Volume 10, Issue 4 (12-2023)
Journal of Spatial Analysis Environmental Hazards 2023, 10(4): 209-224 |
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yousefi Z, Jahantigh H, Zolfaghari F. Assessment of desertification Severity in Morad Abad - Saravan Plain using Albedo-NDVI model. Journal of Spatial Analysis Environmental Hazards 2023; 10 (4) :209-224
URL: http://jsaeh.khu.ac.ir/article-1-3438-en.html
URL: http://jsaeh.khu.ac.ir/article-1-3438-en.html
1- Higher Education Complex of Saravan
2- Higher Education Complex of Saravan ,zol.farhad@gmail.com
2- Higher Education Complex of Saravan ,
Abstract: (1215 Views)
Investigation and monitoring of desertification in arid and semi-arid regions is a major concern for societies and governments due to its increasing rate. It is essential to identify areas at risk of desertification to manage and control this phenomenon in the shortest possible time and at minimum cost. The objective of this study is to create a map of desertification intensity in the MoradAbad plain of Saravan using the Albedo-NDVI model, which is based on remote sensing. Two Albedo and NDVI indicators were extracted from Landsat 8 satellite images in Erdas Imaging software after necessary corrections. A linear regression was formed between the two indicators by selecting 200 pixels corresponding to each indicator. Based on the slope coefficient of the line obtained from linear regression, the equation for determining the intensity of desertification was obtained. A map of the intensity of desertification was prepared based on Jenks’ natural refractive index. To evaluate the accuracy of the model, a clutter matrix was formed between 100 corresponding points. The results of linear regression between NDVI and Albedo indices showed that these two indices have a high negative correlation with each other (R = -0.85). The results of the desertification severity classification based on this model showed that 35% of the area is in the very severe class and only 5% of the area is without degradation. The model’s accuracy value was obtained with a kappa coefficient equal to 0.58, indicating good accuracy of the model.
Type of Study: Research |
Subject:
Special
Received: 2023/08/9 | Accepted: 2023/11/28 | Published: 2024/05/12
Received: 2023/08/9 | Accepted: 2023/11/28 | Published: 2024/05/12
References
1. آرامش میثم؛ ولی عباسعلی؛ رنجبر ابوالفضل. 1401. ارزیابی تغییرات پوشش سطح زمین و تخریب اراضی با استفاده از تکنیک سنجش از دور در شمال استان اصفهان (مطالعه موردی: کاشان، آران و بیدگل). تحقیقات مرتع و بیابان. 29(2): 146-160.
2. حبیبی علیرضا؛ شادفر صمد؛ صادقی معصومه. ۱۳۹۳. بررسی شدت بیابان‌زایی در رخساره‌های ژئومورفولوژی با استفاده از GIS در استان خوزستان. نشریه تحقیقات کاربردی علوم جغرافیایی (علوم جغرافیایی). 14(32): ۱۴۱-۱۵۹.
3. ذوالفقاری فرهاد؛ عبداللهی وحیده. 1401. تعیین مناسب ترین شاخص پوشش گیاهی برای تهیه نقشه شدت بیابان زایی در مناطق خشک به کمک تصاویر سنتینل. مدیریت بیابان. 10(1): 1-14.
4. رایگانی بهزاد؛ زهتابیان غلامرضا؛ براتی سوسن. نقدی بر مدل ایرانی پتانسیل بیابان زایی (IMDPA). بوم شناسی کاربردی. 2(4): 99-73.
5. رنجبر ابوالفضل؛ ولی عباسعلی؛ مکرم مرضیه؛ تاری پناه فریده. 1398. بررسی روند تغییرات زمانی- مکانی پوشش گیاهی و واکنش آن به عوامل محیطی در شمال استان فارس، ایران. سنجش از دور و GIS ایران. 11(4): 61-82.
6. شکوهی الهام السادات؛ زهتابیان غلامرضا؛ طویلی علی. ۱۳۹۱. پهنه‌بندی وضعیت بیابان‌زایی منطقه خضرآباد اله آباد دشت یزد با استفاده از مدل IMDPA و با تأکید بر معیارهای آب و خاک. نشریه مرتع و آبخیزداری. 65(4): ۵۱۷-۵۲۸.
