Marziyeh Deiravi pour; Hossein mohammadasgari; saeid Farhadi; Iman Najafi
Abstract
Extended Abstract Introduction One of the important features of desert areas (arid and semi-arid) is dust phenomena that occurs in most days of the year. Dust phenomena occur especially in tropical areas. In some parts of the world, including Africa, Australia and the Middle East, the annual sediment ...
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Extended Abstract Introduction One of the important features of desert areas (arid and semi-arid) is dust phenomena that occurs in most days of the year. Dust phenomena occur especially in tropical areas. In some parts of the world, including Africa, Australia and the Middle East, the annual sediment volume carried by the flow of the wind is greater than the sediment volume carried by the rivers. Today, the dust phenomena are among the most important environmental hazards which have put human and environmental health at serious risk. Based on the country’s comprehensive water plan, the size of the real deserts of Iran has increased to 4.7 million hectares or 35.5 percent of the country’s land area. Materials & Methods The study area was the southwest of Iran including Khuzestan and the Persian Gulf regions. In recent years, these regions have strongly been affected by the dust with internal source and especially with external sources such as dust sources in Iraq, Syria, and Saudi Arabia. In this research, we employed the library method and also determined the days of the dust storm using the weather data of the province. We used satellite data, MODIS sensor data and several algorithms based on the image processing to detect dust. In order to evaluate the different methods of dust detection, it is necessary to compare the results of the algorithms with another independent source. This source can be a natural color images, aerosol sensor products, MODIS dust indicators or other sensors products. In this research, we first introduced the HDF file of MOD021k MODIS images into the ENVI5.2 software to visualize the dust. After preprocessing the satellite images, we employed different methods such as creating False Color images, BTD and NDDI algorithms, and the neural network method to detect dust on satellite imagery. In this regard, we stored the required bands for the NDDI and BTD algorithms as a single band in the ENVI software, and entered it into MATLAB software to apply the detection algorithms. Due to the importance of remote sensing and satellite images and also the efficiency of the artificial neural networks method we decided to classify the images of the MODIS sensor by using the methods of the Artificial Neural Network and dust detection indexes. In general, the bands 20, 23, 31 and 32 of MODIS sensor and the infrared thermal bands were used more to detect dust storms. The Brightness Temperature Difference between these bands can detect dust storms from other phenomena. In this study, a Feed Forward Neural Network (FFNN) was used to detect dust storm in Khuzestan and the north of the Persian Gulf, using 20 data sets for the day and 11 data sets for the night. To categorize different pixels in the neural network based on BTD values, BTD of the bands 20-31, BTD of the bands 23-31, BTD of the bands 31-32 and bands 1, 3 and 4 were used. MODIS bands 1, 3 and 4 were used to create realistic color images to for the better detection of the Earth’s surface phenomena. These three bands were used only for MODIS’s daily images. Discussion The results show that the emissivity of sand in band 31 (0.96) is slightly lower than the band 32 (0.98), while the soil emissivity for these two bands was (0.97) and water emissivity (0.99). Also, the emissivity value of band 31 for the cloud was (0.98) and for band 32 was (0.95). There was a difference between the emissivity value of bands 23 and 31 for soil, sand, and water, which can be used to distinguish dust from other surfaces. The brightness temperature of dust storm (K298/4) and cloud (K276) in the band 23 (4.6 µm) was higher than the brightness temperature of dust storm (K287) and cloud (K271) in the band 31 (11.02 micrometers), while the brightness temperature of water (K285), ground (K310) and vegetation (K295) in the band 23 was lower than that in band 31 for the same items (Water (286K), ground (310K) and vegetation (296K). For these reasons, the difference in brightness temperature between bands 23 and 31 is useful for detecting dust from the ground, vegetation, cloud and water. In the artificial neural network, the correlation coefficient of the training, evaluation, test and total data was equal to R = 0.996, R = 0.99505, R = 0.99559 and R = 0.9958, respectively. These results show the good capability of the neural