Theses and Dissertations
Issuing Body
Mississippi State University
Advisor
Evans, David L.
Committee Member
Matney, Thomas G.
Committee Member
Schultz, Emily B.
Committee Member
Cao, Quang V.
Date of Degree
5-11-2013
Document Type
Graduate Thesis - Open Access
Major
Forestry
Degree Name
Doctor of Philosophy
College
College of Forest Resources
Department
Department of Forestry
Abstract
Ordinary and weighted least squares multiple linear regression techniques were used to derive 720 models predicting Katrina-induced storm damage in cubic foot volume (outside bark) and green weight tons (outside bark). The large number of models was dictated by the use of three damage classes, three product types, and four forest type model strata. These 36 models were then fit and reported across 10 variable sets and variable set combinations for volume and ton units. Along with large model counts, potential independent variables were created using power transforms and interactions. The basis of these variables was field measured plot data, satellite (Landsat TM and ETM+) imagery, and NOAA HWIND wind data variable types. As part of the modeling process, lone variable types as well as two-type and three-type combinations were examined. By deriving models with these varying inputs, model utility is flexible as all independent variable data are not needed in future applications. The large number of potential variables led to the use of forward, sequential, and exhaustive independent variable selection techniques. After variable selection, weighted least squares techniques were often employed using weights of one over the square root of the pre-storm volume or weight of interest. This was generally successful in improving residual variance homogeneity. Finished model fits, as represented by coefficient of determination (R2), surpassed 0.5 in numerous models with values over 0.6 noted in a few cases. Given these models, an analyst is provided with a toolset to aid in risk assessment and disaster recovery should Katrina-like weather events reoccur.
URI
https://hdl.handle.net/11668/16702
Recommended Citation
Collins, Curtis Andrew, "Modeling Hurricane Katrina's Merchantable Timber and Wood Damage in South Mississippi using Remotely Sensed and Field-measured Data" (2013). Theses and Dissertations. 3144.
https://scholarsjunction.msstate.edu/td/3144
Comments
regression||Landsat||remote sensing||forest damage||wind||hurricane