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Scale dependencies in modeled fire behavior and effects in a southern U.S. grassland ecosystem.

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dc.contributor.advisor White, Joseph Daniel.
dc.contributor.author Yao, Jian, 1984-
dc.contributor.other Baylor University. Dept. of Biology. en
dc.date.copyright 2009-12
dc.identifier.uri http://hdl.handle.net/2104/5542
dc.description.abstract FARSITE models were originally developed for the western grass and forests ecosystems thus predictive accuracy as a function of the scale of input data in southern grasslands is relatively unknown. To test predictive accuracy of the model in southern U.S grasslands ecosystem, two prescribed burns were conducted on the grasslands at Camp Swift, near Bastrop, TX. The spatial scale of FARSITE predicted fire behaviors and effects were assessed based on comparison of field observations and FARSITE simulations utilizing three different spatial resolutions of fuel map data. The FARSITE simulations showed that, fine-scale fuel map derived simulation offered better area of burned prediction, better time of arrival simulation, and closer average temperature output. The time of arrival of fire simulation was less a scale dependence process than the temperature simulation. Prediction of fires in grasslands is limited by our detailed knowledge about mapping fine fuel loading, structure, contiguity, and interannual variability. en
dc.rights Baylor University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. Contact librarywebmaster@baylor.edu for inquiries about permission. en
dc.subject Scale effects. en
dc.subject FARSITE. en
dc.subject Grassland. en
dc.subject Fire modeling. en
dc.subject Remote sensing. en
dc.title Scale dependencies in modeled fire behavior and effects in a southern U.S. grassland ecosystem. en
dc.type Thesis en
dc.description.degree M.S. en
dc.rights.accessrights Worldwide access en
dc.rights.accessrights Access changed 12/13/11
dc.contributor.department Biology. en


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