network in detecting dust. The data was divided into two classes of dust (0.9) and no dust (0.1). In fact, various inputs entered the network and were divided into two classes of dust and no dust. The results showed that the error started from a large amount and gradually decreased. Epoch is referred to as every step of the data correction. In other words, when an input passes through the network and generates an overall error, the weight factors are corrected with the help of that error, a process which is called the number of repetitions or the Epoch. Thus, as itis shown in the figure, the training ends after 151 repetitions. Given the results of the neural network output images, it is observed that dust is well distinguished in both the aquatic and terrestrial ecosystems and a better differentiation will be done with higher dust concentration. The ACC parameter indicates that the neural network method has had a good accuracy and performance. Results show that neural network is a more appropriate method than the BTD index in dust detection, and the neural network does not need to determine the threshold for examining each image. Conclusions The results of the NDDI index show that this parameter alone, is not able to distinguish dust pixels existing in the atmosphere from the pixels of sand and other than dust, and has poor accuracy in images with cloud or water. It seems that this low efficiency is related to the features of the earth’s surface such as land use, land cover, topographical differences, as well as chemical properties of dust minerals in the region. According to the results of this study, the results of applying the BTD index have suitable performance for the detection of dust. In the present research, the artificial neural network shows a fairly good accuracy and performance for the daytime images with an accuracy of 60%.
Reza Borna
Abstract
Extended Abstract
Introduction
Dust is one of the atmospheric and climatic disasters whose occurrence causes environmental damages, respiratory and heart diseases, land and air traffic, tourist and agricultural problems, etc. Considering the great damages of this phenomenon and the possibility ...
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Extended Abstract
Introduction
Dust is one of the atmospheric and climatic disasters whose occurrence causes environmental damages, respiratory and heart diseases, land and air traffic, tourist and agricultural problems, etc. Considering the great damages of this phenomenon and the possibility of an increase in its occurrence in the coming years, the attention of the government and the implementation of appropriate solutions are essential in this regard. It is obvious that, before implementing the operational plans, the appropriate ways of dealing with this phenomenon can be found by having sufficient information and knowledge about it and the way and causes of its occurrence. To this end, it is essential to use the experiences and findings of other countries in this field in order to take a substantial step in this way by applying the right and principled methods. Some of the most important objectives of this research are to identify the factors affecting the dust phenomenon in Khuzestan province, to identify the methods of preventing the effects of dust in Khuzestan province, to use the AHP model for ranking the methods of preventing the effects of dust using the Analytic Hierarchy Process (AHP) in the study area.
Materials & Methods
The methodology of this research is analytical-descriptive, and the research is of applied type. In this research, the meteorological statistics of 12 meteorological synoptic stations of Khuzestan province were used during the period 0f 2001-2014 and, the map of the dispersion of dust storms in Khuzestan province was prepared. Considering the experts’ opinions, the major criteria which include the criteria of individual factors, extraterritorial factors and State factors were determined and then, the sub-criteria were determined for each criterion. After determining the criteria, the hierarchical graph of the criteria was created. Then, the criteria were compared with each other in the pairwise comparison matrices and the weight of each criterion relative to another one was assigned to that criterion in terms of the priority value. After the completion of the paired comparison matrices, the tree of criteria was created in EC2000 software, then, the applied scores were entered into the EC2000 software and the relative weight of each criterion resulted from the sum of the product of the significance of criteria and sub-criteria was obtained. The analysis of the inconsistency rate value is performed by EC2000 software during the pairwise comparison for each set.
