Dust time series analysis using long-term monthly images of MERRA2 satellites and Sentinel5 images in Google Earth Engine
الموضوعات :
Mohamad Reza Dehestani Ardakani
1
(PhD Student in Geography and Urban Planning, Yazd Branch, Islamic Azad University, Yazd, Iran)
الکلمات المفتاحية: Vegetation, dust, East of Iran, satellite imagery, Wind stress,
ملخص المقالة :
Background and objective:The dust phenomenon is one of the important climatic hazards in arid and semi-arid regions of the world, which causes human and financial losses to humans. In recent decades, due to long-term droughts, the incidence of dust has increased. Considering that Iran is one of the centers affected by particulate matter and the damage caused by this phenomenon affects our country, special attention should be paid to the issue of increasing particulate matter. The purpose of this study is to investigate changes in the dust, vegetation density, and wind conditions in the geographical region of south and southeast of Iran and its neighbors, Afghanistan and Pakistan.Materials and methods:Through NASA Giovanni online modeling and the use of MERRA-2 satellite imagery to study dust and wind stress and the MODIS-Terra satellite to study vegetation. During the last 40 years from 1980 to 2020, the state of dust and wind stress was examined. Vegetation has also been studied over the past 20 years and 10-year periods from 2000 to 2020. Dust monitoring from June 2018 to February 2021 was also analyzed using Google Earth Engine, using long-term monthly images of Sentinel5 satellites.Results and conclusion:The results show that with increasing the amount of dust, the percentage of vegetation, increases, and decrease in wind stress. Although plants and wind have had a good trend in these years, this increase in dust can be due to lower water levels and increased dust collection sites as a result of not observing the water level of wetlands.
Adib, A., Oulapour, M., & Chatroze, A. (2018). Effects of wind velocity and soil characteristics on dust storm generation in Hawr-al-Azim Wetland, Southwest Iran. Caspian Journal of Environmental Sciences, 16(4), 333-347.
Akhlaq, M., Sheltami, T. R., & Mouftah, H. T. (2012). A review of techniques and technologies for sand and dust storm detection. Reviews in Environmental Science and Bio/Technology, 11(3), 305-322. https://doi.org/10.1007/s11157-012-9282-y,
Babaee Fini, O., Safarrad, T., & Karimi, M. (2016). Analysis and Identification of Synoptic Patterns of Dust Storms in the West of Iran. Journal of Geography and Environmental Hazards, 5(1), 105-120.
Prospero, J. M., Ginoux, P., Torres, O., Nicholson, S. E., & Gill, T. E. (2002). Environmental characterization of global sources of atmospheric soil dust identified with the Nimbus 7 Total Ozone Mapping Spectrometer (TOMS) absorbing aerosol product. Reviews of geophysics, 40(1), 2-1. https://doi.org/10.1029/2000RG000095,
Karimi, M., & Shakouhi Razi, K. (2012). Interaction between Atmospheric Circulation and Land Cover in the Mechanism of Creation of Summertime Dust Storms in Middle East (Case Study, July 2009). Physical Geography Research Quarterly, 43(78), 113-130.
Bayat, R., Iranmanesh, F., & Kazemi, R. (2021). Investigation of dust storms effect on vegetation cover of Shadegan wetland. Environment and Water Engineering, 7(1), 1-13.
Jamali, A. A., & Ghorbani Kalkhajeh, R. (2020). Spatial Modeling Considering valley’s Shape and Rural Satisfaction in Check Dams Site Selection and Water Harvesting in the Watershed. Water Resources Management, 34(10), 3331-3344. https://doi.org/10.1007/s11269-020-02616-2
Jamali, A. A., & Ghorbani Kalkhajeh, R. (2019). Urban environmental and land cover change analysis using the scatter plot, kernel, and neural network methods. Arabian Journal of Geosciences, 12(3), 100. https://doi.org/10.1007/s12517-019-4258-7
Jamali, A. A., Zarekia, S., & Randhir, T. O. (2018). Risk assessment of sand dune disaster in relation to geomorphic properties and vulnerability in the Saduq-Yazd Erg. Applied Ecology and Environmental Research, 16(1), 579-590. https://doi.org/10.15666/aeer/1601_579590
Parsasyrat, L., & Jamali, A. A. (2015). The effects of impermeable surfaces on the flooding possibility in Zarrin-Shahr, Isfahan Municipal Watershed. J Appl Environ Biol Sci, 5(1), 28-38.
