سیما پورهاشمی

The phenomenon of dust is one of the most important environmental crises in arid and semi-arid regions of the world, which has harmful effects on human health and the environment. Dust or fine dust refers to very small and light particles of silt, clay or sand, which are moved and transported for a long distance in the earth's atmosphere as a result of wind erosion and desertification by the wind, and the horizontal visibility is between It is limited to 1 to 2 km or less. Due to being located in the dry and semi-arid belt of the world, Iran is exposed to numerous local and extra-regional dust systems. The dust storm in our country during the last few years has involved the provinces of the country as a serious crisis and has brought dangerous consequences for the residents of these areas in terms of environment, health and economy. Identifying the dust source area using remote sensing techniques is one of the most important methods in the world. The purpose of this research is to identify the centers of dust harvesting and its risk zoning using RF and MARS models. It is in Ilam province. 38 dust harvesting centers were identified in the study area. 70% of the identified foci were used for modeling and 30% for evaluation. Then 7 factors including soil, lithology, slope, vegetation cover index (NDVI), distance from the river, climatic units and land use were prepared as independent and effective variables on the center of dust collection. Then, using RF and MARS models, dust risk zoning maps were prepared.

The results of the identification of dust source area indicate that a total of 38 dust source area were identified in the entire region. The rule for detecting dust source in this research was based on the Gaussian plume diffusion model. In this way, when a dust emission cone is observed in a satellite image, the top of the cone represents the dust point. The results of the random forest model indicate that land use and soil science factors had the greatest role in the occurrence of dust. Using this model, the areas of sensitivity to dust extraction centers showed that about 18.1% of the studied area is in the category of very high sensitivity, and 63.2% of all dust source area are also in this range. Has taken. According to the results of MARS model, respectively, land use factors and climatic classes had the greatest effect on the creation of dust collection centers, and soil science had the least role. Examining the floor area of the dust sensitivity map using the MARS model showed that the area with high sensitivity has the lowest area (6.7) and the area of high, medium and low floors is 19, 42.8 and 31.5 respectively. It has been estimated. About 44.7% of collection centers are located in the area with very high sensitivity and there are 2.6% dust collection centers in the area with low sensitivity. The results of the random forest model showed that 16.6% of the area of Ilam province is in the area with low sensitivity, 42.3% in the area with medium sensitivity, 23% in the area with high sensitivity and 18.1% in the area with high sensitivity. It is located a lot. The results indicate that the highest concentration of dust collection (63.2%) is located in the area with high sensitivity. The results show that about 81.6% of the dust harvesting centers are located in the area with high and very high sensitivity. In both models, the highest percentage of dust collection centers is in the very high sensitivity class, which includes a small area of the region, especially in the MARS model.

The results of both models indicate that land use had the greatest impact on the creation of dust source area. Evaluation of the models using the ROC curve showed that in relation to the success rate, the RF and MARS models have accuracy of 0.91 and 0.86, respectively. Both models show a high correlation between sensitivity maps and distribution of dust centers. The results showed that the RF model has a higher accuracy in determining the areas sensitive to dust collection centers in the study area.

Physical development of cities seriously and geomorphological indicators of natural and associated complications . These natural phenomena are always changes over time, with the problems in their cities to expand . Thus , policies and functions should be applied to control the natural elements . The research methodology is based on a descriptive - analytical firm . The main tool in the GIS software Arc GIS is and the results show that the topographic maps , slope , elevation , soil , land use , distance to fault , groundwater and ... And then overlay maps in GIS, ranging from the preparation of stable and unstable land where physical development is done in terms of variables , or ventures such as floods , earthquakes, seismicity and ... They are then evaluated based on the optimization of Sabzevar in order to develop appropriate physical and environmental preservation have been porposed

Dust storms are natural hazards that effects on weather conditions, human health and ecosystem. Atmospheric processes are directly affected by the absorption and diffusion of radiation by dust, and dust in the cloud acts as a nucleus of congestion. The main dust regions in the world are arid topographies that have soil that is vulnerable to erosion and poor vegetation, easily eroded by wind. Due to its presence in the dry and semiarid belt of the world, Iran is exposed to multiple local and transboundary dust and dust systems. Iran and especially eastern Iran are exposed to severe environmental challenges such as storm dust. Land use change and soil erosion-sensitive soils are one of the most important factors affecting the creation of dust source areas.

