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Thesis - University Access Only
Master of Science (MS)
Electrical Engineering and Computer Science
Started in 2011, in the Image Processing Laboratory (IP Lab), a project is under way to perform atmospheric correction of space borne imaging sensors with no restrictions on the date, location, sensor or satellite used to create the image. In order to perform this correction, a wide range of meteorological data is needed to characterize the atmosphere. This meteorological data is obtained manually from multiple sources. Each of these sources comes in different data structures, with different compression/packing formats, with different spatial and temporal resolutions. Moreover, new data is periodically added to those sources.The absence of restrictions on the source of the images, which involves gathering large, complete and continuous data sets, has never been attempted before in this field. Thus, the project completed as described in this thesis has one main objective, which is to assess the feasibility of building a database that can support the multiple differences in the input data and that is fully automated, meaning newly available data should be automatically inserted in the database without any human intervention.To address the objective, a database and a script were created with the required exibility. To evaluate it, stored procedures were created to validate the correctness of the data by comparing their results to the data obtained from the multiple sources. The comparison revealed that the data was being processed and retrieved correctly.Using the methodology described in this thesis, the IP Lab was able to increase its efficiency and reliability, while at the same time providing a mechanism for easier linkage to the outside world.
Library of Congress Subject Headings
Imaging systems in meteorology
Includes bibliographical references (pages 72-80)
Number of Pages
South Dakota State University
In Copyright - Non-Commercial Use Permitted
Richard, Romain, "Design and Implementation of an Operational and Fully Automated Database Storing Geolocated Data" (2014). Electronic Theses and Dissertations. 2033.