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Mahmood Khosravi, Samad Fotohi, Soliman Pirouzzadeh,
Volume 2, Issue 4 (1-2016)

Iran is among 10 top potential countries of occurrence of natural hazards in the world and from among 35 natural hazards, so far about 30 hazards have occurred in Iran(Negaresh and Latifi,2009). One of the different types of natural hazards which every year causes a lot of damage particularly in arid and arid regions of the world is the existence of sandy hills(Omidwar,2006); sandy hills are mostly created in coastal regions of most seas and oceans. These hills are the result of mutual effects of waves, marine currents, wind and sediments available in coastal regions. They are implemented with components of the coastal environment and construct the eco-systemic bases in which there are valuable collection flora and fauna(Kidd, 2001). The studied region is among the deserts near Gulf of Oman coasts. Sand on the coast are with marine origins and by getting far from the sea, sandy hills, in addition to having marine origins, have land origins. In some seasons of the year, particularly in summers and falls in which Monsoon winds start blowing up, the range of the movement of running sands is more towards rural regions in such a way that annually, a large part of sands covers residential areas, farmlands, road & building facilities, and infrastructural facilities in the rural areas of the west of Zarabad and left behind heavy damages and losses. The aim of this study is the detection of temporal-spatial changes in sand dunes in the Gulf of Oman coastal region. In addition, trend and severity of this hazard and the effects of climatic and environmental factors that intensified dimensions of risk were considered.

The present study, to achieve the mentioned objective is an applied study and in terms of research, a method is a descriptive-analytical one. To collected data, it uses library-documentary as well as survey studies in the rural areas of the west of Zarabad. After that, to investigate the changes of the degree of displacement in dunes of the studied region in the 23 year time period (1991-2014), GPS and the Enhance Thematic Mapper Plus (ETM+) images of the Landsat Satellite 7 and 8 with the spatial resolution of 15 and 30 m were used. The satellite images were used in this study with time intervals of 10 and 13 years were related to years of 1991, 2001, and 2014 in August respectively and they were extracted from USGS.The ENVI software and Geographic Information System were used for images processing and interpretation. The geometric and radiometric corrections were applied on images according to standard procedures. Finally, classification and related calculation were performed.

The conducted studies in the region based on the interpretation of satellite images and survey studies indicated that changes in the available users in the region, the top increases for dunes occurred in 1991 as 561.25 km2, in 2001 as 568.10 km2, and in 2014 as 575.45 km2. In fact, it has experienced a growth as 17.198 km2. The vegetation whose area covers 32 km2 in 1991, in 2014 has reached an area with 45km2 and increased as 1.6% compared to the previous period. In 1990 to 2014, the area of the user which has been changed in favor of dunes, includes 0.108 km2 vegetation, 10.60 km2 stream sediment, and 264.35 km2 arid lands. Therefore, dunes move with high speed after each storm and during these displacements, a lot of damages are imposed on farmlands, facilities, and rural settlements. Investigating the degree of imposed damages indicates that annually, a large area of regions such as villages, roads, and facilities are influenced by running sands, which this trend can cover more regions in future years. The degree of displacement of dunes, according to the analyses conducted during the research period(1990-2014), has been so great that it has caused the burial of a large number of villages, infrastructure, farmland and roads and resulted in the unemployment of a large number of farmers in the region. Imposed damages to rural settlements have not been less than agricultural sectors and facilities. Therefore, due to the movement of running sands during recent years, 15 villages have been at the exposure of damages in such a way that compensation of these damages has imposed heavy costs, and consumed a lot of time on the shoulder of the society. As a result, the movement of dunes towards studied villages, i.e. Biahi, Mashkouhi, Abd, Rig Mostafa, Kalirak, Kerti, and Gati which are in the coastal regions, and Sohraki, Ganjak, Tanban, Zahrikar, and Kaidar which are located at far distances from the coast suffer from the highest amount of dunes and are considered as the most critical regions in terms of the movement of sand dunes. The results also showed that the important factors on severity and development of these critical regions are: a shortage of precipitation , loose and fine-grained sediments, low slope, no obstructions against the marine winds and high frequencies of winds and storms in this region.On the other hand, the lack of any varieties of vegetation on dunes, as well as the drought of recent years confirms spatial-temporal changes in the sand dunes towards the study area.

In this research, the hazards due to running sands in the West region of Zarabad (Baluchestan) were studied. The results from satellite image interpretation and field works were showed that the greatest change of land cover in recent years was related to sand hills. The total areas of sand dunes in 1990 are 561 km²,in 2001 these area increases to 568 km² and finally in 2014 reached to 578.5 km².The average growth rate is about 0.76 km² per year. The  landcover change from river sediments and barren land to sand dunes, during this period are estimated 10 and 264 km².

The storm and marine winds moving  sand dunes and running sands from coastal regions to rural settlements,farmland,Roads and other Infrastructures of the region. This hazard was just too much damage like  buried villages, the destruction of roads and unemployment and migration of farmers. The number of evacuated villages are 15 cases that some of these villages is located in the coastal region(Biahi,Mashkohi,Abd,Kalirak……..) and others in inland(Soharaki,Ganjak,Tanbalan,…..).

This is the manifestation of crisis and instability in the rural communities that creating important obstacles to development and it is triggered vulnerable rural development was decreased.