Kim, S. W., Yoon, S. C., & Kim, J. (2008). Columnar Asian dust particle properties observed by sun/sky radiometers from 2000 to 2006 in Korea. Atmospheric Environment, 42(3), 492-504. https://doi.org/10.1016/j.atmosenv.2007.09.055,
Koohestani, B., Darban, A. K., Mokhtari, P., Darezereshki, E., & Yilmaz, E. R. O. L. (2020). Geopolymerization of soil by sodium silicate as an approach to control wind erosion. International Journal of Environmental Science and Technology, 1-12. https://doi.org/10.1007/s13762-020-02943-2,
Kurosaki, Y., & Mikami, M. (2005). Regional difference in the characteristic of dust event in East Asia: Relationship among dust outbreak, surface wind, and land surface condition. Journal of the Meteorological Society of Japan. Ser. II, 83, 1-18. https://doi.org/10.2151/jmsj.83A.1,
Magidi, J., & Ahmed, F. (2019). Assessing urban sprawl using remote sensing and landscape metrics: A case study of City of Tshwane, South Africa (1984–2015). The Egyptian Journal of Remote Sensing and Space Science, 22(3), 335-346. https://doi.org/10.1016/j.ejrs.2018.07.003,
Mei, D., Xiushan, L., Lin, S., & Ping, W. A. N. G. (2008). A dust-storm process dynamic monitoring with multi-temporal MODIS data. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 37.
Nascetti, A., Di Rita, M., Ravanelli, R., Amicuzi, M., Esposito, S., & Crespi, M. (2017). Free global dsm assessment on large scale areas exploiting the potentialities of the innovative google earth engine platform. International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences, 42. https://doi.org/10.5194/isprs-archives-XLII-1-W1-627-2017,
Pourhashemi, S., Boroghani, M., Zangane Asadi, M. A., & Amir Ahmadi, A. (2015). Analysis relation of vegetation cover on the number of dust event in Khorasan Razavi using geographic information system and remote sensing. Journal of RS and GIS for Natural Resources, 6(4), 33-45.
Qian, Z. A., Song, M. H., & Li, W. Y. (2002). Analyses on distributive variation and forecast of sand-dust storms in recent 50 years in North China. Journal of Desert Research, 22(2), 106-111.
Reynolds, R. L., Yount, J. C., Reheis, M., Goldstein, H., Chavez Jr, P., Fulton, R., ... & Forester, R. M. (2007). Dust emission from wet and dry playas in the Mojave Desert, USA. Earth Surface Processes and Landforms: The Journal of the British Geomorphological Research Group, 32(12), 1811-1827. https://doi.org/10.1002/esp.1515,
Sashikkumar, M. C., Selvam, S., Karthikeyan, N., Ramanamurthy, J., Venkatramanan, S., & Singaraja, C. (2017). Remote sensing for recognition and monitoring of vegetation affected by soil properties. Journal of the Geological Society of India, 90(5), 609-615. https://doi.org/10.1007/s12594-017-0759-8,
Sharma, A. R., Kharol, S. K., & Badarinath, K. V. S. (2009). Satellite observations of unusual dust event over North-East India and its relation with meteorological conditions. Journal of Atmospheric and Solar-Terrestrial Physics, 71(17-18), 2032-2039. https://doi.org/10.1016/j.jastp.2009.09.010,
Tan, M., Li, X., & Xin, L. (2014). Intensity of dust storms in China from 1980 to 2007: A new definition. Atmospheric environment, 85, 215-222. https://doi.org/10.1016/j.atmosenv.2013.12.010,
