علوم زیستی دریا
Saeid Farhadi; Hossein Mohammad Asgari; Ali Dadolahi Sohrab; Seyed Mohammad Jafar Nazemosadat; Sayyed Hossein Khazaei
Abstract
Dust prediction such as prediction of wind and rain needs to synoptic information to the earth's surface, upper layers of the atmosphere, the prediction maps of land surface and upper levels as well as using radar and satellites. The purpose of this study, use of remote sensing technology and MODIS images ...
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Dust prediction such as prediction of wind and rain needs to synoptic information to the earth's surface, upper layers of the atmosphere, the prediction maps of land surface and upper levels as well as using radar and satellites. The purpose of this study, use of remote sensing technology and MODIS images to estimate dust optical depth on the Persian Gulf surface and estimating the linear correlation relationship between the dust measurements in ground and atmospheric. The dust optical depth calculated using the code developed in MATLAB software. Evaluation of extracted data conducted using Pearson correlation coefficient, RMSE and RMSD index. In this study, optical depth obtained from image processing compared with the optical depths obtained from AERONET network. The evaluation results showed a high and significant correlation between the obtained optical depth and optical depths obtained from AERONET network (R2=0.99). The best and most suitable mode demonstrated for 1.243 and 1.643 bonds. At all stations, AOD value obtained from satellite image is bigger than AOD amount corresponding to the AERONET station and the algorithm used has overestimated. The cause of this more estimate can be use of limited particle's effective radius, because the scope of this effective radius is limited at the distribution of particle size in log-normal. Error resources at the retrieving particulate matter was defined such as sensor calibration error, pollution on the radiation angle, or poor predictor of water reflection.
علوم زیستی دریا
Nasrin Abdolkhanian; Heeva Elmizadeh; Ali Dadolahi Sohrab; Ahmad Savari; Mohammad FayazMohammadi
Abstract
Water resources under threat of pollution such as industrial waste, fertilizers, pesticides and urban sewage that negative effects on the environment and ecosystems. Arvand Rood is one of the most important navigable rivers in Iran, and it’s the most traffic place for floating which don’t ...
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Water resources under threat of pollution such as industrial waste, fertilizers, pesticides and urban sewage that negative effects on the environment and ecosystems. Arvand Rood is one of the most important navigable rivers in Iran, and it’s the most traffic place for floating which don’t have any system for delivery waste materials and discharging these waste materials in water making oil pollution. In this research, modeling pollution in the Arvand River using three-dimensional and hydrodynamic model to simulate how the pollution is studied, the Navier-Stokes equations in three dimensions and equations are solved transfer salinity and water temperature separation method. Boundary conditions applied, including changes in temperature, salinity and flow rate, temperature and salinity changes and apply for open border river and tidal components O1، S2، M2 and K1 open sea in the model used for the border. The results of modeling pollution in Arvand After running the model revealed that the pollution is pollution in the Arvand River according to location and time of release, In other words, in the Arvand River pollution from one point to another and from season to season is different, in fact, pollution is reciprocating mode. Diffusion of oil pollution in Arvand rood is depending to current. And in low tide because of same side of river current with low tide pollution reached to the Persion Gulf with high speed. The results shows, represent the effect of tie on diffusion pollution.
مهندسی دریا
khosro fazelpoor
Abstract
In order to provide SST images, the sensor MODIS installed on Aqua Satellite EOS-1 was used. Applying lighting assessment out of images from Modis 21-Level 1B Calibrated Radiances -1km in Persian Gulf and the Bushehr sea station (Bouyeh) from global algorithm specified for above sensor was used to estimate ...
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In order to provide SST images, the sensor MODIS installed on Aqua Satellite EOS-1 was used. Applying lighting assessment out of images from Modis 21-Level 1B Calibrated Radiances -1km in Persian Gulf and the Bushehr sea station (Bouyeh) from global algorithm specified for above sensor was used to estimate the sea surface temperature. With function of Matlab software to extract data of satellite images, and GIS software to convert the matris obtained, the maps of sea surface temperature were used. Forty eight images taken in 2008, 2009, 2012, and 2013 were selected. Their correlation coefficient eventually was 0.75, 0.86, and 0.75 respectively. Likewise the special coefficient obtained as 0.86, 0.90, 0.94 and 0.86 respectively. Finally, taking the 31 band temperature into consideration for the years 2008, 2009, 2012 and temperature differences of bands 31 and 32 and the sensor angle as independent factors were used at Bouyeh temperature as an affiliated factor calibrated by SPSS software for global algorithm of Persian Gulf. In order to check the correctness the algorithm suggested, the sea surface temperature was re-examined with satellite images of the year 2013; the correlation coefficient 0.96 and 0.94 were obtained. The searching has shown that the depth with current sea and latitude have effect on sea surface temperature, and temperature balance specially in north and central latitude have contrary relation with depth.