Saeid Hamzeh, Zahra Farahani, Shahriar Mahdavi, Omid Chatrobgoun, Mehdi Gholamnia,
Volume 4, Issue 3 (9-2017)

As a result of climate change and reduction in rainfall during the last decade, drought has become big problem in the world, especially in arid and semi-arid areas such as Iran. Therefore drought monitoring and management is great of important. In contrast with the traditional methods which are based on the ground stations measurements and meteorological drought monitoring, using the remote sensing techniques and satellite imagery have become a useful tool for spatio-temporal monitoring of agricultural drought. But using of this technique and its results still need to be evaluated and calibrated for different areas.
The aim of this survey is to study the spatial and temporal patterns of drought using remote sensing and the regional meteorological data in the Markazi province. For this purpose, the MODIS satellite data between the years of 2000-2013 have been used to monitor and derived vegetation indices. Drought indices based on satellite data including the Normalized Difference Vegetation Index (NDVI), Vegetation Condition Index (VCI), Temperature Condition Index (TCI), Temperature Vegetation Dryness Index (TVDI), and Soil Water Index (SWI) were obtained from the MODIS satellite data for the period of study for different temporal scales (seasonal, biannual and annul).Then, correlation between obtained results from satellite data and standardized precipitation index (SPI) have been analyzed in all time periods.
Results show that study area has a low to medium vegetation cover. According to the results, the climate situation of the study area is more compatible with the seasonal results of the VCI, and VCI was selected as the best indicator for agricultural drought monitoring in the study are. The obtained results from the applying of VCI over the area show the drought condition in 2000 and 2008 and the wetness in 2009 and 2010 during the study period.

Marzieh Taabe, Abolfazl Ranjbarfordoei, Sayed Hojat Mousavi, Mohammad Khosroshahi,
Volume 4, Issue 4 (1-2018)

The correct management in natural ecosystems is not possible without knowledge of the health in its sectors. Vegetation is the most significant sector in ecosystem that has important role in its health. Resilience is one of the defining features of health vegetation The term resilience was first introduced in the study of ecological systems and demonstrates the ability of the ecosystem to maintain its performance in the face of environmental disorders. A resilience-based system is not only equipped with a disorder adjustment mechanism but also has the potential to benefit from changes in a way that lead to creating an opportunity for development, innovation, and updating. Therefore, when a change occurs, the resilience provides the needed conditions for restarting and reorganization. If this goes beyond disturbing forces, the system will have the power to return to the maximum vegetation density with the least erosion effects, otherwise the system will be vulnerable to the change that was created and could already be controlled.
This research was done in part of North east of South Khorasan province (arid climate) with the aim of quantifying vegetative resilience on behalf of ecosystem health in response to drought occurrences and long-term precipitation changes, as environmental disturbances. Therefore first, using daily precipitation data from 15 meteorological stations around the study area, their annual precipitation was extracted and was standardized by Standard Precipitation Index (SPI) over the course of thirty years (1986 - 2015). Then, the SPI index data in 15 stations were interpolated by ArcGIS software based on Inverse Distance Weighted (IDW) method and dry, wet and normal years was estimated in the study region for each year. On the other hand, from archive of satellite images of Landsat 5 and Landsat 7, an image was created for each year in study period, between 15 June and 15 July, with permanent coverage at the best of growth. Following the necessary corrections for satellite images, the average Transformed Normalized Difference Vegetation Index (TNDVI) was obtained of each image by ENVI software. Finally, effected of precipitation changes on mean TNDVI was assessed and vegetation resilience was stabilized whit selected of sever time period samples based on four effective parameters (Amplitude, Malleability, Damping and Hysteresis).

Comparison of annual precipitation variations in the thirty-year time series (1986 -2015) indicated two approximate wet and dry periods in study area. The wet period is related to the first fourteen years of the time series (1986-1999) and the dry period is related to the last sixteen years (2000-2015). In this term, severe precipitation incidents with different intensities were occurred in the study area including one case of very intense precipitation (1986), one case of intense precipitation (1991) and two cases of moderate precipitation (1996 and 1992). Also, four drought incidents were occurred including one case of intense drought (2001) and three cases of moderate drought (1987, 2006 and 2008). All precipitations (wet years) are related to the first half and most droughts are related to the second half of the studied period. In this study for fixing of vegetation resilience in study area and for calculating of its parameters, In addition to the thirty-year time series selected sever time sections. in the whole study series (1986 - 2015), maximum of mean TNDVI (49.37 %) was in 1986 (reference), the lowest mean TNDVI (43.58%) was in 2010, The year effect of the decrease precipitation and drought, and mean TNDVI in 2015 was 44.28 %. Amount of parameters amplitude, malleability and damping are respectively 5.79, 0.7 and 5.09, and hysteresis was zero (%). The result of this case showed that the vegetation has moved towards the reference state (Resilience) but has not reached to amount of reference vegetation. The most specific cases for vegetation resilience happened from 1986 to 1996 (wet period) and 2003- 2009 time sector (dry period). In the first time section amount of amplitude and malleability were 0.64 %, damping was zero and hysteresis was 0.25%. The result of this case showed that not only the vegetation was returned to the reference state but also was increased to the reference (Cross reference).So despite the reduced rainfall and occurrence of sever occurrences of drought in dry period, hysteresis parameter (0.05 %) observed in 2003- 2009 time sector too that confirmed clearly vegetation health in study area whit dry climate. 

