XML Persian Abstract Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Mohammadpour K, Saligheh M, Darvishi Bloorani A, Raziei T. Analysis and Comparing Satellite Products and Simulated of AOD in West Iran (2000-2018). Journal of Spatial Analysis Environmental Hazards 2020; 7 (1) :15-32
URL: http://jsaeh.khu.ac.ir/article-1-2938-en.html
1- Kharazmi University of Tehran , Kawe.m@hotmail.com
2- Kharazmi University of Tehran
3- Tehran University
Abstract:   (3242 Views)
Analysis and Comparing Satellite Products and Simulated
 Of AOD in West Iran (2000-2018)
Kaveh Mohammadpour, Ph.D. Student in Climatology, Kharazmi University of Tehran
Mohammad Saligheh, Associate Professor in Climatology, Kharazmi University of Tehran
Ali Darvishi Bloorani, Assistant Professor in RS & GIS, Tehran University
Tayeb Raziei, Assistant Professor in Climatology, SCWMRI, Iran
Dust are the main type of aerosols that affects directly and indirectly radiation budget. In addition, those affect the temperature change, cloud formation, convection, and precipitation. In recent years, the increase of different sensors and models has made possible to research the dust. The most important studies about dust analysis has been considered of Aerosol Optical Depth (AOD) as the most key parameter, which are based on the use of remote sensing technique and global models for analyzing the behavior and dynamics of dust in recent two decades. To achieve this, it has used of MODIS and MACC to study and identify the behavior of dust in the last two decades over west Iran.
Materials and methods
Areas in this study are Ilam, Kermanshah, Kurdistan, Lorestan and Hamedan provinces. The area has studied of two data series such as: first is MACC data with a spatial precision of 14 km2 and a 3-hour time scale; and other one is MODIS sensor production on the Terra satellite with a 10-square-kilometers resolution. In order to analyze the dust in the area in the period 2000 to 2018, statistical methods and simulation has used of the AOD parameter in MACC and MODIS. Before any processing, the data regraded to 0.2 × 0.2 degrees in order to compare the data. Then, the average daily AOD formed in a 22 × 23 matrix with 560 pixels that presented with 3653 × 560 for MACC during 2003 to 2012 and 6489 × 560 for MODIS during 2000-2018. Average of daily AOD obtained of MACC and MODIS calculated using of statistical equations. Then, the spatial distribution of AOD during the dusty months for synoptic stations and total province surface extracted using of R packages during the daily time series of the periods. Finally, the spatial distribution of the obtained AOD interpolated using the kriging function.
Results and Discussion
The average annual AOD obtained from Deep Blue algorithm from MODIS was less than MACC in all of the interested stations, except for Hamedan and Khorramabad stations, and provinces surfaces.
Correlation of AOD between MODIS and MACC shown that the correlations is high between model and sensor data (R2 = 59). In addition, the spatial correlation map shows 0.38 to 0.76 in which indicates a significant relationship between the MACC and MODIS pixels and the relationship is more in the western provinces of the area than the northeast of the region (Hamedan). The monthly comparison of the mean of AOD of the sensor and the model in the whole the area shows a highest correlation between the AOD in February and October.
The interpolation of the spatial distribution in the decade of the study (2003-2012) in MACC showed that the spatial variations of AOD is decreasing from the south of Ilam to the north of Kurdistan and reached the lowest level in the north of Kurdistan province. In general, the findings of annual and seasonal spatial distribution (dry period) of dust showed that MACC overestimated AOD compared to MODIS in the area. Nonetheless, the dust pattern in both of the sensor and the model increased from south to north. Although, the dust pattern is more regular in the sensor than the model. The spatial distribution of dust in Ilam, Kermanshah, and Kurdistan provinces in MODIS and MACC shows that dust in the southern point of the Ilam province has the highest concentration and the lowest is observed in the northeast of Kurdistan province. This spatial distribution of dust showed that dust in western provinces of the area follow latitudinal trend , in which is influenced by the high topography of Kermanshah and Kurdistan provinces and the proximity of Ilam province to dust sources in the distribution of dust intensity.
The results showed that there was a significant correlation between the sensor and the model and the coefficient was more than 0.4 in all months on the area. The findings of the annual amount of dust in MODIS showed that the amount of dust in the years 2000 to 2009 has increased in whole areas and from 2009 onwards, this annual trend has been reduced by 2018. MACC findings also showed that the AOD has been growing up in the period, although AOD amount have had a steep slope by 2010, but since 2010, dust has a steady slope. Therefore, West Iran has experienced two active (before 2010) and inactive (after 2010) periods in dust during an 18-years period on the area. The findings of MODIS and MACC in the study area indicate that the monthly distribution of dust from April to August has the highest concentration. In general, the annual and seasonal spatial distribution (months with the highest AOD) of dust indicates that the intensity of AOD in MACC was higher than MODIS in the area. Although the sensor and model has a roughly similar pattern and increases from south to north, but the trend in MODIS is more regular than MACC.
Keywords: Aerosol Optical Depth (AOD), MACC, MODIS, West Iran
Full-Text [PDF 1559 kb]   (1199 Downloads)    
Type of Study: Research | Subject: Special
Received: 2019/04/9 | Accepted: 2019/06/26 | Published: 2020/06/16

Add your comments about this article : Your username or Email:

Send email to the article author

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2024 CC BY-NC 4.0 | Journal of Spatial Analysis Environmental hazarts

Designed & Developed by : Yektaweb