علمی - پژوهشی
F Shafiei; A Darvishi Boloorani; S Pourmanafi; A Shahsavani
Volume 8, Issue 2 , November 2016, Pages 1-16
Abstract
Dust storms are atmospheric phenomena with negative environmental effects and especially for human health. Sampling and analysis of physical and chemical composition of recent dusts show that they are not merely composed of dust, gravel, sand and salt particles, rather they are of complex combination ...
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Dust storms are atmospheric phenomena with negative environmental effects and especially for human health. Sampling and analysis of physical and chemical composition of recent dusts show that they are not merely composed of dust, gravel, sand and salt particles, rather they are of complex combination of chemical elements. Metals such as soil alkaline metals, carbon, silica, aluminum, potassium, calcium and other organic components are observed that all these elements can have harmful effects on public health. In this study, Ahwaz where during last decades has seen several storms was studied. Using collected samples in the ground station and laboratory analyses dust contents were determined for seven dust events. For use of remote sensing technology using satellite images in order to identify the elements of dust, MODIS satellite images were used. Using MODIS images, the least squares method and cross-validation modeling, the relationship between MODIS bands and the results and measured chemical contents of dusts were created. Results show that silica, can be estimated from the ratio of 21 band to 26 with RMS 1.28. For aluminum, the ratio bands 25 to 26 with RMSE 2.08, for calcium the ratio of bands 24 to 25 with RMSE 2.3, for sodium of the ratio of bands 23 to 27 with RMSE 0.48 and finally for Magnesium the ratio of bands 15 to 24 with 0.78 RMSE are useful indexes to identify these elements using MODIS satellite images. According to the results MODIS images are useful for dust storms chemical elements estimation. Also using CALIPSO data, the rate of concentration and intensity of dust particles at the height of 6 km/asl are
علمی - پژوهشی
R Hosseini; A Alimohammadi; M.H Ghasemian
Volume 8, Issue 2 , November 2016, Pages 17-34
Abstract
Change detection methods are powerful tools to present the changes on the Earth’ surface. The multi-scale approaches which proceed the observations at coarser and finer scales, can be applied to maximize the accuracy of the change maps. The multi-scale approach, based on discrete wavelet, has been ...
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Change detection methods are powerful tools to present the changes on the Earth’ surface. The multi-scale approaches which proceed the observations at coarser and finer scales, can be applied to maximize the accuracy of the change maps. The multi-scale approach, based on discrete wavelet, has been applied in this research. In addition to the spectral information, the contextual or local information- available in the image are set in the processing. The wavelet technique is exploited in many processing fields of images. The ability of the wavelet technique has been applied for the change-detection, based on the satellite images in this study. The necessary parameters for the wavelet modification are the quantity decomposition levels and kind of mother wavelet. Thus The effect of the mother wavelet boir3/7 and db4 and the levels of decomposition s=1 to s=6 on the final change detection map have been assessed . All the results have been stated on the basis of the detection accuracy kappa coefficient and overall accuracy. The results reveal the influences of the mother wavelet and levels of decomposition on the final change detection map. The Change detection map, using t bior3/7mother wavelet, reveals higher overall accuracy and better kappa coefficient in proportion to bd4 mother wavelet. It is 0/7966 and 89/8013 for band 3 of Mother wavelet bior3/7 and 9/8013 & 0/7966 for mother wavelet db4. The next parameter being investigated here is related to the analysis surfaces influence on the precision of the change detection map. It increases to the level 3 of analysis and then decrease down. Eventually, most of the overall precision and kappa coefficient is related to the analysis level 3 of both mother wavelet. A comparison has been also conducted between the wavelet technique and the three methods image differencing , image ratio and supervised classification. The final review reveals the priority of the wavelet technique, as it presents better results.
علمی - پژوهشی
H Lashkari; A.A Matkan; H Asakereh; Y Khosravi
Volume 8, Issue 2 , November 2016, Pages 35-52
Abstract
Water vapor as one of the most important climate elements, plays an important role in decision-making, design and evaluation in hydrological models. Therefore, understanding the spatial changes of this important climate element have a significant effect on water management and planning. Accordingly, ...
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Water vapor as one of the most important climate elements, plays an important role in decision-making, design and evaluation in hydrological models. Therefore, understanding the spatial changes of this important climate element have a significant effect on water management and planning. Accordingly, this study is tried to studythe spatial structureand estimation of watervapor pressurein south and south west of Iran, using by geostatisticsmethodand variography analysis. In this regard, the water vapor pressure data of 78 synoptic stations on 18 August 2007 as one of the sweeping days by the water vapor pressure was analyzed. The first step for this purpose was calculation of the spatial variable of water vapor pressure that were analyzed by plotting the variogram. After fulfilling this requirement, geostatistical methods such as simple kriging, ordinary kriging, Co-kriging with auxiliary variables, and circular, spherical, exponential, Gaussian and quadratic rational models were used and their performance were evaluated. The results of cross validation showed that the best method that being able to justify the amount of water vapor pressure is Co-kriging method with altitude. According to the drawn map with the optimum method it was found that near the Persian Gulf and Oman Sea and the North and North West of study area are the highest and lowest amounts of water vapor pressure, respectively. It was determined that three reasons 1. Far and near to the main sources of humidity, 2. Zagros Mountains and 3. The establishment of strong pressure has an important role in water vapor pressure distribution.