Awareness of the health status of the vegetation and its response to long-term precipitation changes and environmental disorders, such as drought occurrence, ensure the success of the managerial plans for renewable natural resources. The present study is the second study on quantifying the vegetation resilience and the first study under dry climatic conditions in Asia (an average annual precipitation of 160 mm) conducted in Iran by calculating four factors related to resilience, and is the first study that has presented the factor hysteresis in the calculations. Despite continuous of difficult condition, the native vegetation of the study area has been able to return the reference state not only by resolving the disorder relatively, but also it has experienced hysteresis stage. A set of quantitative calculations showed despite reduced annual precipitation and drought events, vegetation has been able to maintain its resilience, which indicates the health of the vegetation in the studied ecosystem. With the presence of such amazing protective and consistent mechanisms in the vegetation of arid regions, it is possible to maintain and restore these regions by proper managerial plans.


Amir Saffari, Amir Saffari, Jalal Karami,
Volume 5, Issue 1 (6-2018)

Investigation about the influence of land-cover and land use changes on soil erodibility potential, case study: Gharesou, Gorganrood
Land use and land cover (LUC) change associated with climatic and geomorphologic conditions of the area have an accelerating impact on the land degradation. Natural as well as human-induced land use land cover change (LUCC) has significant impacts on regional soil degradation, including soil erosion, soil acidification, nutrient leaching, and organic matter depletion. Since the last century, soil erosion accelerated by human activities has become a serious environmental problem. It has a manifold environmental impact by negatively affecting water supply, reservoir storage capacity, agricultural productivity, and freshwater ecology of the region. In recent years, many researchers have highlighted the environmental consequences of soil erosion.
Soil erosion estimation at a regional scale is influenced by the complexity of the soil erosion process and the availability of data describing the soil erosion factors. In the last decade, regional and national level assessments of soil erosion were carried out using different approaches, ranging from indicator or factor-based approaches to process-based models. However, the revised universal soil loss (RUSLE) and its modifications are still widely used because of its simplicity and a greater availability of input parameters.
Gharesou basin is one of the sub-basins of Gharesou, it suffered from severe erosion in some areas over the past years. This erosion has occurred for different reasons and one of them is land use change and weak management of water and soil resources. The purpose of this research is to investigate the effects of land-cover changes on the potential of soil erosion in Gharesou Basin, a sub-basin of Gorganrood, in Golestan province. For this, we have employed RUSLE Model and used landsat satellite images from the sensors of TM, ETM, and OLI for 1985, 2000, and 2015. The potential soil erosion in this study was estimated using RUSLE model, which can be described using following equation:
A = R × K × LS × C × P
where A is amount of soil erosion calculated in tons per hectare per year, R is rainfall factor , K is soil erodibility factor , L is slope length factor, S is slope steepness factor, C is cover and management factor, and P is erosion control practice factor. To run the RUSLE model in GIS, first, rainfall raster layer, soil, slope, Digital Elevation Model, and also layers of soil protection range were created. Each of the involved factors was calculated in separate units in the basin level. In this research, Gharesou basin was analyzed based on raster network data with 30 meters cell size, because, from one hand it's small
enough to show heterogeneity of the basin and on the other hand, it matches pixel dimensions of landsat satellite images.
The results of land-cover changes have revealed a decrease in dense forest areas, low forest areas and the mixture of orchard, forest and pastures in a thirty years period. According to the results of RUSLE, changes of the classes indicate a general trend to the soil loss in the basin. Therefore, Gharesou basin is a basin with increasing soil erosion potential. In the plain and coastal plain areas of the basin, that is the mainly cultivated area, the amount of erosion is different from the other areas, and soil loss process is decreasing. It's due to the changes of cultivation method from traditional to modern, increase of irrigated farming area, choosing more environmentally friendly plants, and also, increase in the area of cities and villages from 7.14 percent to 29.04 percent during 30 years. In the study classes, for output of RUSLE model, in every 3 years of study, the maximum area relates to the classes of 100 to 200 Ton per year that is more seen in the mountainous regions. In these regions, all factors except vegetation are toward soil loss. Also, during 30 years, the amount of dense vegetation decreased from 34.56 to 31.55. In fact the only factor in protecting soil in (prone to erosion) areas has given its place to less effective vegetation, so, the area of this region has increased and Gharesou basin is in danger of soil loss in mountainous and forest parts. Also, areas with more than 200 Ton in hectare, with the lowest amount, have had a tangible increase during 30 year of study and its amount has increased from 11.74 to 12.50. These areas are usually located in mountainous parts with no vegetation. Also, the average of soil erosion potential estimated in Gharesou basin for 1985, 2000 and 2015 is 102.02, 103.11, and 103.76 (ton per hectare per year). This amount was found in the sub-basins too and except the sub-basin 4 located in coastal plain areas of the basin, with farming use, the amount of other sub-basins is increasing. According to the results of study, mountainous parts of Gharesou basin, has the most damage due to the accumulation of involved factors in the potential increase of soil loss. So, the necessity of watershed management is observed. Also modification of cultivation pattern and soil conservation training in farming lands of foothills and hillsides are required.
Keywords: RUSLE Model, soil erosion, Gharesou, Remote Sensing, land-cover changes

Sayedenegar Hasheminasab, Reza Jafari,
Volume 5, Issue 3 (12-2018)


