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moderate-resolution-imaging-spectroradiometer
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The Implementation of an Operational MODIS Aerosol Retrieval Algorithm at High Spatial Resolution
, M.Sc. Thesis Sharif University of Technology ; Tajrishy, Masoud (Supervisor)
Abstract
Urmia Lake is one of the largest permanent hypersaline lakes in the world. Since Urmia Lake is faced with drying phenomena, the release of dust from its surface is expected. The most appropriate technique on dust storms is the remote sensing technique. One of the most popular parameter that provides the integrated information over a vertical column of unit cross section of this phenomenon is aerosol optical depth (AOD). Satellite remote sensing has been used to retrieve AOD over land and ocean at spatial resolutions of several to several tens of km. However, higher spatial resolution aerosol products for local scale areas have not been well-researched mainly due to the difficulty of...
Zoning of Dust Hotspots and Investigation of their Formation Factors
, M.Sc. Thesis Sharif University of Technology ; Tajrishy, Massoud (Supervisor)
Abstract
Identification of dust storm hotspots using high resolution 1 km MODIS Aerosol Optical Depth (AOD) data obtained by MAIAC algorithm for a region including Iran and its neighbors, is one of the objectives of the present study. By implementing three important statistics on AOD and averaging over the last decade time period (2009-2019), dust sources of Iran, Iraq, Syria, Saudi Arabia, Oman, Afghanistan, and Pakistan were specified. These statistics include frequency of occurrence AOD>0.3, mean and coefficient of variation of aerosol optical depth. The membership rank of source zones in the set of hotspot areas has been obtained by applying the fuzzy logic approach on the three mentioned layers....
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...
Estimating Particulate Matter (PM10) Concentration using Satellite data and Meteorological data from Synoptic Stations and WRF in Tehran
, M.Sc. Thesis Sharif University of Technology ; Arhami, Mohammad (Supervisor)
Abstract
Detetrmination of particulate matter (PM), as one of the most important pollutants in big cities, requires extensive system of monitoring stations. Remotely sensed atmospheric data due to their large spatial coverage and frequent observations are emerging as an important addition to conventional ground based atmospheric monitoring. In this regards this study presents an approach to analyze the relationship between PM10 (particles with aerodynamic diameter less than 10 μm) and the satellite product of aresol optical depth (AOD), which is the measurement of the extinction of light due to interferences with particulate matter. In the current study AOD is observed by Moderate Resolution Imaging...
Developing Models to Estimate Ground Level PM2.5 Concentrations Using Satellite Measurements
, Ph.D. Dissertation Sharif University of Technology ; Arhami, Mohammad (Supervisor)
Abstract
In this study different prediction models including linear mixed effect (LME), multi-variable linear regression (MLR), gaussian process model (GPM), artificial neural network (ANN) and support vector regression (SVR) were developed using satellite AOD product - with spatial resolution of 3 km – coupled with various auxiliary parameters to estimate ground-level PM2.5 over Tehran. The influence of site effect term on performance of LME models was evaluated using random intercept for monitoring sites. Results showed LME models without this term were able to explain variabilities of PM2.5 in ranges of 60 – 66% and 35 – 41% during model fitting and cross-validation (CV), respectively. By...
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....