The purpose of this study is to identify and determine the characteristics of dust source areas in eastern Iran. The study area is in the eastern part of Iran with an area of about 3711854.1704 km2. The altitude in the study area is 107 to 3527 meters above sea level. This area includes 7 provinces including North and South Khorasan, Khorasan Razavi, Semnan, Kerman, Yazd, Sistan and Baluchestan. In this research, MODIS data was used to identify the dust source area. To identify dust source area from MODIS satellite imagery for the period of 2004 to 2017 and using dust detection indicators including BTD3132, BTD2931, NDDI and D, were used. After determining the areas for dust source and preparing the distribution map of these points in the study area, the surface properties of dust source areas were investigated. In this study, landslide, geology, slope and normalized vegetation index (NDVI), which are effective in creating dust source area, were studied. Finally, to determine the characteristics of dust source areas, the mapping of the distribution map of dust source areas with land use maps, slope, NDVI and lithology in ArcGIS software environment was performed. After covering the layers, land use characteristics, slope, NDVI and lithology of dust source areas were extracted.

Using the four parameters and the method of false color combination and applying it to the MODIS image, the dust mass was detected on the images and then, by their visual interpretation, the starting point of the dust was determined. 147 dust points were identified in the study area. The results show that the highest dust points in land use, rangeland and agricultural land with 54, 45 and 18 points, which is about 36.73%, 30.61% and 24.24% The total points of the study area are located. The distribution results show the dust points on different slopes. As you can see, most of the dust points are two slopes of 0-2 and 2-5 with 104 and 27 points, with 90% of the source points in these two slopes. The results indicate that clay-loamy soils with the 61 point of dust, accounting for about 41.5% of the total points, have the highest point. This soil contains 38.084 percent of the total area of the region. The Vegetation Indicator Map (NDVI) in the region indicates that most of the area has no vegetation or vegetation, and only a very small part of the area (less than 1%) has a vegetation that indicates the land Far East of Iran. The results also indicate that all dust points are located on the 0 to -0.394673 class, and the rest of the classes have no point of view. The results showed that the highest and lowest dust points were in the geological units of chemical-sedimentary formations and intrusive rocks with a number of 43 and 0 source of dust.

The results show that most of the dust source areas in land use and rangeland uses 54 and 45 points, which is about 37% and 31% of the total source points of the study area. The results also showed that among different soils, the highest point of dust with clay-loamy soil texture with 61 points was observed (about 41.5% of total source points). Also, most dust source area are visible in areas with low slope and no vegetation cover. From the perspective of geology, the highest and lowest dust points in the region are located in the geological units of the sedimentary chemical formations and intrusive rocks of the player.

Dust storms are natural hazards that effect on weather conditions, human health and ecosystem. Atmospheric processes are directly affected by the absorption and diffusion of radiation by dust, and dust in the cloud acts as a nucleus of congestion. The main dust areas in the world are flat topographically dry areas with erosion-sensitive soil and poor vegetation that is easily eroded by wind. Atmospheric processes are directly affected by the absorption and scattering of radiation by dust, and the dust in the clouds acts as a condensation nucleus. Iran is exposed to numerous local and trans-regional dust systems due to being in the arid and semi-arid belt of the world. Recent observations indicate that this phenomenon is increasing in the country and region under study. Khorasan Razavi province has arid and semi-arid climates with numerous dust storms occurring annually. In some years, more than 50 dust events have been recorded in the province. The large amount of dust in this area indicates large harvesting areas across the province, indicating the importance of research in this area. The purpose of this study was to evaluate the factors affecting the occurrence of dust and to prepare its susceptibility map in Khorasan Razavi province using logistic regression and random forest regression models.