Trend of increasing natural resource degradation in many parts of the world, is a serious threat to humanity. Desertification is one of the manifestations of the damage that has already suffered as a scourge of many countries, including developing countries are. At present, remote sensing is one of technologies with timeliness data and accuracy suitable for monitoring land use changes in the areas of natural resources. Desertification monitoring and tracking changes, which seeks to desertification that the change could be for any reason and also collect and analyze data from activities, projects, plans and programs that may desertification range condition assessment and reporting to provide them. The purpose of this study was to evaluate changes in land use on desertification monitoring using remote sensing techniques to the agricultural lands around zayandeh rood in the East region of Isfahan.

materials and methods

In this study, the image sensor of TM to date 1987, 1998, ETM+ to date 2002 and  OLI to date 2014 related to the Landsat 5,7 and 8 to obtain the land use map used and then was performed radiometric and geometric correction.Then was used the color combination, the main component analysis, vegetation index and supervised classification method for detection of complications and the maximum likelihood algorithm as the most appropriate method for supervised classification in classes 9 of land cover. After production the land use map correctness evaluating operations with calculation error matrix and then was performed detection operations for these maps. Finally, for desertification of monitoring, land use years 27 changes around zayandeh rood  using the comparison method  is paid changes to identify and was obtained the area of each use.

Results and discussion

For investigate the the process of desertification, land use changes in the period of 27 years. In order to select the appropriate bands in supplying the best color composite satellite images and operations classified in order to reconstruct the images, index optimization factor was applied. The results of accuracy assessment shows that For all the images above the 80% overall accuracy and Kappa statistics indicate that almost 80 percent. Generally good agreement between the classification and classes of users on the ground there. By comparing bit images specified land use changes in the period of 27 years, riverbank has the greatest changes during this period. So during these 27 years the river high Zayandehrood degradation, which could be due to the expansion of agricultural activities in rivers. This degradation is generally represents gradual drying of the river and go surrounding cultivated by farmers. This degradation process in the margins of the river and the gradual drying of the river towards the desertification situation in the region shows.


In year 27 time period, Zayandeh Rood neighboring rivers has changed dramatically, so 86.43% of neighboring rivers was destroyed due to the expansion of agricultural activities vicinity of the river and drying river. Another significant changes, loss of agricultural land is notable such that 64% of this land has been reduced compared to 1987. Of reasons for the loss of agricultural land will be noted the region drought and Zayandeh Rood river drying up and Low rainfall, land use change and the proximity of the region desert. Also, has become about hectares 324.99 Of salt marsh lands to agricultural land. Moreover, the developed urban areas to its development contributed agricultural land and rangeland. Bayer lands around Zayandeh Rood Increase and also in region of rangeland lands Low and has increased Bayer lands  and somewhat until agricultural land which inappropriate use of this land shows in order to the agricultural. That this is the desertification progress in the region. Generally desertification process in this period years 27 has been a growing trend.Therefore multi-temporal and multi-spectral satellite data for enhancement, especially for desertification monitoring was large capability and classification after comparison method is helpful for determine the type and direction of changes occurred. Since the development of desertification, limited to a small area and is not recommended range is therefore more effective, in addition to work sheets, other sheets around the area also evaluate the process of desertification is to allow for planning and management in the field of combating desertification exist.

Mr Dana Rostami, Dr Seyed Asaad Hosseini,
Volume 5, Issue 3 (12-2018)

 Dust is one of the environmental hazards and atmospheric phenomena familiar to residents of the southern and southeastern parts of the country. Which each year causes a lot of damages to various sectors such as environment, agriculture, health, transportation, facilities, and so on. Therefore, in this research, we investigated and identified the sources of dust in the area, the intensity and frequency of dust, its governing patterns and dust-free areas during the 30-year statistical period (1984-1984). The research method is a combination of statistical, synoptic and remote sensing analysis. The data used include the hourly data of 22 synoptic stations (8 times per 24 hours), CDC1 data up to 2006, and then GDAS data, temperature, wind direction and wind speed, geopotential height at different levels. In selecting the studied days, it was tried to select the selected samples with a duration of three days and more, the spatial expansion of at least 4 stations with horizontal vision less than 1000 meters. For this purpose, were used the characteristics of the 11.3 and 12-micrometric wavelengths of the wavelengths were used to visualize the dust on the MODIS images from the ENVI 5.2 software environment, to track the wind direction from the GDAS data in the HYSPLIT software environment and to study the maps of various atmospheric levels from Temperature, wind speed, wind speed and geopotential heights were used from GRADS software and weather data stations. The annual frequency of the occurrence of days with dusty phenomena in the study area showed that during the statistical period of 1984-2013, a total of 11616 days with dust was recorded with the 06 code for south and southeast of Iran at the stations study. Most days with the dust event at Zabol Station with 1136 days and the lowest occurrence occurred at Bandar Abbas Station with 171 days during the studied period. In general, the annual survey of the data shows that the phenomenon of dust in the stations study in the past has been high and very high; however, in recent years, it has been expanding more and more than the past, and has been growing. The results of the monthly and seasonal surveys showed that the summer and the months of June, July, August and May are the most frequent and most frequent, with a peak of 1000 meters, respectively, and December have the lowest dust incidence and Zabul and Zahedan station

Koohzad Raispour, Yones Khosravi,
Volume 7, Issue 2 (8-2020)

