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Autonomous Attitude and Position Determination of Satellites Using Earth Imagery
, M.Sc. Thesis Sharif University of Technology ; Ghanbarpour Asl, Habib (Supervisor)
Abstract
An autonomous method for attitude and position determination of a satellite without using data from ground stations and also without the need for human interference is proposed using the image that the satellite has taken at each moment. The proposed method is based on recognition of stable features in the image and using them in order to match the satellite image with a source image from the Earth and the latitude and longitude of the features become known.SIFT and SURF algorithms have been examined. Using the perspective equation and camera coordinate system, a model has been developed that relates the coordinates of a point in the image with its equivalent coordinates in the real world....
Regional Dust Storm Trend and Dust Source Areas Contribution to PM10 Concentrations in Iran
, M.Sc. Thesis Sharif University of Technology ; Arhami, Mohammad (Supervisor) ; Tajrishy, Masoud (Supervisor)
Abstract
Several dust storms originated from western countries deserts of Iran hit different cities in Iran and substantially elevates PM10 levels. To the date, some studies on trend and origin of the dust storm have been carried out. However, not enough information is available on the contribution of different deserts around the country to the aerosol concentration in Iranian cities. In this study, the deserts of potential dust sources have been identified and their contributions to PM10 concentration in Tehran have been investigated. The PM10 data collected over a 5 year period from 2006 to 2010 at monitoring stations in Tehran were used. A statistical approach was implemented in order to determine...
Revisiting bathymetry dynamics in Lake Urmia using extensive field data and high-resolution satellite imagery
, Article Journal of Hydrology ; Volume 603 , 2021 ; 00221694 (ISSN) ; Bayati, M ; Tajrishy, M ; Chehrenegar, B ; Sharif University of Technology
Elsevier B.V
2021
Abstract
Bathymetric mapping for an accurate estimation of stored water volume in drying lakes is a key information for an effective monitoring of their recession or restoration status. Extraction of bathymetry in shallow saline lakes using remote sensing techniques has always been challenging due to the complex influences imposed by the physical properties of substrate and the spatial variability of salinity. In this study, we developed a machine learning-based model to quantify the implicit, non-linear relationship between water depth and surface reflectance by leveraging extensive in-situ data and high-resolution satellite imagery. We trained and tested the learning model in the hyper-saline Lake...
Design of Water Conveyance Systems Route Applying Satellite Images, Geographic Information System(GIS) & Genetic Algorithm
, M.Sc. Thesis Sharif University of Technology ; Shamsai, Abulfazl (Supervisor)
Abstract
To reduce construction costs selecting the optimal route for water conveyance line entails ample observation and considering all effective parameters. Some part of Aidoghmoush dam project of water conveyance line located in Azerbijan the east has been investigated in this research. First, by investigating, effective factors in determining the optimal route have been identified and then categorized into two groups of quantitative criteria(technical-economical) and qualitative criteria(environmental). Quantitative objectives include: slope, transportation system, infrastructures, fault and soil type. Qualitative objectives include: environmental considerations, land use and land cover. Because...
Studying and Modeling Climatic and Terrestrial Factors Effect the Occurrence of Dust Phenomena, and Determining the Origin of Dust Storms in IRAN
,
M.Sc. Thesis
Sharif University of Technology
;
Farhanieh, Bijan
(Supervisor)
Abstract
Particulate matter is an important source of air pollution. Particulate matters have an Undesirable effect on the environment, economic, and the health of Tehran Citizens. Annually, more than 8 thousands of tons of mineral dust from Internal and external resources deposit in Tehran city. In this project, the increase in the level of PM10 concentration during June, 12th to 14th, 2015 have been considered. The intrusion and dispersion of mineral dust during June, 11th to 15h, 2015 have been simulated with the HYSPLIT Model. Also, the Trajectory of particle end in Tehran during the mentioned days simulated and plotted with the HYSPLIT. The results show that more than 85% of PM10 reported by Air...
