis model in the Khezrabad region. Journal of geographic space, Vol. 16 (56), pp. 241-261. (In Persian)
Sadeghiravesh, M. H., 2020. Desertification hazard zoning using Multi-Attribute Utility Theory (MAUT) model, Environmental Recerches, Vol 10 (20), pp. 177-194. (In Persian)
Azar, A., Faraji, H., 2016. Science of fuzzy management. Fifth edition, Mehraban press, Tehran, Iran. (In Persian)
Wang, Y., Zhang, J., Guo, E., Sun, Z., 2015. Fuzzy comprehensive evaluation- based disaster risk assessment of desertification in Horqin Sand land, China, International Journal of Environmental Research and Public Health, Vol 12, pp.1703 –1725.
Koohbanani, H., Dashti Amirabad, J., Nikoo, S., Taya, A., 2017. Desertification-intensity zoning through Fuzzy-Logic approach: a case study of Deyhook-Tabas, Iran. Quarterly journal of Environmental Erosion Research, Vol 25(1), pp. 35-49. (In Persian)
Bidgoli, R. D., Koohbanani, H.,Yazdani, M., Dashti Amirabad, J., 2019. Risk assessment of land destruction and desertification severity using fuzzy method (case study: Miyandehi, Khorasan Razavi province), Iranian Journal of Range and Desert Research, Vol. 25(4), pp. 877-887. (In Persian)
Silakhori, E., Ownegh, M., Soleimani sardo, M., 2019. Assessment of risk and hazard desertification using Topsis-GIS method (case study: Bashtin, Sabzevar, Razavi province), Journal of Arid Regions Geographics Studies, Vol 9 (35), pp. 44-59. (In Persian)
Sadeghiravesh, M. H., Khosravi, H., Abolhasani, A., Ghodsi, M., Mosavi, A., 2021. Fuzzy logic model to assess desertification intensity based on vulnerability indices. Acta Polytechnica Hungarica, Vol 18(3), pp. 7-24.
Wang, Y., Zhang, J., Guo, E., Sun, Z., 2015. Fuzzy comprehensive evaluation- based disaster risk assessment of desertification in Horqin Sand land, China, International Journal of Environmental Research and Public Health, Vol 12, pp.1703 –1725.
Sharifi, M., Farahbakhsh, Z., 2016. Investigation about temperature and humidity anomalies between pleistocene and present times; reconstruction of climate condition using geomorphic evidence (case study: Khezrabad-Yazd). Physical Geography Researches, Vol 47(4), pp. 583-605. (In Persian)
Gharachelo, S., Ekhtesasi, M.R., Zareian Jahromi, M., Samadi, M. B., 2010. Evaluation of current condition of desertification using I.C.D Model, case study: Khezrabad, Yazd. Iranian journal of Range and Desert Reseach, Vol 17(3), pp. 402-420. (In Persian)
Sadeghiravesh, M. H., 2008. Investigation of effective desertification factors on environment degradation.D. Thesis, Islamic Azad University, Science and Research Branch, Tehran, Iran. (In Persian)
Sarkar, S., Parihar, S. M., A. Dutta., 2016. Fuzzy risk assessment modelling of East Kolkata Wetland Area: a remote sensing and GIS based approach, Environmental Modelling & Software, Vol 75 (C), pp.105 – 118.
Chen, S. J., Hwang, C. L., Beckmann, M. J., Krelle, W., 1992. Fuzzy multiple attribute decision making: methods and applications. Springer-Verlag Press, Secaucus, New Jersey, United States.
Chen, C., 2000. Extensions of the TOPSIS for group decision making under fuzzy environment. Fuzzy Setsand Systems, Vol 114(1), PP. 1-9.
Chen, C., Lin, C., Huang, S., 2006. A fuzzy approach for supplier evaluation and selection in supply chain management. International Journal of Production Economics, Vol 102, pp. 289-301.
Ahmadi, H., 2005. Applied geomorphology, desert, and wind erosion. University of Tehran press, Tehran, Iran. (In Persian)
Malchefski, Y., 2016. geographic information system and multi-criteria decision analysis, translated by Parhizgar, A and Ghafari Gilandeh, A., fourth edition, Samt press, Tehran, Iran. (In Persian)
Azar, A., Rajabzadeh, A., 2017. Applied decision making with an approach of multi-attribute decision making (MADM). Publication of Negah Danesh, Tehran, Iran. (In Persian)
Asgharpour, M. J., 2014. Multi-criteria decision making. Tehran University Publishing, Tehran, Iran. (In Persian)
Nadaban, S., Dzitac, S., Dzitac, I., 2016. Fuzzy TOPSIS: A General View. Procedia Computer Science, Vol 91, pp. 823 – 831.