Air pollution is one of the most important problems in many countries in the world, which, besides the environmental damage and human health, imposes many adverse social and economic impacts. Therefore, considering the vital importance of air and the rising course of increasing the contaminating agents in recent decades, it is necessary to study the elements and their pollutant gases in order to be aware of the existing situation and to adopt the necessary solutions. The phenomenon of atmospheric air pollution in Iran, as part of the world's atmosphere, is one of the goals of the industrial revolution, which has been increasing day by day as industrialization; population growth and urbanization have grown dramatically. Carbon monoxide (CO) is a colorless, odorless, and tasteless gas that is slightly less dense than air. In the atmosphere, it is spatially variable and short lived, having a role in the formation of ground-level ozone. Carbon monoxide consists of one carbon atom and one oxygen atom, connected by a triple bond that consists of two covalent bonds as well as one dative covalent bond. Carbon monoxide is produced from the partial oxidation of carbon-containing compounds; it forms when there is not enough oxygen to produce carbon dioxide (CO2), such as when operating a stove or an internal combustion engine in an enclosed space.
Carbon monoxide is one of the most dangerous air pollutants. Due to its importance, many techniques and methods have been used to monitor the Earth's atmosphere in recent years. as well as, the use of satellite data has become widespread because of the availability and availability of features such as spatial, temporal and spatial resolution. In this study, the data from Aqua / AIRS Carbon Monoxide data can be used to study the rate and trend of carbon monoxide gas changes in the atmosphere of the entire world, including Iran.The relevant data in NetCDF format, with one-day and 13.5 x 13.5km spatial resolution of during the 16-year statistical period (2003-2018), was extracted from ttps:// using ArcGIS software And Grads are processed, represented, analyzed.
The results indicate that the amount of carbon monoxide was reduced during the monthly and annual time series. Of course, monthly and seasonal variations have been impressive. Monthly, the highest concentration of carbon monoxide in January, February and March, and the lowest in August, September and October. Among the seasons, the highest and lowest levels of carbon monoxide were observed in the seasons of winter and summer, respectively. In spatially, the highest amount of surface carbon monoxide with an average of 150 ppb above the city of Tehran and the coastal area of the Caspian Sea and its lowest level with an average of 115 ppb on the Zagros heights was observed.
The results clearly show a clear picture of the dispersion of carbon monoxide gas in the horizontal and vertical direction of Iran's atmosphere. Based on the results obtained from the monthly carbon monoxide data collected during the statistical period (2003-2018), conducted in a three dimensional and regional area extending to the geographical area of Iran, The average surface carbon monoxide of more than 150 ppb above the Tehran metropolitan area and northern coast of Iran is less than 115 ppb on Zagros altitudes. Among other results, there are significant differences between the monthly carbon monoxide average in the surface troposphere of Iran, so that in the twelve months, the highest amount of carbon monoxide was observed in cold months and the lowest was observed in the warm months of the year, respectively. Seasonally, the highest level of seasonal carbon monoxide has been observed in winter and its seasonal season has peaked in summer. The results of vertical profiles (vertical aspect) of carbon monoxide changes in Iran's atmosphere in line with latitude and longitude indicate the maximum carbon monoxide concentration at lower levels of barley so that the maximum amount of carbon monoxide in the Iranian atmosphere is concentrated in the lower levels and Rarely exceeds the level of 250 hPa. Also, the results indicate that the rate of carbon monoxide emissions in the atmosphere of Iran has decreased, so that in the last years of the statistical period, about 30% of the amount of carbon monoxide in the atmosphere of Iran has been reduced, compared to the early years of the statistical period.
Key words: Air Pollution, Carbon Monoxide, AIRS, Remote Sensing, Iran.
Hamed Haidari, Dariush Yarahmadi , Mostafa Karampour,
Volume 7, Issue 3 (11-2020)

