Volume 10, Issue 2 (9-2023)
Journal of Spatial Analysis Environmental Hazards 2023, 10(2): 115-130 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Mohammadpour K, Khorshiddoust A M, Ahmadi G. Assessment of ground-based dataset and satellite remotely sensed images for analyzing of dust over western Iran. Journal of Spatial Analysis Environmental Hazards 2023; 10 (2) :115-130
URL: http://jsaeh.khu.ac.ir/article-1-3417-en.html
URL: http://jsaeh.khu.ac.ir/article-1-3417-en.html
1- PhD, Department of Climatology, faculty of Geographical Sciences, Kharazmi University, Tehran, Iran , kawe.m@hotmail.com
2- Professor, Department of Climatology, faculty of planning and Environmental Sciences, Tabriz University, Tabriz, Iran.
3- Master, Department of Climatology, faculty of Planning and Environmental Sciences, Tabriz University, Tabriz, Iran.
2- Professor, Department of Climatology, faculty of planning and Environmental Sciences, Tabriz University, Tabriz, Iran.
3- Master, Department of Climatology, faculty of Planning and Environmental Sciences, Tabriz University, Tabriz, Iran.
Abstract: (2153 Views)
Introduction
Dust storm is a complex process affected by the earth-atmophere system. The interaction between the earth and atmosphere is in the realm of the climatologists and meteorologists, who assess atmospheric and climatic changes, and monitor dust spread. Dust is the main type of aerosols which affects directly and indirectly radiation budget. In addition, altogether they affect the temperature change, cloud formation, convection, and precipitation. The most important studies about dust analysis have considered the use of remote sensing technique and global models for analyzing the behavior and dynamics of dust in recent two decades. To achieve such a goal, this paper has used MODIS and NDDI data to study and identify the behavior of atmospheric dust in half west of Iran.
Materials and methods
The western region of Iran is the study area. The data used in this study are divided into two categories: ground-based observations in 27 synoptic stations extracted from the Iran’s Meteorological Organization during the period (1998-2010) and satellite MODIS images during the first to fourth days of July 2008 as atmospheric dust extremes. Data was analyzed by using ArcGIS and ENVI software and NDDI index.
Results and Discussion
According to results, interpolated map for the number of dusty days during the study period over the western half of Iran showed that the scope of study area does not involve an equal system aspect quantity of occurrences. The number of dusty days occurrences increase from north toward south and the sites located in northern proportions of the area have experienced lower dust events. In contrast, maximum hotspots are occurring over southwestern sites such as: Ahvaz, Ilam, Boushehr and Shiraz. Therefore, principal offspring of dust input has been out of country boundaries and arrived at distant areas. Also, based on results obtained using satellite remote sensing images and applied NDDI index, maximum of intense dust cover is observed over Fars, Ilam, Boushehr and Ahvaz provinces on the first, second, third and fourth of July. However, the lowest rate of index situated in extent far such as: East and West Azerbaijan provinces. Thus, parts located on the north of the study area experienced less dusty days and the maximum dust cores were located in the southwestern (mostly Khuzestan). The long-term results were consistent with the daily average of NDDI index in the whole study area and indicated the hotspot areas (Ilam, Ahvaz, Omidyeh, Bushehr and Shiraz) during the first to fourth days of July 2008. However, the level of dust cover in the region has reduced when a wet and cloudy synoptic system passes over the central and northwestern parts of the study area.
Conclusions
The climatic interpolated map interpretation indicated that increase of dust concentration based on ground-based stations, which are consistent with dust concentration, is overshadowed by the latitude and proximity of sources of dust source in the Middle East. Also, the long-term climatic results of ground-based observations were consistent with the NDDI index calculated on dust extremes in the whole study area and in the southern areas (Ilam, Ahvaz, Omidyeh, Bushehr and Shiraz) during study days of July, 2008. Therefore, dust occurrence increases from north to south and the maximum hotspots over southwestern confirm the proximity of the south western region of Iran to deserts and sedimentary plains and their direct relationship with dust sources in the Middle East. These regions highlight the volume and expansion of dust outbreaks, which were well detected due to the satellite imagery and spectral characteristics of MODIS for monitoring changes in the dust phenomenon.