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Li, W., Yu, G., Shouyu, C., Huicheng, Z., 2006. Use of variable fuzzy sets methods for desertification evaluation. Computational intelligence, theory and applications. Polish Academy of Sciences, Vol 38, pp. 721-731.
Jafari, M., Hayati, J., Zargham, N. A., Azarniuond, H., Sofi, M., 2004. Review and assessment of desertification projects in Lamard plain. Geographical Research, Vol 50(36), pp.199-214. (In Persian)
UN (United Nations), 1994. United Nations Convention to Combat Desertification in Those Countries Experiencing Serious Drought and/ or Desertification, Particularly in Africa, UNEP/IPA, Nairobi,
Wang, X. D., Zhong, X. H., Liu, S. Z., Wang, Z. Y., Li, M. H., 2008. Regional assessment of environmental vulnerability in the Tibetan Plateau: Development and application of a new method, Journal of Arid Environment, Vol 72(10), pp. 1929-1939.
FAO-UNEP, 1984. Provisional Methodology for Assessment and Mapping of Desertification, Food and Agriculture Organization (FAO) Press, Rome, Italy.
European commission, 1999, Mediteranean Desertification and Land use (MEDALUS), MEDALUS office. London. UK.
Ekhtesasi, M. R., Mohajeri, S., 1996. Classification of the type and severity of desertification in Iran. The second national conference on desertification and desertification control methods, August 22-23, Kerman, Iran.
Ahmadi, H., Abrisham, E., Ekhtesasi, M. R., Jafari, M., Gokarian, A., 2005. Evaluation and mapping of desertification condition in FAKHRABAD-MEHRIZ region with the ICD and MICD models, BIABAN, Vol 10(1-1), pp. 37-50. (In Persian)
Abrisham, E., 2004. Evaluation and mapping of desertification condition in Fakhrabad--Mehriz region with the FAO-UNEP and MICD models, M.Sc Thesis. Faculty of Natural Resources, University of Tehran. Tehran, Iran. (In Persian)
Koohafkan, A. P., Lantieri, D., Nachtergaele, F., 2003. Land Degradation Assessment in Drylands (LADA) guidelines for a methodological approach. Food and Agriculture Organization (FAO), Rome, Italy. fao.org/ag/agl/agll/lada/bckgrdocs.stm
Ahmadi, H., Zehtabian, G. H., Jafari, M., Azarnivand, H., 2006. Iranian model of potential desertification assessment. Faculty of Natural Resources, University of Tehran, Tehran, Iran. (In Persian)
Sadeghiravesh, M. H., Ahmadi, H., Zehtabian, G. R., Rehayi Khoram, M., 2009. Development of the Numerical Taxonomy (MNT) model to assess desertification: an example of modeling intensity in central Iran, Philippine Agricultural Scientist, Vol 92(2), pp. 213- 227.
Sadeghiravesh, M. H., Khosravi, H., 2012. Zoning wind erosion potential risk in central Iran using modified numerical taxonomy model. American-Eurasian Journal of Agricultural & Environmental Sciences, 2012, Vol. 12 (1), pp. 91-99.
Sadeghiravesh, M. H., Ahmadi, H., 2014. Zoning desertification Potential risk in Abozydabad region by using modified numerical taxonomy model, Geographical Space, Vol 14(47), pp. 83-99. (In Persian)
Sadeghiravesh, M. H., Zehtabian, G. H., Tahmores, T., 2012. A vulnerability assessment of environmental issue to desertification risk (case study: Khezrabad region, Yazd). Journal of Watershed Management Research, Vol. 96 (1), pp. 75-87. (In Persian)
Sadeghiravesh, M. H., 2014. Zoning the potential of desertification hazard using the MADM approach and Shannon entropy model in the Khezrabad region, Yazd province. Iranian Journal of Soil Research, Vol. 28(3), pp. 572-588. (In Persian)
Sadeghiravesh, M. H., 2016. Zoning the potential of desertification hazard using the principal component analysis model in the Khezrabad region. Journal of geographic space, Vol. 16 (56), pp. 241-261. (In Persian)
Sadeghiravesh, M. H., 2020. Desertification hazard zoning using Multi-Attribute Utility Theory (MAUT) model, Environmental Recerches, Vol 10 (20), pp. 177-194. (In Persian)
Azar, A., Faraji, H., 2016. Science of fuzzy management. Fifth edition, Mehraban press, Tehran, Iran. (In Persian)
Wang, Y., Zhang, J., Guo, E., Sun, Z., 2015. Fuzzy comprehensive evaluation- based disaster risk assessment of desertification in Horqin Sand land, China, International Journal of Environmental Research and Public Health, Vol 12, pp.1703 –1725.