Khorasan Razavi Province with an area of 143864.118 square kilometers and with a population of 5.999529 is the fourth largest province in the country. The highest point of the province is in the highlands of Binalood, north of Neyshabur, at an altitude of 3211 meters above sea level, and the lowest point of the province is 300 meters above sea level, on the border of Iran and Turkmenistan. Dust indices include BTD2931, D, NDDI and BTD3132, which were calculated for all satellite images of these indices. Then there are four false color combination methods including 1- R: NDDI, G: B4, B: B3, 2- R: D, G: BTD2931, B: NDDI, 3- R: D, G: BTD3132, B: NDDI and 4- R: BTD2931, G: B4, B: B3, were used to determine the best method for identifying dust source. Initially, 65 dust sources were identified in the study area and for the period 2005-2016. Of the identified focal points, 70% (46 dust source) were used for modeling and 30% (19 dust source) were used for evaluation. Then, 7 factors including soil, lithology, slope, vegetation index (NDVI), distance from the river, geomorphic units and land use as an independent and effective variable on dust were prepared. Then using logistic regression and random forest regression models, the weight of each of the factors in R software was calculated, finally, the dust hazard sensitivity maps were prepared.

Four different false color combinations were used to detect dust areas in all images. Each of these methods revealed a dusty mass. The second method (R: D, G: BTD2931, B: NDDI) is the best method for detecting dust and determining dust collection zones. Finally, by employing these techniques and creating false color combinations and applying them to existing images and their visual interpretation, 65 dust collection points were identified throughout the area. Based on the results, slope had the greatest impact on creating dust source zones. Geomorphology, lithology, vegetation index, soil and land use are the next influential categories of dust source area. Negative coefficients indicate the inverse relationship of the dependent variable (dust source) with the independent variables; in fact, negative coefficients do not indicate a lack of correlation, but mean a weaker correlation than other factors. The distance factor from the river has the least impact on the formation of these dust source. The OOB results show a predicted error rate of about 35.16%. In other words, the accuracy of the model can be considered 64.84%. The results of logistic regression algorithm showed that 24.5% of Khorasan Razavi province was in low sensitivity area, 28.2% in medium sensitivity area, 29.4% in high sensitivity area and 17.9% in high sensitivity area. It is very sensitive. The results show that the highest dust source points (57.9%) are located in high sensitivity area. The results indicate that about 84.2% of the dust collection points are located in the area of high and high sensitivity. Surveying the area of dust susceptibility map using random forest algorithm showed that the area with the highest sensitivity had the lowest area (16.7) and the areas of high, medium and low were 23.5, 31 and 8.8, respectively. 28 estimated. About 63.2% of source are located in the area of high sensitivity and there is no source for the area of low sensitivity.

The results of both models show that slope and land use with the significant coefficients of 0.852 and 0.673 had the most effect on the creation of dust source area. The results also indicate that most dust removal sites (57.9%) are located in high sensitivity area. The results indicate that about 84.2% of the dust collection points are located in the area of high and high sensitivity. The evaluation of models using the ROC curve showed that in terms of success rate, logistic regression models and random forest had a precision of 781 and 907 respectively. Each of the two high correlation models between the sensitivity maps and the distribution of dust source areas can be observed. But in general, the random forest model has a higher accuracy than the other logistic regression models.

Due to the drought and land use changes in recent years, dust storm phenomenon in Iran has increased. The purpose of this research is to identify and prioritize dust source areas using bivariate models (probability model of event weight and frequency ratio model) in R software environment and determine the importance of each of the environmental factors affecting it in Khorasan Razavi province. To this porpuse, 65 dust extraction points were identified in the study area and a dust distribution map was prepared. Then maps of each of the factors influencing the occurrence of dust including soil maps, lithology, slope, vegetation index (NDVI), distance from the river, geomorphology and land use were prepared. Using the frequency and event weighting models, the weight of each effective factor and the relationship between each of the factors and the points of dust source were determined and, finally, priority maps of the dust source areas were prepared for the case study. Models were evaluated using the ROC curve. According to the results of both models, geomorphology units, land use and slope have the most effect on the occurrence of dust in the region, and both models have a frequency ratio and event weight with a sub-curve of 0.818 and 0.825, respectively. They accept.