7. کفاش عباس؛ روحی مقدم عین اله؛ افشاری اعظم؛ ذوالفقاری فرهاد. 1397. بررسی میزان تاثیر معیارهای اقلیم، پوشش گیاهی، فرسایش بادی و خاک در ارزیابی پتانسیل بیابن زایی با استفاده از GIS (مطالعه موردی: منطقه مرادآباد سراوان). پژوهش های نوین علوم جغرافیایی، معماری و شهرسازی. 2(14).
8. کوهبنانی حمیدرضا؛ دشتی امیرآباد جمال؛ نیکو شیما؛ تایا علی. ۱۳۹۶. پهنه‌بندی شدت بیابان‌زایی با استفاده از رویکرد منطق فازی (مطالعه موردی: دیهوک طبس). فصل‌نامه علمی - پژوهشی پژوهش‌های فرسایش محیطی. 7(1): ۳۵-۴۹.
9. نیک پور نورالله؛ نگارش حسین؛ فتوحی صمد؛ حسینی سید زین العابدین؛ بهرامی شهرام. 1397. پایش روند تغییرات شاخص پوشش گیاهی (NDVI)، یکی از مهمترین شاخص های تخریب سرزمین ( در استان ایلام). تحلیل فضایی مخاطرات محیطی. ۵(4): ۲۱-۴۸.
10. هاشم گلوگردی ساره؛ ولی عباسعلی؛ شریفی محمد رضا. 1400. بررسی روند بیابان زایی در مرکز استان خوزستان با استفاده از داده های سری های زمانی سنجش از دور. تحقیقات آب و خاک ایران. 52(11): 2857-2843.
11. Allen, R., Tasumi, M., Trezza, R., (2002), Surface Energy Balance Algorithms for Land. Advanced Training and User’s Manual Idaho Implementation.
12. Aramesh, M., vali, A. A., Ranjbar, A., (2022). Assessment of land cover change and desertification using remote sensing technology in north of Isfahan province (Case study: Kashan, Aran and Bidgol). Iranian Journal of Range and Desert Research, 29(2).
13. Cai, G., Du, M., Liu, Y., (2010), Regional drought monitoring and analyzing using MODIS data—a case study in Yunnan Province. In Proceedings of the 4th IFIP International Federation for Information Processing. 345: 243–251.
14. FAO/UNEP., (1980), Provisional methodology for assessment and mapping of desertification. Romp.
15. Guo, B., Zang, W.Q., Luo, W., Wen, Y., Yang, F., Han, B.M., Fan, Y.W., Chen, X., Qi, Z., Wang, Z., Chen, S. andYang, X., (2020), Detection model of soil salinization information in the Yellow River Delta based on feature space models with typical surface parameters derived from Landsat8 OLI image. Geomatics, Natural Hazards and Risk, 11(1): 288–300.
16. Habibi, A., Shadfar, S., & Sadeghi, M., (2014). investigation severity of desertification in geomorphology facies using with GIS in Khuzestan province. journal of Geographical Sciences, 14(32), 141-159.
17. Hadeel, A., Jabbar, MT., Chen, X., (2010), Application of remote sensing and GIS in the study of environmental sensitivity to desertification: a case study in Basrah Province, southern part of Iraq. Applied Geomatics, 2(3): 101-112. 27.
18. Hakimzadeh, M. A., (2014), Assessment of Desertification Risk in agricultural land in south of Iran. International journal of Advanced Biological and Biomedical Research, 2(3): 669-681.
19. Hashem Geloogerdi, S., Vali, A. A., Sharifi, M. R., (2022), Investigation of Desertification Trend in the Center of Khuzestan province Using Remote Sensing Time Series Data. 52(11): 2843-2857. (In Persian).
20. Jafari, R., Bakhshandehmehr, L., (2016), Quantitative mapping and assessment of environmentally sensitive areas to desertification in central Iran. Land Degrad. Dev. 27(2): 108-119.
21. Kaffash, A., Rouhimoghadam, E., Afshari, A., Zolfaghari, F., (2018), Investigation the effects of Climate, Vegetation, Wind Erosion and Soil Criteria on desertification Potential Using GIS (Case Study: Moradabad Saravan Regio). Journal of Geographical New Studies, Architecture and Urbanism. 2(14): 15-29. (In Persian).
