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Statistical correlation between economic activity and DMSP-OLS night light images in Florida

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Date Issued:
2011
Summary:
The Defense Meteorological Satellite Program (DMSP) Optical Line Scan (OLS) instruments collect data from an altitude of approximately 830km above the surface of the Earth. The night light data from these instruments has been shown to correlate by lit area with national level Gross Domestic Product (GDP) and to correlate with GDP at the State level by total radiance value. Very strong correlation is found between the night light data at a new, larger scale, the Metropolitan Statistical Area (MSA) within the state of Florida. Additional statistical analysis was performed to determine which industries within each MSA explain the greatest amount of variance in the night light data. Industrial variables exhibited strong multi-collinearity. It is therefore impossible to determine which industries explain the greatest variance in the night light image data.
Title: Statistical correlation between economic activity and DMSP-OLS night light images in Florida.
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Name(s): Forbes, Dolores J.
Charles E. Schmidt College of Science
Department of Geosciences
Type of Resource: text
Genre: Electronic Thesis Or Dissertation
Date Issued: 2011
Publisher: Florida Atlantic University
Physical Form: electronic
Extent: viii, 43 p. : ill. (some col.)
Language(s): English
Summary: The Defense Meteorological Satellite Program (DMSP) Optical Line Scan (OLS) instruments collect data from an altitude of approximately 830km above the surface of the Earth. The night light data from these instruments has been shown to correlate by lit area with national level Gross Domestic Product (GDP) and to correlate with GDP at the State level by total radiance value. Very strong correlation is found between the night light data at a new, larger scale, the Metropolitan Statistical Area (MSA) within the state of Florida. Additional statistical analysis was performed to determine which industries within each MSA explain the greatest amount of variance in the night light data. Industrial variables exhibited strong multi-collinearity. It is therefore impossible to determine which industries explain the greatest variance in the night light image data.
Identifier: 749963302 (oclc), 3175019 (digitool), FADT3175019 (IID), fau:3700 (fedora)
Note(s): by Dolores Jane Forbes.
Thesis (M.A.)--Florida Atlantic University, 2011.
Includes bibliography.
Electronic reproduction. Boca Raton, Fla., 2011. Mode of access: World Wide Web.
Subject(s): Earth -- Remote-sensing images
Rendering (Computer graphics)
Urban ecology (Sociology)
Sustainable development -- United States -- Florida
Persistent Link to This Record: http://purl.flvc.org/FAU/3175019
Use and Reproduction: http://rightsstatements.org/vocab/InC/1.0/
Host Institution: FAU