Investigation of Ardabil Plain Subsidence with Respect to Changes in Groundwater Level and Climate Fluctuations
, M.Sc. Thesis Sharif University of Technology ; Khosravi, Ali (Supervisor)
Abstract
The subsidence phenomenon in the past years has caused many problems and issues for the agricultural lands, roads, power transmission lines, energy etc., due to different reasons including over use of groundwater resources and changes in climate. This phenomenon has been observed in different plains of the country including the Khorasan, Kerman, Hamedan, Ghazvin and Isfahan plains and has caused many damages to infrastructure and agricultural products in the mentioned regions. In this research the main factors which have affected the subsidence phenomenon especially reduced ground water table and climate changes in Ardebil plain, are taken into account and some studies which comprise...
Nationwide prediction of drought conditions in Iran based on remote sensing data
, Article IEEE Transactions on Computers ; Vol. 63, issue. 1 , Jan , 2014 , p. 90-101 ; 0018-9340 ; Gharibshah, J ; Ghavami, S. M ; Beheshtifar, M ; Farshi, R ; Sharif University of Technology
Abstract
Iran is a country in a dry part of the world and extensively suffers from drought. Drought is a natural, temporary, and iterative phenomenon that is caused by shortage in rainfall, which affects people's health and well-being adversely as well as impacting the society's economy and politics with far-reaching consequences. Information on intensity, duration, and spatial coverage of drought can help decision makers to reduce the vulnerability of the drought-affected areas, and therefore, lessen the risks associated with drought episodes. One of the major challenges of modeling drought (and short-term forecasting) in Iran is unavailability of long-term meteorological data for many parts of the...
Optimization of echo state networks for drought prediction based on remote sensing data
, Article Proceedings of the 2013 IEEE 8th Conference on Industrial Electronics and Applications ; 2013 , Pages 126-130 ; 9781467363211 (ISBN) ; Jalili, M ; Sharif University of Technology
2013
Abstract
In this paper, we used echo state networks - a class of recurrent neural networks - for prediction of drought based on remote sensing data. To this end, the drought index was obtained for a number of stations in different clime zones of Iran. For each station, we also extracted the corresponding vegetation indices based on satellite imagery. Our model takes the satellite-based features as input and outputs the severity of drought. One of the major challenges of echo state networks is optimization of the reservoir parameters. Here we used a method based on Kronecker product in order to substantially reduce the parameter space to be optimized. We then used various optimization techniques...
The application of MODIS satellite remote sensing in estimation of particulate urban air pollution
, Article 100th Annual Conference and Exhibition of the Air and Waste Management Association 2007, ACE 2007, 26 June 2007 through 29 June 2007 ; Volume 2 , 2007 , Pages 736-742 ; 9781604238464 (ISBN) ; Amid, F ; Keshavarzi, H ; Sharif University of Technology
Air and Waste Management Association
2007
Abstract
Particulate matter (PM) pollution is a growing concern in urban areas in the developing countries because of its potential to aggravate cardiovascular and respiratory illnesses. Traditional approaches in monitoring urban pollutants have relied on ground-based networks even though they essentially provide point measurements and are inadequate for health alerts on large spatial and long temporal scales. Recent advances in satellite imagery has attracted managers to look into this new alternative as a predictive tool for improving air quality at urban and regional scales by providing necessary data in advance of the onset of actual severe conditions. Moderate Resolution Imaging...
Contribution of Iraqi and Syrian dust storms on particulate matter concentration during a dust storm episode in receptor cities: Case study of Tehran
, Article Atmospheric Environment ; Volume 222 , 2020 ; Arhami, M ; Sharif University of Technology
Elsevier Ltd
2020
Abstract
Frequent dust storms originated from Middle Eastern deserts impact major cities in Iran, including Tehran. Previous studies identified Iraqi and Syrian deserts as the main cross-border contributors to Tehran Particulate Matter (PM) levels. In this study, the contribution of Iraqi and Syrian dust storms to Tehran's PM10 and PM2.5 concentration were assessed during a dust storm episode. Initially, a dust storm event was identified through the statistical analysis of the recorded air pollution data at Tehran's monitoring stations and the visual inspection of the satellite images. A combination of CMAQ/WRF/SMOKE modeling systems was used to simulate PM concentrations from Tehran local sources...
