Theses and Dissertations

Issuing Body

Mississippi State University

Advisor

Cooke, William

Committee Member

Evans, David

Committee Member

Dyer, Jamie

Committee Member

Fan, Joseph

Date of Degree

1-1-2009

Document Type

Graduate Thesis - Open Access

Abstract

An estimated 39 million m3 of timber was damaged across the Southeast Forest District of Mississippi due to Hurricane Katrina. Aggregated forest plot-level biometrics was coupled with wind, topographical, and soil attributes using a GIS. Data mining through Regression Tree Analysis (RTA) was used to determine factors contributing to shear damage of pines and wind-throw damage of hardwoods. Results depict Lorey’s Mean Height (LMH) and Quadratic Mean Diameter (QMD) are important variables in determining the percentage of trees and basal area damaged for both forest classes with sustained wind speed important for wind-throw and peak wind gusts for shear. Logistic regression based on stand damage classification compared to RTA revealed LMH, stand height to diameter ratio, and sustained wind variable concurrence. Reclassification of MIFI plot damage calls based on percentage of trees damaged increased predictability of wind-throw and shear classification. This research can potentially aid emergency and forest managers for better mitigation and recovery decisions following a hurricane.

URI

https://hdl.handle.net/11668/15564

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