Journal of Spatial Analysis

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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
 
Introduction
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.
 
Conclusion
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
 
 
 
 

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Introducing the appropriate model of oak forest and drought relations

in Ilam province

Introduction
The forest ecosystems of the Zagros vegetation region have a very long history of exploitation in various
forms. The material of the Zagros vegetation region is Iranian oak. In recent years, a significant
proportion of oak forests have dried up or have experienced drought. Although the main cause of drought
in these forests has not been determined yet, in the preliminary studies, factors such as climate change,
increasing dust, increasing drought periods, pest infestation and disease, high user changes have been
cited as reasons for drought in the Zagros forests. (Hosseinzadeh and Pourhashemi, 1396). Iran's location
in the arid and semi-arid zone of the world (sub-tropical region) has often been associated with
fluctuations in climatic and atmospheric elements and under the influence of atmospheric currents,
synoptic patterns, irregularities in precipitation and temperature patterns (Rahmati, 2016; 1383).
Comparison of the effect of climatic variables on healthy masses and affected by the decline of oak in
Khorramabad city based on rainfall and temperature data using Pearson correlation coefficient, on annual
growth rings of oak trees Effectiveness of drought of oak trees from both series In general, healthy trees
have been more affected by monthly and seasonal temperatures and have shown the highest coefficient of
correlation with the temperature of the region (Naseri Karimvand et al., 2016). , And the Standardized
Rainfall Index (SPI) and the correlation between these two indicators in assessing and monitoring drought
in different areas of Isfahan province, the results showed that NDVI plant index can be a good alternative
to climatic indicators in drought assessment and monitoring) with the conclusion and colleagues, 2011:
79).
Data and Method
So from SPI and NDVI indicators and Moran index and statistical regression statistics and satellite
images of Modis and Landsat have used to analyze the relationship between dieback of Ilam forests and
happened drought in the region. The precipitation data of 93 rain gauge stations were analyzed during the
statistical period and according to the dry coefficients of SPI index, drought zoning layers of Ilam
province were prepared for two time series of 2000 to 2009 and 2010 to 2019. Greenery's raster layers
were prepared from Modis satellite imagery for the mentioned time series. The results of analysis of
Moran's statistical showed a significant correlation between the SPI index and the NDVI index in spatial
dimensions. By a simple random method, 143 points of oak dieback with dimension of 30 m 2 , which each
point was equivalent to a pixel-size, were recorded with a GPS device, and by simulating in satellite
imagery, the droplet layer of oak dieback was extracted.
Result and Discussion
What is debatable about the results of the implementation of methods for obtaining drought ranges and its
relationship with oak drought points or masses is that the results of the models show a statistically close
and direct relationship between drought and oak drought. . The general trend of oak drought and drought
in these two decades has been from the southeast to the northwest of Ilam province, with increasing
temperature and decrease in rainfall in the southern and eastern regions of the province and increasing
rainfall and decrease in temperature in the central and northwestern regions of Ilam province. The data of
the synoptic stations are consistent. Analysis of satellite imagery and declining greenery in the models
although the study was aimed at meteorological drought and precipitation fluctuations, but spatial
changes of arid points and masses in the province were adapted to field visits and human intervention,
especially in the southeast with agriculture. Under the rubble and the remnants of the dried trees, the ax
has been placed on the roots of these trees, and this trend is spreading in almost other parts of the arid
areas of the province. Therefore, due to the irregularity in the pattern of precipitation and temperature of
the research country (Rahmati, 2016; Zandi Army, 2004) and the effect of monthly and seasonal

نشریه تحلیل فضایی مخاطرات محیطی، سال نهم، شماره 1، بهار 1401 2
temperature on the growth and decline of oak trees in the study (Naseri Karimvand et al., 2016) and other
related research and The flooding situation in the basins of Ilam province, the rainfall, the impermeability
of the soil and their erosion, and finally the lack of moisture in the months before the oak trees grow in
the soil and the increase in temperature in the dry season, which leads to reduced humidity and eventually
greenery. Variables affecting oak drying in linear regression are not responsive, but more accurate results
will be obtained in multivariate regression, although regression analyzes are spatially empty, and X and Y
represent a one-way, quantitative analysis based on the number of dried trees with pixel counts. Drought
range is measured which this defect in SPI method despite its spatial and statistical analysis using Moran
statistical index due to non-compliance in the coefficients of this index with the range of changes in
Moran statistical analysis in statistical analysis is a more appropriate explanatory coefficient than The
regression models showed but at a lower level than the NDVI method it placed. The advantage of NDVI
method with Moran statistical analysis is the relationship between pixel and pixel, ie in spatial analysis,
all pixels that have green changes have been analyzed in the same domain of spatial changes with oak
trees. High results and higher statistical explanation coefficient were obtained than other models.
Conclusion
Although linear regression between extracted oak dieback points with SPI and Moran statistical indicators
was significant, but the relationship between NDVI index and Moran statistic has the effect of
independent variable of drought trend in spatial and temporal dimensions on the dependent variable
process of oak drought with spatial analysis. And nonlinear regression has a more appropriate and
accurate statistical significance and explanation. So this method as desirable method has been introduced
for analyzing of drought and oak dieback.
Keywords: Ilam province, oak forest drought, drought, Moran index