Dust phenomenon is one of the climatic fronts that is often formed in the dry and desert regions of the world, and is known as a natural hazard. Occurrence of walnuts causes dust, damage to the environment and the occurrence and exacerbation of respiratory, cardiac, air traffic and threats of tourism, agriculture and so on. Also, in the health section of the compounds in calcium dust, more than 2.5 g of it causes the appearance of kidney stones, and blood vessels. Iron causes swelling of the conjunctiva and retinal inflammation, as well as the syndrome. Magnesium causes depression, depression and dizziness of the individual. Short-term breathing of aluminum leads to coughing and irritation of the lungs and prolonged breathing causes damage to the lungs. In recent years, the identification of dust source areas has attracted the attention of researchers in numerous studies, and have introduced various areas around the world as the main source of generous production. The country of Iran, and in particular the Western and Southwestern logic of Iran, is constantly experiencing the phenomenon of dust and its problems. In the west of Iran, desert areas are located in the deserts of southern Iraq, Saudi Arabia and far away from Syria and North Africa. The geographic location of the southwestern part of Iran and its proximity to these deserts have led to a frequent occurrence of the phenomenon of dwarfs, which are different throughout the year.
In this research, two categories of data were used: the first group is data on climatic elements or unstable elements.
The annual climatic layers of the region were used for a 30-year statistical period of 2016- 2016. Measurement data on the temperature of surface temperature was obtained from a MODIS sensor in a 17-year statistical period (2000-2016). The second group of data layers and information on the ground factors or factors were stable. The layers of these variables included:
  1. The digital elevation layer of the area with a precision spacing of 30 meters from this layer was used as the elevation layer of the area.
    2. The slope of the region, in percent, which is the layer derivative of the digital elevation model and derived from the same specifications of the DEM layer.
    3. The surface layer of the surface layer that was taken from the MODIS surface coating product
    4. Layer of vegetation on the surface of the earth, which was also taken from the 1 kilogram MODIS vegetation cover
    5. Soil layer that was prepared by the country's water and soil organization
 The method of conducting analytical and statistical research in which the main objective is the determination of areas conducive to the formation or expansion of dust cores. In this regard, the establishment of land-based and climate databases is the first stage of work, after forming the required databases, the formation of information layers These data are in the GIS environment. In order to form these layers, the interpolated models in GIS were used and the optimal model was selected in such a way that less error values ​​were obtained. After forming the existing layers, we classified and weighed each layer based on the AHP weighting algorithm. Finally, due to the assigned weights, the overlaying of the weights of the layers in the GIS environment was obtained and finally a potential capability map of the formation of local dust collectors in Lorestan province was obtained.
 The rainfall factor is the most important and most important factor in determining the areas susceptible to becoming dusty. The weight of this factor in determining and identifying areas susceptible to dusty cores was equal to 239%. Vegetation factor, which was prepared using the NDVI indicator of the MODIS product, was the second factor in the development of dust-prone areas with a weight of 199.99. Relative humidity factor is the third factor or component that influences the determination of suitable areas to become the local focus of dust. The weight of this factor is equal to 0.15. The wind speed factor is in the fourth place in terms of determining the areas susceptible to dust. The relative weight of this factor is estimated at 116.0. As shown in Table 14, slope and elevation factors are the least important factors that can play a role in the production and development of dusty centers. The weight of these factors in identifying areas susceptible to formation of dusts is 0.024 and 032.2, 0 is detected. The calculated incompatibility index for this weighing is as high as 4.8, as shown in Table 15, which indicates that the contradiction between the offered weights of indices relative to each other is less than the allowed threshold (12).
 Neutbay expressed the highest concentration of areas susceptible to dust mites in the eastern region, especially the northeast of the province, which includes the cities of Azna and Aligudarz. There are also parts of this category in the southern regions of the study area, including the cities of Poldokhtar and Rumshagan. In the central regions of the province as well as in the northwest of the province including the Khorramabad, Delfan, Dynasty and Dorood districts this class is not observed. In the southern parts of the city of Kohdasht, small parts of the floor of the potential centers of dust are also observed. This flooring has the most risk of becoming a dusty focus. The power source of many of the province's dusty incidents can also be said to be areas where some of them are currently potential sources of dust. Since they have played a major role in the identification and detection of these areas, rainfall and vegetation cover, these areas are exactly in line with parts of the province, which, firstly, have a mean rainfall of less than 250 mm, and the density of vegetation is less than 2 / 0 (NDVI index), which represents a very poor vegetation and, in fact, a lack of viable vegetation. In terms of land use, these areas, or inferior land, or very rangelands, are very weak.

Mr Mohammad Hossein Aalinejad, Pro Saeed Jahanbakhsh Asl,
Volume 8, Issue 1 (5-2021)

Simulation of runoff from Gamasiab basin snowmelt with SRM model
Snow cover in a basin affect its water balance and energy balance. So, snow cover variation is a major factor in climate change of a region. Study of temporal variation of snowmelt and snow water equivalent depth is very important in flood forecasting, reservoir management and agricultural activities of an area. In the most of the mountainous basins of the country, information on snow cover were not available. Also, the number of meteorological stations in high altitude areas do not match with information needed for snowmelt simulation. Therefore, indirect methods such as the analysis of satellite images to obtain the needed parameters for simulation is necessary, which is the one of the most effective methods in estimation of runoff originated from snow. Using the NOAA satellite data for zoning the snow cover of area started firstly in the USA since the 1961 and continuous until today (spatial and temporal resolution of satellite images increased by starting the MODIS work).
Gamasiab River is one of the important branches of Karkheh basin. Its basin area is about 11040 km2 between latitude 47 degrees 7 minutes to 49 degrees 10 minutes east and latitude 33 degrees 48 minutes 4 degrees 85 minutes north. The altitude of this basin is 1275 to 3680 meters above sea level. In this study, for simulation of runoff originated from melting snow, firstly snow cover in the basin of Gamasiab in 2014 to 2017 calculated by using the satellite images of MODIS in the google earth engine system. Also, air temperature and precipitation data of synoptic stations in the area of study and daily stream flow discharges of Polechehr hydrometric station, from November of 2014 to July of 2017 was used. Then, weather and snow cover area included as the input of SRM for simulation of snowmelt runoff. To obtain the information needed to the model, physiographic characteristics of the basin including the area and different classes of height obtained from the Arc-Hydro and Hec_GeoHMS in DEM maps of GIS software. Then the snow cover areas obtained from the images of MODIS in daily interval that obtained by google earth engine system.
Using the digital elevation map (DEM) and the accession of the Arc-Hydro and Hec_GeoHMS software of GIS, firstly flow direction map plotted. Secondly flow accumulation and stream flow network maps plotted, and by introducing the basin output to the program (Polechehr hydrometric station) borders of the basin identified and classification of the basin accomplished according to the three distinct height classes. Monitoring the snow surface cover during the daily time interval showed that the area covered with snow in winter season. This area decreases as the air temperature increases. The SRM model simulated the snowmelt of Gamasiab basin with good accurately, in which, the percent of volume error or Vd was lose than 2% and the R was above 0.9.
The results of this research showed that the using the images of MODIS yields a reasonable estimation of the snow cover area of Gamasiab with local of data. Also simulation results showed the high capability of the SRM in snowmelt runoff of the area under study. Result showed that the coefficient of determination and volume percent of error of model was 0.93 and %0.3 for 2014-2015 and it was 0.9 and 3.33 for 2015-2016 years, respectively. The results of this study, was in consistent with the previous studies fading in which in addition of model's parameters, physiographic characteristics, basin play a major role in the accuracy of the simulation. According to the calculated and observed runoff diagram, in both years of study, peak temperatures begin in March, as the weather warms and the snow melts, and will continue until April. Considering the snow cover, it can be concluded that the main runoff of March Peak is related to snowmelt, but with the change in the shape of precipitation from snow to rain and the warming of the weather, April peak is related to rain. Regardless of acceptable simulation results of the model, the lack of snow survey station in the study area, (yield the model to face with difficulty) in process. To overcome this shortcoming, we used the presumptions of the model and recommended values of the model.
Keywords: MODIS; Remote sensing; Runoff Snow; SRM; Gamasiab.       
Zahra Arabi, Ayub Badragh Nejad,
Volume 8, Issue 4 (3-2022)