Discussion & Results
Based on the yearly frequency of the occurrence of days with dust phenomenon during the 13 year statistical period (2001-2014), a total of 592.7 dusty days has been reported for the province of Khuzestan at the meteorological stations under study. The study of the data of all stations indicated that the highest frequency of dusty days was related to the Omidieh station with 125 days, then Dezful with 84.8 days and the lowest frequency was related to the Behbahan station with 22 days. The criteria studied in the dust phenomenon and the ranking of the methods for preventing its effects in Khuzestan, are diverse and complicated. Effective criteria in the ranking of the methods for preventing the effects of dust phenomenon are individual factors, extraterritorial factors and State factors that, each one of the main criteria has sub-criteria. In order to rank the methods of preventing the effects of dust phenomenon in Khuzestan province, observing the hygiene of houses and residential areas, keeping to personal hygiene (using masks and washing the mouth and nose), forming joint regional working groups (countries affected by dust), utilizing international facilities, adhering to regional and international commitments, Soil conservation programs, conservation and revival of wetlands and water resources, mulching, constructing windbreaks, sprinkling pebble, growing vegetation, providing medical equipment and informing people about the dangers of dust were selected, and using the Analytical Hierarchy Process ( AHP) model and Expert Choice software were evaluated.
Conclusions
The results of the calculations obtained from the application of Expert Choice software show that among the criteria studied, the State factors are the most influential index in ranking the methods of preventing the effects of dust phenomenon in Khuzestan, among other criteria. Considering the analysis of the sensitivity based on efficiency, the State factors criterion is more important than other criteria. In the analysis of sensitivity, individual factors, extraterritorial factors and State factors account for 29.7%, 16.3% and 54% of the total weight, respectively. Among the sub-criteria of individual factors, personal hygiene (using masks and washing the mouth and nose) with a weight of 0.750, accounts for the highest weight in ranking the methods of preventing the effects of dust phenomenon. Observing hygiene in houses and residential areas is at the next priority with a weight of 0.250. Among the sub-criteria of the extraterritorial factors, the formation of regional joint working groups of regional (countries affected by dust) with a weight of 0.540, adherence to the regional obligations has the highest role in the ranking of the methods of preventing the effects of dust phenomenon. The international sub-criterion with a weight of 0.297 and utilizing international facilities within the weight range of 0.163, have the subsequent priorities in the ranking of the methods of preventing the effects of dust phenomenon. Among the sub-criteria of the State factors, informing people about the dangers of dust with the weight of 0.263, soil conservation programs within the weight range of 0.155, providing medical equipment with the weight of 0.147, Conservation and revival of wetlands and water resources with the weight of 0.127 and creation of vegetation with the weight of 0.124 have the highest role in the methods of preventing the effects of dust phenomenon, respectively.
Maryam Arjmand; Alireza Rashki; Hossein Sargazi
Abstract
Extended Abstract Introduction Dust cycles are an integral part of the Earth system, which emits about 2000 tons of dust every year (Shao et al., 2011) and plays an important role in the global climate changes (Park & Jong, 2008). The frequency of dust events in the arid and semi-arid regions is ...
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Extended Abstract Introduction Dust cycles are an integral part of the Earth system, which emits about 2000 tons of dust every year (Shao et al., 2011) and plays an important role in the global climate changes (Park & Jong, 2008). The frequency of dust events in the arid and semi-arid regions is much higher, meanwhile, dried lakes have the largest ration in dust emission (Goudie and Middleton, 2006). Hamoun e Jazmurian is a dried lake located in an homonymous topographic-low basin in southeast Iran and a main source for high dust emissions under favorable weather conditions, but so far limited studies have been carried out in this area, especially on dust. Remote sensing provides useful information about spatiotemporal variability of dust storms over the arid environment of the world. So the present study examines the spatiotemporal variability of dust activity over the region by identifying the dust events from the satellite data. Materials & Methods In this work, spatial and temporal variability of dust aerosol were analyzed over the arid environment of Jazmurian region and surroundings located on southeast of Iran by means of monthly mean data, including Absorption Aerosol Index (AAI), values products of TOMS-Nimbus7 (N7) (1979-1984), TOMS-Earth Probe (EP)(1990-2005) and OMI (2005-2014) as well as Deep Blue AOD of MODIS-Terra (2000-2007) and MODIS-Aqua(2002-2014) and Aerosol Optical Depth (AOD555nm) of MISR (2000-2013). Results & Discussion The results indicated that several hot points of dust including Sistan/Hamoun, Rootak, a region in Pakistan near the border with Iran, Makran coast, Gwadar Bay ion the southeast corner of Iran and the Jazmurian region. Overall, the annual trend of both AAI and AOD values obtained from all sensors, are increasing during the periods expect MODIS retrievals which has negative partial amounts, the time periods of 2002-2004, 2008-2009 and 2011-2012 are the peak of dust storms over the Jazmurian region because of human activities and severe droughts. Seasonal variations of AAI and AOD values showed the major dust activities occur during spring and summer and it is minimum in autumn over Jazmurian region. high activity of dust storms are in four months of May, June, July and August and low in the four months of November, December, January and February Conclusion Hamoun e Jazmourian is one of the active dust emission regions in south east of Iran. The amount of dust and affected areas have increased in recent years. Severe droughts in recent years and numerous dam construction are one of the main factors of dust emission increase in this region.