Overall, the use of satellite remotely sensed data/images not only cover the ground-based observation datasets gap to identify, highlight, and analyse the dust phenomenon, but also takes a much more geographical approach in analysing environmental hazards such as dust. It is also suitable for studies of atmospheric compounds such as atmospheric aerosols.
Dust storm is a complex process affected by the earth-atmophere system. The interaction between the earth and atmosphere is in the realm of the climatologists and meteorologists, who assess atmospheric and climatic changes, and monitor dust spread. Dust is the main type of aerosols which affects directly and indirectly radiation budget. In addition, altogether they affect the temperature change, cloud formation, convection, and precipitation. The most important studies about dust analysis have considered the use of remote sensing technique and global models for analyzing the behavior and dynamics of dust in recent two decades. To achieve such a goal, this paper has used MODIS and NDDI data to study and identify the behavior of atmospheric dust in half west of Iran.
Materials and methods
The western region of Iran is the study area. The data used in this study are divided into two categories: ground-based observations in 27 synoptic stations extracted from the Iran’s Meteorological Organization during the period (1998-2010) and satellite MODIS images during the first to fourth days of July 2008 as atmospheric dust extremes. Data was analyzed by using ArcGIS and ENVI software and NDDI index.
Results and Discussion
According to results, interpolated map for the number of dusty days during the study period over the western half of Iran showed that the scope of study area does not involve an equal system aspect quantity of occurrences. The number of dusty days occurrences increase from north toward south and the sites located in northern proportions of the area have experienced lower dust events. In contrast, maximum hotspots are occurring over southwestern sites such as: Ahvaz, Ilam, Boushehr and Shiraz. Therefore, principal offspring of dust input has been out of country boundaries and arrived at distant areas. Also, based on results obtained using satellite remote sensing images and applied NDDI index, maximum of intense dust cover is observed over Fars, Ilam, Boushehr and Ahvaz provinces on the first, second, third and fourth of July. However, the lowest rate of index situated in extent far such as: East and West Azerbaijan provinces. Thus, parts located on the north of the study area experienced less dusty days and the maximum dust cores were located in the southwestern (mostly Khuzestan). The long-term results were consistent with the daily average of NDDI index in the whole study area and indicated the hotspot areas (Ilam, Ahvaz, Omidyeh, Bushehr and Shiraz) during the first to fourth days of July 2008. However, the level of dust cover in the region has reduced when a wet and cloudy synoptic system passes over the central and northwestern parts of the study area.
Conclusions
The climatic interpolated map interpretation indicated that increase of dust concentration based on ground-based stations, which are consistent with dust concentration, is overshadowed by the latitude and proximity of sources of dust source in the Middle East. Also, the long-term climatic results of ground-based observations were consistent with the NDDI index calculated on dust extremes in the whole study area and in the southern areas (Ilam, Ahvaz, Omidyeh, Bushehr and Shiraz) during study days of July, 2008. Therefore, dust occurrence increases from north to south and the maximum hotspots over southwestern confirm the proximity of the south western region of Iran to deserts and sedimentary plains and their direct relationship with dust sources in the Middle East. These regions highlight the volume and expansion of dust outbreaks, which were well detected due to the satellite imagery and spectral characteristics of MODIS for monitoring changes in the dust phenomenon.
Overall, the use of satellite remotely sensed data/images not only cover the ground-based observation datasets gap to identify, highlight, and analyse the dust phenomenon, but also takes a much more geographical approach in analysing environmental hazards such as dust. It is also suitable for studies of atmospheric compounds such as atmospheric aerosols.
Type of Study: Research |
Subject:
Special
Received: 2023/12/29 | Accepted: 2023/09/1 | Published: 2023/09/1
Received: 2023/12/29 | Accepted: 2023/09/1 | Published: 2023/09/1
References
1. احمدی ملاوردی مجید، جباری ایرج و امان اله فتح نیا. 1399. شناسایی، ارزیابی و مدیریت خاستگاه هایگردوغبار در غرب ایران. پژوهشهایجغرافیایطبیعی، 52(3): 445-465.
2. آرامی، سید عبدالحسین، اونق مجید، محمدیان بهبهانی علی، اکبری مهری و علیرضا زراسوندی .1397. تحلیل مطالعات مخاطره گردوغبار در جنوب غرب ایران در دوره 22 ساله (1996 – 2017)، مجله تحلیل فضایی مخاطرات محیطی، 5(1): 39-66.