Drought is one of the environmental disasters that is very frequent in arid and semi-arid regions of the country. Rainfall defects have different effects on groundwater, soil moisture, and river flow. Meteorological drought indices are calculated directly from meteorological data such as rainfall and will not be useful in monitoring drought if the data are missing. Therefore remote sensing technique can be a useful tool in drought measurement. Drought is a recognized environmental disaster and has social, economic, and environmental impacts. Shortage of rainfall in a region for long periods of time is known as drought. Drought and rainfall are affecting water and agricultural resources in each region.
Materials & Methods
The present study is a descriptive-analytic one with emphasis on quantitative methods due to the nature of the problem and the subject under study. In this study, the Tera Sensor Modis satellite images from 2000 and 2017 were used to verify the existence of wet and drought phenomena. In the next step, by examining the rain gauge and synoptic data of the existing stations and using a standardized precipitation index model of three months (May, June and April), the sample was selected. Next, we compared the temperature status indices (TCIs) and vegetation health indices (VHIs) in these three months to determine the differences in these indices over the three months. Modi satellite Tera satellite was used to find out the vegetation status in the study area. Subsequently, using the condition set for the NDVI layer, the vegetation-free areas were separated from the vegetated areas. Experimental method was used to determine the threshold value of this index. For this purpose, different thresholds were tested, with the optimum value of 1 being positive. NDVI is less than 1 plant-free positive and more than vegetation-free. MODIS spectral sensing images for ground surface temperature variables, with a spatial resolution of 1 km, including bands 31 (bandwidth 1080/1180 central bandwidth / 11.017 spatial resolution 1000 m) and 32 bands- 770/11 Central Wavelength Band 032/12 Spatial Resolution Power (1000 m) Selected for months that are almost cloudless. All images have been downloaded from the SearchEarthData site and have been edited. The total rainfall of June, April, and May for the 20-year period was provided by the Meteorological Organization of Iran. ARC GIS software and geostatistical methods were used to process the Excel data. Also, to estimate the correlation between the data Pearson's correlation coefficient was used.
Results & Discussion
The standardized precipitation index is a powerful tool in analyzing rainfall data. The purpose of this study was to compare the relationship between remote sensing indices and meteorological drought indices and determine the efficiency of remote sensing indices in drought monitoring. Correlation between variables with SPI index was evaluated and calculated. The results of the indicators are different, so a criterion should be used to evaluate the performance of these indicators. SPI index on quarterly time scale (correlated with vegetation) as the preferred criterion Selected. According to the results of correlations, the TCI index with the SPI index had a strong correlation with other indices. In the short run, this index has the highest correlation with thermal indices at 1% level. The correlation between meteorological drought index and plant water content and thermal indices increases with increasing time interval. Positive correlation between vegetation indices and plant water content with meteorological drought indices indicates that trend of changes is in line. Therefore, the TCI index makes drought more accurate and is a better method for estimating drought.
The results showed that among the surveyed fishes, the highest drought trend was observed in the eastern part of these provinces and covered more than 50% of the area. The trend of changes in this slope was statistically significant. According to the results of correlations, the TCI index with the SPI index had a strong correlation with other indices. It can also be concluded that the Modis images and the processed indices along with the climate indices have the potential for drought monitoring. Using maps derived from drought indices can help improve drought management programs and play a significant role in mitigating drought effects.
Drought, remote sensing, correlation, climate index.

Mrs Zeinab Shogrkhodaei, Dr. Amanollah Fathnia, Mr Vahid Razavi Termeh,
Volume 9, Issue 1 (5-2022)

Study the Effects of Covid-19 on Air Pollutants by Using Sentinel-5 Satellite Images (Case Study: Metropolises of Tehran, Isfahan, and Mashhad)

Zeinab shogrkhodaei, PHD. Student of Climatology, Faculty of Literature and Humanities, Department of Geography, Razi University
Amanollah Fathnia*, Assistant Professor of Climatology, Faculty of Literature and Humanities, Department of Geography, Razi University
Vahid Razavi Termeh, PHD. Student of GIS, Faculty of Geodesy and Geomantic, K. N. Toosi University.