22. Karnieli, A., Qin, Z., Wu, B., Panov, N., Yan, F., (2014), Spatio-Temporal Dynamics of Land-Use and Land-Cover in the Mu Us Sandy Land, China, Using the Change Vector Analysis technique. Remote Sensing. 6: 9316-9339.
23. Koohbanani, H., Dashti Amirabad, J., Nikoo, Sh., Taya, A., (2017), Desertification-Intensity Zoning through Fuzzy-Logic Approach: A Case Study of Deyhook-Tabas, Iran. Environmental Erosion Researches. 7(1): 35-49. (In Persian).
24. Lamchin, M., et al., (2017), Correlation between Desertification and Environmental Variables Using Remote Sensing Techniques in Hogno Khaan, Mongolia. Sustainability Journal. 9(581). doi:10.3390/su9040581.
25. Landsat 8 (L8) Data Users Handbook, June (2015), Approved By K. Zanter Lsds Ccb Chair Usgs. Version 1.0. https://www.greenpolicy360.net/mw/images/Landsat8DataUsersHandbook.pdf
26. Liu, F., Chen, Y., Lu, H. and Shao, H., (2017), Albedo indicating land degradation around the Badain Jaran Desert for better land resources utilization. Science of the Total Environment, 578: 67–73.
27. Ma, Z., Xie, Y., Jiao, J., & Wang, X., (2011), The construction and application of an Aledo-NDVI based desertification monitoring model. Procedia Environmental Sciences, 10: 2029-2035.
28. Nikpour, N., negaresh, H., Fotoohi, S., Hosseini, S, Z., Bahrami, S., (2019), Monitoring the trend of vegetation changes one of the most important indicators of land degradation (in Ilam province). Journal of Spatial Analysis Environmental Hazards, 5(4): 21-48.
29. Pan, J., Li, T., (20130, Extracting desertification from Landsat TM imagery based on spectral mixture analysis and Albedo- Vegetation feature space. Nat Hazards. 68: 915–927.
30. Piña, R. B., Díaz-Delgado, C., Mastachi-Loza, C. A., González-Sosa, E., (2016), Integration of remote sensing techniques for monitoring desertification in Mexico. Human and Ecological Risk Assessment. 22(6): 1323-1340
31. Ranjbar, A., Valia, A., Mokarramb, M., and Taripanahc, F., (2020), Analyzing of the spatio-temporal changes of vegetation and its response to environmental factors in north of Fars province, Iran. Journal of Remote sensing & GIS, 11(4): 61-82 (In Persian)
32. Rayegani, B., Zehtabian, G., Barati, S., (2013), Surveying of Iranian Model of Desertification Potential Assessment. Iranian Journal of Applied Ecology, 2(4): 73-99.
33. Shokoohi, E. S., Zehtabian, Gh. R., and Tavili, A., (2013), Study of desertification status using IMDPA model with emphasis on water and soil criteria (Case study: Khezr Abad - Elah Abad of Yazd - plain). Iranian Journal of Natural Resources, 65(4): 517-528.
34. UNCCD (United Nations Convention to Combat Desertification)., (2010), Recommendations and Conclusions of the African Regional Conference Preparatory to the First Session of the Committee for the Review of the Implementation of the United Nations Convention to Combat Desertification (UNCCD–CRIC1). Secretariat of the Convention to Combat Desertification: Windhoek, Namibia
35. 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, 12: 1703 –1725.
36. Wei, H., Wang, J., Han, B., (2020), Desertification Information Extraction Along the China–Mongolia Railway Supported by Multisource Feature Space and Geographical Zoning Modeling. IEEE Journal of selected topics in applied earth observations and Remote Sensing. 13: 392-402.
37. Ya, Z., Xue, S., WangWen, R.J., Chun, L.Z., Qing, L. and Jiao, L., (2018), Monitoring of aeolian desertification on the Qinghai-Tibet Plateau from the 1970s to 2015 using Landsat images. Sci Total Environ, 620:1648–1659.
38. Zolfaghari, F., Abdollahi, V., (2022), Determining the Most Suitable Vegetation Index for Mapping of Desertification Intensity in Arid Lands of Sistan Using Sentinel Images. Desert Management. 10(1): 1-14.
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