3. اکبری، مهری و فرحناز فرحبخشی .1395. تحلیل سینوپتیکی و شبیهسازی حرکت طوفان های شدید گردوغبار (مطالعه مورد: جنوب غرب ایران)، فصلنامه ی علمی-پژوهشی فضای جغرافیایی، 16(55): 273-291.
4. ترکاشوند، محمدقاسم .1397. مدل سازی گردش منطقه ای جو در رخداد شدیدترین توفان ریز گرد بهاره غرب ایران، مجله مخاطرات محیط طبیعی، 5(2): 19-34.
5. جبالی، عاطفه؛ زارع، محمد ؛ اختصاصی، محمدرضا و رضا جعفری .1398. ارزیابی عملکرد الگوریتم های آشکارساز طوفان های گردوغبار در مناطق خشک (مطالعه موردی استان یزد)، مجله علمی-پژوهشی مهندسی اکوسیستم بیابان، 8(23): ۸۵ـ.۱
6. رنجبر سعادت آبادی، عباس، میهن پرست، مجتبی و فائزه نوری . 1395. بررسی پدیده گردوغبار در غرب ایران از دیدگاه هواشناختی (مطالعه بلند مدت و کوتاه مدت)، مجله علمی و ترویجی نیوار، 93-92.
7. زینالی، بتول .1395. بررسی روند تغییرات فراوانی روزهای همراه با توفان های گردوغباری در نیمه غربی ایران، مجله مخاطرات محیط طبیعی، 5(7): 87-100.
8. ساری صراف، بهروز، علی اکبر رسولی، آذر زرین و محمد سعید نجفی .1396. شبیه قائم سامانه های گردوغبار زا در ارتباط با سامانه های همدید و توپوگرافی در غرب ایران، پژوهش های جغرافیای طبیعی، 49(2) : 189-169
9. محمدپور، کاوه؛ سلیقه، محمد؛ درویشی بلورانی، علی و طیب رضیئی .1399. واکاوی و مقایسه تولیدات ماهوارهای و شبیهسازی شده AOD در تحلیل گردوغبارهای غرب ایران (2000 - 2018)، تحلیل فضایی مخاطرات محیطی، ۷ (۱) :۱۵-۳۲.
10. Akbary, M., Farahbakhshi, M. 2015. Analyzing and Tracing of Dust Hazard in Recent Years in Kermanshah Province, Int. J. Environ. Res., 9(2):673-682.
11. Albaqami, S. 2019. Spatial and temporal analysis of dust storms in Saudi Arabia and associated impacts, using Geographic Information Systems and remote sensing, PhD thesis, King Abdulaziz University.
12. Albaraka, R., Lakshmi, V., 2019. Monitoring Dust Storms in Iraq Using Satellite Data, Sensors, 19: 3687; doi:10.3390/s19173687.
13. Arkian, F., Nicholson, S. E. 2018. Long-term variations of aerosol optical depth and aerosol radiative forcing over Iran based on satellite and AERONET data, Environ Monit Assess 190: 1-15.
14. Ashrafi, K., Shafiepour-Motlagh, M., Aslemand, A., Ghader, S. 2014. Dust storm simulation over Iran using HYSPLIT, Journal of Environmental Health Science and Engineering :1-9.
15. Bangert, M., Nenes A., Vogel B., Vogel H., Barahona D., Karydis V. A., Kumar P., Kottmeier C., Blahak U. 2012. Saharan dust event impacts on cloud formation and radiation over Western Europe, Atmos. Chem. Phys., 12: 4045–4063.
16. Barkan. J, Kutiel. H, Alpert. P. 2004. Climatology of source in North Africa and the Arabian Peninsula, Based on TOMS Data. Original Article, Indoor Built Environ 2004, 13: 000-000.
17. Chang, SC., Chou, CCK., Chen, WN., Lee, CT. 2010. Asian dust and pollution transport—a comprehensive observation in the downwind Taiwan in 2006. Atmos Res 95: 19–31.
18. Chin, M., Diehl, T., Tan, Q., Prospero, J. M., Kahn, R. A., Remer, L. A., Yu, H., Sayer, A. M., Bian, H., Geogdzhayev, I. V., Holben, B. N., Howell, S. G., Huebert, B. J., Hsu, N. C., Kim, D., Kucsera, T. L., Levy, R. C., Mishchenko, M. I., Pan, X., Quinn, P. K., Schuster, G. L., Streets, D. G., Strode, S. A., Torres, O., Zhao, X.-P. .2014. Multi-decadal aerosol variations from 1980 to 2009: a perspective from observations and a global model, Atmos. Chem. Phys., 14: 3657–3690, doi:10.5194/acp-14-3657-2014.