In arid and semi-arid regions dust phenomenon occurs frequently. These phenomenon seriously affects the human health, soil erosion, desertification and transport. Drought is one of the natural phenomena that decrease precipitation, reduce vegetation and increase dust in case study. The purpose of this study was to examine the relationship between the number of dust events and climatic drought.

In this study, SPI index was used to estimate drought. Rainfall data for the years 1980-2010 and data of the dust for the years 2004-2010 were analyzed. The zoning dust and drought in the same period (2010-2004) was performed using the Kriging method in ArcGIS software.

The results of zoning the occurrence of dust and drought suggest that the greatest number of dust events (226 dust events) and severe drought happened in the province in 2008. Also, in 2005, the lowest number of dust events (85 dust events) and wet conditions prevailed in the province. Discussion and

The results indicate the direct relationship between dust event and drought, and dust event increased or decreased during the years that drought intensity increased or decreased.

Due to the drought and land use changes in recent years, the phenomenon of storm dust in Iran is increasing as a dangerous environment. Dust influences climate change and human health, causing serious damage. The subject of this research is to identify and prepare a map of sensitivity of dust source area for controlling and determining the role of each of the factors affecting its occurrence using the regression tree data mining model (BRT) in eastern Iran. For this purpose, at first 147 dust source area were identified in the region and divided into two groups for modeling and evaluation. According to the studies, eight effective factors including land use, geology, slope degree, elevation, normalized vegetation index (NDVI), distance from the river, wind speed and rainfall were identified and the layers of these factors were prepared in GIS environment. To evaluate the results, the ROC curve was used. The results showed that the BRT model with the area under the curve (79.6) had a good performance in producing a dust sensitivity map in the study area. Based on the results of the model, vegetation index, elevation and slope had the most impact on the occurrence of dust in the region.

Dust phenomenon is the One of the most important hazards in the dry and semi-arid region. The occurrence of this phenomenon is accompanied by many physical and financial losses. In this research, was studied the characteristic of land use and geomorphology dust source in Khorasan Razavi Province. At first, 65 soil dust sources were identified for the time period (2005-2016) by using the dust enhancement indices on the MODIS images. Then geomorphologic and land use maps were prepared and the dust source area were overlaid on these maps. The results indicate that in geomorphology map, 81 percent of the dust source area in the plain head unit occurred, accounting for about 71.5 percent of the all area. At other geomorphic surfaces, dust sources area are located in the Playa unit (10.7% in 17.5% of the area) and in the mountains (6.4% in 14% of the area). The results of land use survey showed that the highest number of dust source area occurred in poor rangelands (35.3%) and dryland lands (27.6%), which covers 35.3% of the total area. By calculating the dust rate at different levels, it was determined that in addition to the type of geomorphology and land use structure, there is a close correlation between the area and the number of dust source per unit with the emission rate of dust.

Abstract Physical development of cities seriously and geomorphological indicators of natural and associated complications . These natural phenomena are always changes over time, with the problems in their cities to expand . Thus , policies and functions should be applied to control the natural elements . The research methodology is based on a descriptive - analytical firm . The main tool in the GIS software Arc GIS is and the results show that the topographic maps , slope , elevation , soil , land use , distance to fault , groundwater and ... And then overlay maps in GIS, ranging from the preparation of stable and unstable land where physical development is done in terms of variables , or ventures such as floods , earthquakes, seismicity and ... They are then evaluated based on the optimization of Sabzevar in order to develop appropriate physical and environmental preservation have been proposed.