Correlation between concentrations of chlorophyll-a and satellite derived climatic factors in the Persian Gulf
, Article Marine Pollution Bulletin ; Volume 161, Part A , December , 2020 ; Moradi, N ; Sharif University of Technology
Elsevier Ltd
2020
Abstract
Monthly mean satellite derived Chl-a, aerosols, wind, SST, PAR, and turbidity datasets were used to investigate the possible factors regulating phytoplankton variability in the Persian Gulf. The spatial correlation analysis revealed two distinct regions of SST and PAR, and a relatively uniform spatial correlation pattern of the other parameters. The cross correlation between aeolian dusts and Chl-a was significantly positive with 1–3 months offset. The pattern of spatial correlation between Chl-a and SST was positive in the shallow regions without time lag, and was negative with time offset of 3–5 months in deeper regions. The cross correlation between Chl-a and north-ward winds were...
Mapping the spatiotemporal variability of salinity in the hypersaline Lake Urmia using Sentinel-2 and Landsat-8 imagery
, Article Journal of Hydrology ; Volume 595 , 2021 ; 00221694 (ISSN) ; Danesh Yazdi, M ; Sharif University of Technology
Elsevier B.V
2021
Abstract
The spatiotemporal dynamic of salinity concentration (SC) in saline lakes is strongly dependent on the rate of water flow into the lake, water circulation, wind speed, evaporation rate, and the phenomenon of salt precipitation and dissolution. Although in-situ observations most reliably quantify water quality metrics, the spatiotemporal distribution of such data are typically limited and cannot be readily extrapolated for either long-term projections or extensive areas. Alternatively, remotely sensed imagery has facilitated less expensive and a stronger ability to estimate water quality over a wide range of spatiotemporal resolutions. This study introduces an adaptive learning model that...
Comparison and Evaluation of Flood Simulation Under Different Scenarios in Kashkan River and Missouri Basins Using Hec-Ras and Lisflood-Fp, and Development of a Method for Downscaling of Flood Discharge
,
M.Sc. Thesis
Sharif University of Technology
;
Moghim, Sanaz
(Supervisor)
Abstract
This study consists of two parts. In the first part, the performance of the LISFLOOD-FP model, which is raster-based, and the HEC-RAS model, are compared and evaluated. This work studied different scenarios under various digital models in two study areas, the Kashkan study basin with mountainous topography and the basin in Nebraska, which has a plain surface. The flood events are among the most severe floods in both study areas that occurred in March and April 2019. This study showed that in mountain topography, the performance of both models is good even with the 30 m high digital models. Although two models perform well, in the Nebraska basin, the performance of the two models in the...
The lake urmia environmental disaster in Iran: a look at aerosol pollution
, Article Science of the Total Environment ; Volume 633 , 2018 , Pages 42-49 ; 00489697 (ISSN) ; Khaghani, A ; MacDonald, A. B ; Nguyen, P ; Karimi, N ; Heidary, P ; Karimi, N ; Saemian, P ; Sehatkashani, S ; Tajrishy, M ; Sorooshian, A ; Sharif University of Technology
Abstract
Lake Urmia (LU) once was the second largest hypersaline lake in the world, covering up to 6000 km2, but has undergone catastrophic desiccation in recent years resulting in loss of 90% of its area and extensive coverage by playas and marshlands that represent a source of salt and dust. This study examines daily Aerosol Optical Depth (AOD) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) between 2001 and 2015 over northwestern Iran, which encompasses LU. Intriguingly, salt emissions from the LU surface associated with ongoing desiccation do not drive the study region's AOD profile, whereas pollution transported from other regions and emissions around LU are more important....