19. Desouza, Nirmala D., Baby, S., Qureshi, Muhammad S..2011. Evolutionary characteristics of a dust storm over Oman on 2 February 2008, Meteorol Atmos Phys, 114:107–121.
20. Ghazal, Nawal K. .2020. Monitoring dust storms using normalized difference dust index (NDDI) and brightness temperature variation in Simi arid areas over Iraq, Iraqi journal of physic, 2020: Vol: 18, No: 10: 68-75
21. Ghedira. H., AL Rais. A., AL Suwaidi. A. 2009. Developing a new automated tool for detecting and monitoring dust and sand storms using Modis and Meteosat SEVIRI- MSG data. IGARSS.pp. 905-908.
22. Goudie, A. S, Middleton, N. J. 2001. Saharan dust storms: nature and consequences. Earth- Science Reviews, 56: 179-204.
23. Guleria, RP., Jagdish, CK., Pan SR., Nand, LSh., Harinder KTh., Pitamber PD., Mahavir S. 2011. The assessment of aerosol optical properties over Mohal in the northwestern Indian Himalayas using satellite and ground-based measurements and an influence of aerosol transport on aerosol radiative forcing, Meteorol Atmos Phys 113:153–169.
24. Guo, N., Liang, Y., Wang X. 2005. Quantitative Identification of Dust and Sand Storm Using MODIS Data. Key Laboratory of climate changes and reduced disaster, Institute of Arid Meteorology, CMA, Lanzhou,730020, China 0-7803-9050-4/05/$20.00 ©2005 IEEE.
25. Haiping, L., Xiong, L., Zhuang, D. 2003. Research Progress and Future Development of Remote Sensing Monitoring on Sand-dust Disaster in China. Progress In Geography, 22(1): 45-52.
26. Han, T., Li. Y., Han, H., Zhang, Y, Wang. Y. 2005. Automatic detection of dust storm in the northwest of China using decision tree classifier based on MODIS visible bands data. Geoscience and Remote Sensing Symposium, Proceedings of IGARSS, IEEE International, 5 (25-29): 3603-3606.
27. Klingmüller, K., Pozzer, A., Metzger, S., Stenchikov, G. L., Lelieveld, J. 2016. Aerosol optical depth trend over the Middle East, Atmos. Chem. Phys., 16: 5063–5073, doi:10.5194/acp-16-5063- 2016.
28. Kutiel, H., Furman, H. .2003. Dust Storm in the Middle East: Sources of origin and their temporal characteristics. Environmental Problems Affecting Health Original Paper, Indoor Built Environ 2003; 12: 419-426.
29. Lee, Y. C., Yang, X., Wenig M. 2010. Transport of dusts from East Asian and non- East Asian sources to Hong Kong during dust related events 1996- 2007. Atmospheric Environment XXX: 1-11.
30. Li, X., Song W. .2010. Dust Storm Detection Based on Modis Data. Liaoning Technology University, No. 47 Zhonghua Road, Fuxin, LIAONING, lee_xian@126.com.
31. Mao, K.B., Ma, Y., Xia, Wendy, L., Chen, Y., Shen, X.Y., He, T.J., Xu, T.R..2014. Global aerosol changes in the last decade: An analysis based on MODIS data, Atmospheric Environment, 94: 680-686.
32. Mei, DI., Xiushan, LU., Lin. SUN., Ping, W. 2008. A dust-storm process dynamic monitoring with multi-temporal Modis data. Geomatics College, Shan Dong University of Science and Technology, Shan Dong Qingdao, 266510, China.
33. Middleton, N. J, Chaudhary, QZ. 1988. Severe Dust Storm at Karachi, 31 May 1986. Weather; 438: 298–301.
34. Mohammadpour, K., Sciortino, M., Saligheh, M., Raziei, T., Darvishi Boloorani A. 2021, Spatiotemporal regionalization of atmospheric dust based on multivariate analysis of MACC model over Iran, Atmospheric Research, 249, Available online 17 October 2020, 105322. [DOI:10.1016/j.atmosres.2020.105322.]