علمی - پژوهشی
F Taghavi; A Ahmadi; Z Zargaran
Volume 8, Issue 2 , November 2016, Pages 53-72
Abstract
In this study, a combined model of modular networks and satellite image processing and optimization algorithms to forecast land surface temperature in an area including city of Tehran is presented. Calculating the LST has been done based on brightness temperature features in 31 and 32 MODIS channels. ...
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In this study, a combined model of modular networks and satellite image processing and optimization algorithms to forecast land surface temperature in an area including city of Tehran is presented. Calculating the LST has been done based on brightness temperature features in 31 and 32 MODIS channels. Thus, brightness temperature data related to these images is fed to neural network and values of land surface temperature are recovered as the output of the network. In this way,after obtaining the optimal structure obtained for networks they are trained and their weights are extracted. Then by applying a neural network with a modular structure and clustering algorithms, training will be also modular. Decomposition of the networks and after that combining the results to get the final forecast makes the performance of the modular network more effective. As a result , a new approach based on the combination of neural network or self-organizing map and particle swarm optimization algorithms is proposed. The results showed that using PSO algorithm causes appropriate distribution of cluster of SOM method and using satellite images improved performance of the proposed model. Finally, results are compared with training neural network models and non-modular structure. The results of this comparison show that model-training time in predicting the land surface temperature is decreased and the accuracy of model increased. The little difference between the predicted values and actual (real) values of temperature in the region shows that this model could predict the temperature accuraetly, so that, in this hybrid model Mean Square Errors (MSE) and Mean Absolute Percentage Error (MAPE) are 0.0081 and 10.59 respectively.
علمی - پژوهشی
A Daneshi; M Panahi
Volume 8, Issue 2 , November 2016, Pages 73-86
Abstract
Because the various algorithms have been developed for the land use classification by using remote sensing, the suitable algorithm selection plays an important role in achieving good results. For this purpose, by efficiency comparison of two algorithms classification i.e. support vector machines (SVM) ...
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Because the various algorithms have been developed for the land use classification by using remote sensing, the suitable algorithm selection plays an important role in achieving good results. For this purpose, by efficiency comparison of two algorithms classification i.e. support vector machines (SVM) and maximum likelihood (ML), the more precision method was determined and it was used for investigating land use changes trend. The present research was carried out using TM, ETM+ and OLI sensors images in Siminehroud watershed. The research results showed that SVM algorithm classified satellite images better than ML algorithm and radial basis function (RBF) kernel has the highest overall accuracy among the studied methods. Therefore, SVM algorithm with RBF kernel was used to derive land use maps and monitor land use changes in the studied periods. By analysis of land use changes trend using this kernel, it was found that during studied periods, irrigated farming from 30535ha to 67210ha, dry farming from 79909ha to 123387ha, residential from 474ha to 1934ha land uses have been increased but rangeland from 259811ha to 178397ha and water resources from 30535ha to 67210ha land uses are decreasing
علمی - پژوهشی
K Nosrati; S.H Pourali
Volume 8, Issue 2 , November 2016, Pages 88-101
Abstract
With regard to the hydrologic and agricultural issues, the capacity of water available to soil is considered to be an important variable and its estimation in catchment basin is deemed a principle. Due to the lack of consistency in taking the samples, unavailability of sufficient data for recognizing ...
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With regard to the hydrologic and agricultural issues, the capacity of water available to soil is considered to be an important variable and its estimation in catchment basin is deemed a principle. Due to the lack of consistency in taking the samples, unavailability of sufficient data for recognizing the characteristics of a region and also it is being time-consuming and costly to estimate the water available to soil and its space changes, the use of satellite images is more feasible and less costly. That being said, it is of the essence to develop simple method and models for estimating the capacity of water available to soil from distance. The theoretical background of this research is based on the relationship between vegetation and the temperature of the surface of the earth in estimating the capacity of water available to soil. In the study, in order to estimate the capacity of water available to soil in catchment basin in Hiv located at Hashtgerd, Landsat 7 satellite was used. For the earth control, 50 samples of soil were taken which were distributed in systematic ways. 80 percent of the taken samples were used for combined-model process of the earth surface, using a normalized index for vegetation. Also, 20 percent of the samples were used for the validation of the model. The validity, using multivariate regression with a coefficient determination of 0/85 was significant at 0/01 and the square mean error was 2/6.
علمی - پژوهشی
H Heydari; M.J Valadan Zouj; Y Maghsoudi; M.R Beheshtifar
Volume 8, Issue 2 , November 2016, Pages 101-112
Abstract
Iran as one of the countrieslocated in arid and semi-arid regions of the world, has been in drought danger. Shortage information about long-term weather conditions in many regions of the country, is one of the most important problems in drought monitoring. In this article, spectral vegetation indices ...
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Iran as one of the countrieslocated in arid and semi-arid regions of the world, has been in drought danger. Shortage information about long-term weather conditions in many regions of the country, is one of the most important problems in drought monitoring. In this article, spectral vegetation indices (SVIs) have been employed in order to drought modeling and its forecast. To this end, SPI drought indicator (standardized precipitation index) used to represent period of drought and its intensity. Some broad band spectral vegetation indices including Normalized Difference Vegetation Index (NDVI), Temperature Condition Index (TCI) and Vegetation Condition Index (VCI) were extracted by using NOAA-AVHRR satellite imagery. These indices entered to SVM classifier model to gain the SPI index as its result. After comparing the results, TCI was diagnosed as the best index to predict drought condition via 3 months SPI (trimester SPI).