Madjid Montazeri; Leyla Dadkhah
Volume 22, SEPEHR , July 2013, , Pages 89-91
Abstract
Dust has always been one of the most important environmental hazards and it leaves adverse environmental consequences. The present article seeks to identify and analyze dusty days’ trend in Bushehr station during the last 55 years.
In this regard, monthly and annual statistical data of dusty days ...
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Dust has always been one of the most important environmental hazards and it leaves adverse environmental consequences. The present article seeks to identify and analyze dusty days’ trend in Bushehr station during the last 55 years.
In this regard, monthly and annual statistical data of dusty days in Bushehr station between 1951 and 2005 was applied. First, normality test was performed using Ncss and homogeneity test was performed using Runs Test. After proving data abnormality, nonparametric test of Mann-Kendall was chosen.
Findings indicate that except for June, other months show an increasing trend of dusty days even in annual scale. Noteworthy, the increasing trend in cold months is more obvious than warm months of the year so that March and November with respectively 3.71 and 4.4 show an increasing trend in 99.9 percent significant level.
Mohammad Reza Servati; Mohammad Reza Yusefi Roshan
Volume 21, Issue 83 , November 2012, , Pages 16-35
Abstract
Movements of sand and small particles (dust) because of wind occur in many different environments, but the phenomenon is much more powerful in arid areas and cover larger areas. The phenomenon is one of the most important issues arid areas face. In order to preserve buildings, agricultural lands, pipe ...
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Movements of sand and small particles (dust) because of wind occur in many different environments, but the phenomenon is much more powerful in arid areas and cover larger areas. The phenomenon is one of the most important issues arid areas face. In order to preserve buildings, agricultural lands, pipe lines and transport networks from sandstorms and from being buried in dust and sand, it seems necessary to create and develop monitoring tools and confront this natural phenomenon. Urban areas in arid lands can block movements of sand and dust suspended in wind. In arid lands and deserts population is centralized around ground water resources. Cultivated lands are limited which results in more pressure on the earth due to centralization and population being attracted to settlements. Thus, desert ecosystem near urban areas faces more damages, plant life faces destruction and soil structure will be damaged. Movements of sand and small soil particles increase and wind-related problems and issues display in a larger scale. In this regard, factors creating problem of sand and small soil particles depend on desertification factors which have gained attentions in recent years (A. J. Pilor and Honey, 1976; United Nation, 1977).
To decrease disagreeable results of sand and small soil particles movements, we need to gain enough information regarding the natural characteristics of such movements and identify factors accelerating this process, while trying to decrease the quality and quantity of these natural events. Therefore, the present article aims to identify natural characteristics, intensity, dispersion and movement of sand and small soil particles in arid areas and problems caused by wind processes. Then, the study seeks to create a new model to identify and observe sand and small soil particles movements. Furthermore, it tries to find a way to evaluate sand and small soil particles movements and dangers cause by wind erosion, and also a way to measure these movements precisely and bring them under control.