Introduction In Iran, landslides cause many problems every year, such as: destruction of roads, destruction of agricultural lands and pastures, residential areas, soil erosion and transition a great deal of deposits to the watersheds. It is important to be aware of number, area and volume of landslides in order to estimate sensitivity, determination of landslide danger and long-term evaluations to estimate bulk sensitivity. Area and number of landslides information is simply achieved through aerial photos, satellite images and field inspections. However, these methods are of no use for volume determination. It is a difficult task that needs surface and subsurface geometrical data from the rapture slope. Gathering this information which is performed as field operations is difficult and expensive and estimation of the volume of slope in steep hills is very challenging. Thus, estimation of landslide volume may be only carried out by taking experimental relations that connects the volume to geometrical raptures measurements especially the area.Since, deposit delivery in a basin exit is very important in watersheds management and most of deposits are caused by landslides on side-lines of rivers; the importance of estimation of landslides volumes has to be emphasised. Hence, the present study tried to find an experimental relation to estimate landslide volume in Neyshabour Baqi Basin (southern slopes of Binaloud) considering the significance of deposit volume caused by bulk erosion and also expensive and time-consuming field operations. It expands from 59” 38 ’58° to 13” 44’ 58° longitudes and from 09” 31’ 58° to 30” 38’ 36° latitudes; in southern slops of Binaloud Mountains. 3. Materials and methods In order to suggest an experimental relation to calculate the volume of recorded landslides, the only ones were chosen that had complete area and volume information. Thus, data of 44 observed landslides including longitude, latitude and area was given to SPSS Software to set a relationship between area (AL) and volume (VL). In order to model the experimental relation of AL and VL, considering existing statistical relations, general form of this equation was used: Finally, in order to estimate the volume of landslide by area information considering regression assumptions, a power regression model was obtained. In this relation, the observed volume is given by multiplication of slide area by observed depth obtained from remote calculations and GIS. Various experimental power relations which were used for landslide volume calculations, number of landslides and the associated area with calculated volume are given in table 1. Relations were applied for 44 observed landslides areas in the basin and results were compared with the observed values. At last, a statistical improved model for Baqi Basin was also compared with other relation. Comparison was made through R2 coefficient, percentiles statistics values, maximum, minimum and average and the root mean square errors (RMSE). 4. Results After collecting the data required from surveys, first their accuracy and quality were controlled and then their statistical properties were calculated and provided. According to the results of this table, landslides in the Baghi area are in a relatively wide range of area, size and depth, such that their area (AL) was in the range between. The observational volume or size of landslides (VL) was in the range between and their depth (DL) was in the range of. This wide range may increase the standard deviation (SD) followed by variation coefficient for each parameter. Because there are no observational data for depth, we decided to calculate the observational depth of landslides by remote sensing and GIS. In addition, to ensure the reliability of data, by selecting 8 sites for landslide out of 44 landslides occurred in the region and field studies, the accuracy of calculation depth were estimated indicates No. 44 of landslide with complete data of area (AL) and volume (VL), in a diagram with Log-Log coordinates. the frequency of slides is higher in the area range between 100000 m2 to 1000000 m2 and volumetric range between 500000 m2 to 5000000 m3.. Exponential regression fitness on the data of observational area and volume finally resulted in creation of equation (1). To evaluate the calculation values of size of landslide by related equation, these values were compared to volumetric estimations by other equations. After calculating the size of landslides in the Baghi area, the diagram for range of area determined were drawn by different equations. it can be said that equations like Imaizumi and Sidle (2007), Imaizumi (2008), Rice and Foggin (2008), Rice (1969) were relatively in good conformity to diagram of this study (equation 1); however, equations developed by Larsen and Sanchez (1998), Guthrie and Evans (2004), Marrtin et al (2002) have relatively lower estimation than developed equation. 5. Conclusion Results from this study indicated that the equation developed for Baghi area are in good conformity to some equations developed by others internationally. Because these equations presented in study areas with different local and physiographical conditions than Baghi are as well as for different ranges of areas, therefore, this conformity indicates that the relation between volume and area of landslide is basically geometrical and independent from local and physiographical conditions. In final conclusion, according to statistical accuracy of model provided and its conformity to some other equations as well as benefiting from results of this model from data obtained through whole area, this model can be considered as a desirable model for Baghi area and for calculating the size of landslides in the Eastern North of Iran.