Spatial Analysis of Environmental Hazards

Spatial Analysis of Environmental Hazards

Identification of potential sources of dust in Lorestan province

Authors
hamed Haidari 1
Dariush Yarahmadi 2
Mostafa Karampour 3
1 Doctoral student of climatology, Lorestan University, Iran.
2 Associate Professor, Department of Climatology, Lorestan University, Iran.
3 Assistant Professor, Department of Climatology, Lorestan University, Iran.
10.61186/jsaeh.7.3.95
Abstract
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:


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.
Keywords
Dust
Potential
Remote Sensing
MODIS Sensor
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