Koohbanani, H., Dashti Amirabad, J., Nikoo, S., Taya, A., 2017. Desertification-intensity zoning through Fuzzy-Logic approach: a case study of Deyhook-Tabas, Iran. Quarterly journal of Environmental Erosion Research, Vol 25(1), pp. 35-49. (In Persian)
Bidgoli, R. D., Koohbanani, H.,Yazdani, M., Dashti Amirabad, J., 2019. Risk assessment of land destruction and desertification severity using fuzzy method (case study: Miyandehi, Khorasan Razavi province), Iranian Journal of Range and Desert Research, Vol. 25(4), pp. 877-887. (In Persian)
Silakhori, E., Ownegh, M., Soleimani sardo, M., 2019. Assessment of risk and hazard desertification using Topsis-GIS method (case study: Bashtin, Sabzevar, Razavi province), Journal of Arid Regions Geographics Studies, Vol 9 (35), pp. 44-59. (In Persian)
Sadeghiravesh, M. H., Khosravi, H., Abolhasani, A., Ghodsi, M., Mosavi, A., 2021. Fuzzy logic model to assess desertification intensity based on vulnerability indices. Acta Polytechnica Hungarica, Vol 18(3), pp. 7-24.
Wang, Y., Zhang, J., Guo, E., Sun, Z., 2015. Fuzzy comprehensive evaluation- based disaster risk assessment of desertification in Horqin Sand land, China, International Journal of Environmental Research and Public Health, Vol 12, pp.1703 –1725.
Sharifi, M., Farahbakhsh, Z., 2016. Investigation about temperature and humidity anomalies between pleistocene and present times; reconstruction of climate condition using geomorphic evidence (case study: Khezrabad-Yazd). Physical Geography Researches, Vol 47(4), pp. 583-605. (In Persian)
Gharachelo, S., Ekhtesasi, M.R., Zareian Jahromi, M., Samadi, M. B., 2010. Evaluation of current condition of desertification using I.C.D Model, case study: Khezrabad, Yazd. Iranian journal of Range and Desert Reseach, Vol 17(3), pp. 402-420. (In Persian)
Sadeghiravesh, M. H., 2008. Investigation of effective desertification factors on environment degradation.D. Thesis, Islamic Azad University, Science and Research Branch, Tehran, Iran. (In Persian)
Sarkar, S., Parihar, S. M., A. Dutta., 2016. Fuzzy risk assessment modelling of East Kolkata Wetland Area: a remote sensing and GIS based approach, Environmental Modelling & Software, Vol 75 (C), pp.105 – 118.
Chen, S. J., Hwang, C. L., Beckmann, M. J., Krelle, W., 1992. Fuzzy multiple attribute decision making: methods and applications. Springer-Verlag Press, Secaucus, New Jersey, United States.
Chen, C., 2000. Extensions of the TOPSIS for group decision making under fuzzy environment. Fuzzy Setsand Systems, Vol 114(1), PP. 1-9.
Chen, C., Lin, C., Huang, S., 2006. A fuzzy approach for supplier evaluation and selection in supply chain management. International Journal of Production Economics, Vol 102, pp. 289-301.
Ahmadi, H., 2005. Applied geomorphology, desert, and wind erosion. University of Tehran press, Tehran, Iran. (In Persian)
Malchefski, Y., 2016. geographic information system and multi-criteria decision analysis, translated by Parhizgar, A and Ghafari Gilandeh, A., fourth edition, Samt press, Tehran, Iran. (In Persian)
Azar, A., Rajabzadeh, A., 2017. Applied decision making with an approach of multi-attribute decision making (MADM). Publication of Negah Danesh, Tehran, Iran. (In Persian)
Asgharpour, M. J., 2014. Multi-criteria decision making. Tehran University Publishing, Tehran, Iran. (In Persian)
Nadaban, S., Dzitac, S., Dzitac, I., 2016. Fuzzy TOPSIS: A General View. Procedia Computer Science, Vol 91, pp. 823 – 831.