35. Nabavi S.O., Haimberger L., Samimi C. 2016. Climatology of dust distribution over West Asia from homogenized remote sensing data, Aeolian Research 21: 93–107. http://dx.doi.org/10.1016/j.aeolia.2016.04.002
36. Namdari, S., Valizade, KK., Rasuly A.A., Sari Sarraf, B. 2016. Spatio-temporal analysis of MODIS AOD over western part of Iran, Arab J Geosci: 9:191.
37. Natsagdorj, L. D, Jugder, S. Y. 2002. Analysis of Dust Storm Observed Mongolia During 1937-1999. p12.
38. Notaro, M., Yu, Y., Kalashnikova, O. V. 2015. Regime shift in Arabian dust activity, triggered by persistent Fertile Crescent drought, J. Geophys. Res.-Atmos., 120: 10229–10249, doi:10.1002/2015JD023855.
39. Orlovsky. L, Orlovsky. N, Durdyev. A. 2005. Dust storm in Turkmenistan. Journal of Arid Environments 60: 83-97.
40. Park, SU., Anna, C., Lee, E-H., Park, M-S., Song X.2010. The Asian Dust Aerosol Model 2 (ADAM2) with the use of Normalized Difference Vegetation Index (NDVI) obtained from the Spot4/vegetation data, Theor Appl Climatol 101:191–208.
41. Qian, W., Quan, L., Shi, S. .2002. Variations of the dust storms in China and its climatic control. Journal of Climate, 15: 1216–1229.
42. Qu. J., Hao. X., Kafatos, M., Wang. L. 2006. Asian dust storm monitoring combining Terra and Aqua Modis SRB measurments. Geosciences and Remote Sensing Letters, 3 (4): 484-486.
43. Qu. J., Hao. X., Wang. W., Wang, L., Kafatos. M. 2005. A Study of African Dust Storm and Its Effects on Tropical Cyclones over Atlantic Ocean from Space. CEOSR/SCS, George Mason University, 4400 University Drive, Fairfax, VA 22030, USA NASA/GSFC/614.4, Greenbelt, MD 20771, USA, 0-7803-9050-4/05/$20.00 ©2005 IEEE.
44. Sanchao, L., Qinhuo, L., Maofang, G. 2006. On Asian dust storm in China by combining daytime and nighttime Terra and Aqua Modis data. IEEE Geomantic and Information Science of Wunan University, 31 (20): 1051-1054.
45. Shigong, W., Wang, J., Zhou, Z. , Shang, K. 2005. Regional characteristics of three kinds of dust storm events in China, Atmospheric Environment, 39: 509-520.
46. Taghavi. F., Asadi. A. 2008. The Persian Gulf 12th April 2007 dust storm: observation and model Analysis, EUMETSAT Meteorological Satellite Conference, Darmstadt, Germany, 8-12 September, EUMETSAT P-52.
47. Taheri Shahraiyni, H., Karimi, Kh., Habibi Nokhandan, M., Hafezi Moghadas, N. 2014. Monitoring of dust storm and estimation of aerosol concentration in the Middle East using remotely sensed images, Arab J Geosci , DOI 10.1007/s12517-013-1252-3.
48. Thuraya, M. S., Al-Dashti H. 2011. Optical and physical characterization of “Iraqi freedom” dust storm, a case study, Theor Appl Climatol 104:123–137.
49. Wang, X. M., Dong, Z. B., Zhang, J. W., Liu, L. C. 2004. Modern dust storms in China: an overview. Journal of Arid Environments, 58: 559–574.
50. Ye, D. Z., Chou, J. F., Liu, J. Y. .2000. Causes of sand storm weather in northern China and control measures. Acta Geographic Sinica, 55(5): 513–521.
51. Yong X. 2009. Detection of Smoke and Dust Aerosols Using Multi-Sensor Satellite Remote Sensing Measurements. A dissertation Phd, George Mason University.
52. Yue, H., He, C., Zhao, Y., Ma, Q., & Zhang, Q. 2017. The brightness temperature adjusted dust index: An improved approach to detect dust storms using MODIS imagery. International Journal of Applied Earth Observation and Geoinformation, 57, 166–176. doi: 10.1016/j.jag.2016.12.016.
Send email to the article author
| Rights and permissions | |
 | This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
