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Applications of Urban Modeling Using Vegetation-Impervious Surface-Soil and Linear Spectral Mixture analysis in Non-Western Counties

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dc.contributor.advisor Stefanidis, Anthony
dc.contributor.author Gaw, Caleb Emir
dc.creator Gaw, Caleb Emir
dc.date 2013-05-02
dc.date.accessioned 2013-08-16T20:35:20Z
dc.date.available NO_RESTRICTION en_US
dc.date.available 2013-08-16T20:35:20Z
dc.date.issued 2013-08-16
dc.identifier.uri https://hdl.handle.net/1920/8310
dc.description.abstract Developing accurate methodologies and models for using remotely sensed data is important in examining and understanding urban areas. Just as sensor types have evolved over time, the techniques and methods for modeling urban areas have been in constant development. In particular, there has been much development over the last 20 years increasing the efficiency and accuracy of the Vegetation – Impervious Surface – Soil (V-I-S) Urban model purposed by Ridd in 1995, through spectral mixture analysis. While many works have shown how to reduce errors within these processes and increase the accuracy of their results over their respective study areas, a fundamental question remains: are these models and techniques applicable to other urban areas outside of their study area? This work will address the logical development of the V-I-S urban model through spectral mixture analysis with the application to urban areas outside of western developed countries. The results will indicate that advances in spectral mixture analysis do increase the accuracy of depicting Vegetation, Impervious Surfaces and Soil, but that the V-I-S model does not accuracy accurately and consistently depict urban areas across the globe.
dc.language.iso en_US en_US
dc.subject V-I-S Urban Modeling en_US
dc.subject spectural mixture analysis en_US
dc.subject vegetation, impervious surface and soil modeling en_US
dc.title Applications of Urban Modeling Using Vegetation-Impervious Surface-Soil and Linear Spectral Mixture analysis in Non-Western Counties en_US
dc.type Thesis en
thesis.degree.name Master of Science in Geoinformatics and Geospatial Intelligence en_US
thesis.degree.level Master's en
thesis.degree.discipline Geoinformatics and Geospatial Intelligence en
thesis.degree.grantor George Mason University en


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