Thesis (M.U.D.)--University of Hong Kong, 2000. / Includes bibliographical references. Also available in print.

Theses (M.S.)--Marshall University, 2006. / Title from document title page. Includes abstract. Document formatted into pages: contains ix, 61 p. including illustrations and maps. Bibliography: p. 60-61

Thesis (Ph. D.)--Texas State University-San Marcos, 2006. / Vita. Appendices: leaves 101-106. Includes bibliographical references (leaves 107-112).

Thesis (M.S.) in Resource Economics and Policy--University of Maine, 2005. / Includes vita. Includes bibliographical references (leaves 97-102).

Thesis (Ph. D.)--Texas State University-San Marcos, 2006. / Vita. Appendices: leaves 101-106. Includes bibliographical references (leaves 107-112).

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<p> Understanding the causes of specific fire regimes is critical for determining the long term impacts of fire on vegetation cover. Numerous studies using 30 m Landsat data find a relationship between fire timing and vegetation type, but this relationship has not been observed at broader scales. In West Africa land-cover patterns are heterogeneous and patchy at the landscape scale and annual fires often burn mosaic patterns. It is well documented that where fires are known to be small and fragmented, the commonly used coarse-resolution MODIS data cannot give accurate estimates of burned area. Moreover, their inability to capture the spatial pattern of land-cover types burned presents a mixed pixel problem, because vegetation and agricultural fields vary on a scale less than 500 m². To overcome these issues, this study uses medium-resolution Landsat data to map land-cover. Landscape ecological indices are used to observe spatial patterns at 500 m scale.</p>

<p> FEMA&rsquo;s <i>Hazus Earthquake Model</i> (FEMA, 2018) is used frequently in the United States for scenario driven catastrophic planning, prioritizing mitigation funding, and disaster response situational awareness. The Hazus Earthquake Model requires a significant array of data for conducting earthquake loss estimations in terms of population demographics, building construction proxies, built environment estimates, critical facility locations, building infrastructure, and a variety of engineering and analysis parameters. A basic baseline of these required inputs is provided with Hazus for all 50 U.S. States, the District of Columbia, and the 5 U.S. territories. These default baseline datasets and engineering/analysis parameters however are somewhat rudimentary, and the incorporation of local data greatly increases results. Hazus enables the United States natural hazards risk assessment community to quantify risk using a robust suite of analysis options. By adapting the <i>Hazus Earthquake Model</i> for a country outside of the United States, risk management professionals across the globe can leverage the significant financial investment and over 20 years of software and scientific methodology investments undertaken by the U.S. government for their communities. While the methods and models are transferable internationally, the limited available data upon which the model is reliant minimizes its application outside of the U.S. Many global population exposure, building, and construction practice datasets do exist that could be leveraged to enable regional Hazus Earthquake modeling capability globally and a methodology for integrating these datasets into the software can facilitate technology transfer for supporting risk reduction. By conducting a quantitative comparison between modeled and actual losses from the 2015 Gorkha (Nepal) Mw 7.8 earthquake, this study aims to answer whether FEMA&rsquo;s U.S.-centric Hazus Earthquake Model can be adapted for Nepal to estimate building damages, injuries, and fatalities using global exposure datasets.</p><p>