One of the challenges facing the international community right now is Covid-19. This pandemic has caused a comprehensive change in behavior contrary to the usual routine, which can lead to changes in people's lifestyles (Briz-Redón et al., 2021). The prevalence of this disease has not only affected the economy and health, but also the environment (Sohrabi et al., 2020). Among the effects of Covid-19 on the environment are the effects on beaches, noise, surface and groundwater, municipal solid waste, and air quality (Zambrano-Monserrate et al., 2020). The restrictions applied during the Covid-19 era were accompanied by a reduction in greenhouse gas emissions by transport and industry, which affected air quality (Rybarczyk and Zalakeviciute, 2020). Air is a vital element for the survival of all living things, but human activities have caused the release of many harmful pollutants into the atmosphere and endangered human health (Ghorani-Azam et al., 2016). Among the causes of death, air pollution is the fourth leading cause of death in the world after tobacco (WHO, 2020a). Sulfur dioxide, nitrogen oxide, carbon monoxide, and ozone are some of the pollutants that cause short-term or long-term exposure to heart and lung disease (Briz-Redón et al., 2021). Human activities are one of the main sources of air pollutants, so their concentration is expected to decrease during the Covid-19 period (Ghahremanloo et al., 2021).
Materials and methods
In this study, the required data were the average monthly pollutants of sulfur dioxide, nitrogen dioxide, carbon monoxide and ozone before (20 February 2019 to 20 February 2020) and after (20 February 2020 to 20 February 2021) the prevalence of Covid-19 virus. For this purpose, Sentinel-5P satellite images were used to prepare the required data set. The case study included three metropolises of Tehran, Mashhad, and Isfahan. Google Earth Engine was used to access Sentinel-5P satellite images. The final output of the images for each pollutant was interpolated for better display and exposure in GIS software using the kriging method. Then, a T-test was used to compare the differences between the concentrations of contaminants before and after the outbreak of the Covid-19 virus and to evaluate the mean correlation. Based on this test, values that were p-value <0.05 were considered significant. This was considered as a change in the concentration of the contaminant before and after the Covid-19 virus (decreasing or increasing). Those pollutants with a p-value <0.05 were considered unchanged.
Results and Discussion
Analysis of the T-test showed that for pollutants such as sulfur dioxide, nitrogen dioxide, and carbon monoxide in all three metropolises, there was no significant change in their concentration before and after the outbreak of the Covid-19 virus. However, significant changes were observed for ozone pollutants. Also, its concentration trend in all three metropolises has been a decreasing trend. The main sources of emissions of nitrogen dioxide, carbon monoxide, sulfur dioxide, and ozone are related to human activities, including transportation and industry (Ghahremanloo et al., 2021; Cárcel-Carras et al., 2021). Pollutants such as carbon monoxide, nitrogen dioxide and sulfur dioxide are the primary pollutants; It means that they are emitted directly from sources, while ozone is a secondary pollutant and depends on complex and nonlinear atmospheric chemistry (Bekbulat et al., 2021). Given that the concentration of ozone surface decreases significantly with increasing concentration of nitrogen dioxide. When nitric oxide (NO) emissions are high enough, the NO released into the atmosphere converts a large portion of ozone to nitrogen dioxide (Hashim et al., 2021). In addition, in all three cities, when the concentration of nitrogen dioxide increased, we saw a decrease in the amount of ozone concentration. In addition, during the Covid-19 era, many industries that produced primary pollutants, including carbon monoxide, nitrogen dioxide, and sulfur dioxide, were not on the closure list or were telecommuted. Despite the decline in the performance of some activities, important sectors such as manufacturing plants, industrial and mining centers, agriculture, and public transportation have continued to operate even during severe restrictions. The mean difference between the concentrations of nitrogen dioxide before and after the outbreak of Covid-19 was positive. However, this average difference is small. However, the concentration of nitrogen dioxide is slightly increased, especially in cold seasons; Therefore, it can be said that ozone concentration has decreased.

Keywords: Covid-19, Air Pollutants, Remote Sensing, Sentinel-5.

Dr. Homayoun Motiee, Mrs. Saba Ahrari,
Volume 9, Issue 2 (9-2022)

Glaciers are one of the most important water resources in the world, which are heavily affected by global warming and climate change. This paper investigates the effects of global warming on the changes in the snow cover level of the Takht Suleiman region located in Mazandaran province during the warm months of the year through the past three decades using remote sensing. For this purpose, the images from June to August of the Landsat-5 and 8 satellites in the period of 1990 to 2021, as well as the data of the air temperature product of the ERA5 sensor were processed on the Google Earth Engine. In this research, NDSI index (Normalized Snow Cover Surface Index) was used to detect snow covered surfaces and the Mann-Kendall test was used to evaluate the trend of the data. The results of the overall accuracy and Kappa coefficient in the Google Earth Engine system show an overall accuracy of 94% and a Kappa coefficient of 89% in 2021, which shows the high compatibility of this method with real data.
The results obtained during the investigated period show an increase of about 1.5 degrees in temperature during the last three decades at a significant level of 95%. The snow and ice cover of the Takht Suleiman region in June month decreased from 127 square kilometers( in 1990) with a decrease of 82% to 22 square kilometers( in 2021). The trend of changes in the level of snow cover in June was analyzed with the Mann-Kendall test, which shows a decreasing trend at a significance level between 80 and 90%. In general, these results indicate an increase in temperature and a decrease in the level of this glacier during the statistical period studied, and the continuation of the gradual depletion of the glaciers of this region in the future is a serious threat to the downstream water source and the surrounding environment.

Kaveh Mohammadpour, Ali Mohammad Khorshiddoust, Gona Ahmadi,
Volume 10, Issue 2 (9-2023)

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.
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.

Mrs Ziba Yousefi, Dr Hossein Jahantigh, Dr Farhad Zolfaghari,
Volume 10, Issue 4 (12-2023)

 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.

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