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Document Type

Thesis - University Access Only

Award Date

2013

Degree Name

Master of Science (MS)

Department

Electrical Engineering and Computer Science

First Advisor

Larry leigh

Abstract

In satellite remote sensing, the view of the satellite passes through the layer of the atmosphere. The various components present in the atmosphere are vital in defining the characteristics of satellite imagery. The proper characterization of the atmospheric components like aerosols, ozone, water vapor, etc. are essential to uncover the information content of the satellite imagery in the most correct form. As one of the active components of the atmosphere, the characteristics of the aerosol particles should be properly studied as they can either absorb or scatter electromagnetic radiation that comes in contact with them. Aerosols include different particles and gases that are highly variable in shape, size and nature. Accordingly, different parameters like aerosol optical depth, aerosol index, angstrom exponent, etc., are used to represent the different aspects of their behavior. Several satellite missions have tried to characterize aerosol particles. However, these data records are not complete in space and time. The goal of this study was to create a global data set aerosol optical depth of 40 years that is continuous in both time and space at all locations around the Earth. The model simulation results showing the linear relationship between aerosol index and aerosol optical depth has been verified for TOMS aerosol index and MISR aerosol optical depth for various sites. In this study, the linear relation has been used to cross calibrate the aerosol index data at 380nm from TOMS on-board Nimbus 7 and Earth Probe to aerosol optical depth at 550nm. Data gaps exist in both the TOMS and MISR data. These data gaps were filled using appropriate interpolation algorithms. Synthetic gaps were created in the locations containing original data and filled using the interpolation algorithm. Uncertainty values were calculated as the difference between the original data and the interpolated data. The final uncertainty for a given location was the uncertainty due to cross calibration added to the uncertainty values for filling the gaps. The calibration results were within 24.2% of the MISR data and within 40% of the AERONET measurements. For the temporally interpolated data, the total uncertainty for the month long gap is less than 30%. For the temporal gaps that represent the small duration than a month, the total uncertainty is smaller. For the spatially interpolated AOT data, the uncertainty is less than 7.6% for a gap as big as 25o x 31.25o (latitude x longitude). In this case, the final uncertainty is still less than 25%. The spatially interpolated MISR AOT data has the uncertainty of less than 28.3% for the spatial gaps of size 50o x 62.5o (latitude x longitude). For the temporal gaps that are one week or less, the uncertainty has the maximum value of 24.9% while for the larger temporal gaps, the uncertainty can reach as high as 27.8%. For the case of aerosol loading at which atmospheric correction works are carried out, the process of calibration and interpolation created the difference of about 0.05 in the transmittance calculation.

Library of Congress Subject Headings

Atmospheric aerosols -- Remote sensing.
Aerosols -- Optical properties.
Landsat satellites -- Calibration.
Artificial satellites in remote sensing.

Description

Includes bibliographical references (pages 110-117).

Format

application/pdf

Number of Pages

134

Publisher

South Dakota State University

Rights

In Copyright - Educational Use Permitted
http://rightsstatements.org/vocab/InC-EDU/1.0/

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