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Date Permissions Signed

11-14-2013

Date of Award

2013

Document Type

Masters Thesis

Degree Name

Master of Science (MS)

Department

Environmental Sciences

First Advisor

Wallin, David O.

Second Advisor

Helfield, James M.

Third Advisor

Bodensteiner, Leo R., 1957-

Abstract

Riparian areas are a complex component of stream ecosystems and provide critical habitat for Pacific salmon (Oncorhynchus spp.). Comprehensive techniques are needed for assessing riparian areas that can be used on small and large regional scales. I examined the application of airborne LiDAR and high resolution multi-spectral imagery from the World View-2 (WV-2) satellite to analyze riparian landcover and riparian forest structure in the Nooksack River Watershed. I employed an object-oriented approach to segment the imagery into meaningful objects consisting of groups of pixels. I examined the advantages of the four additional spectral bands from the 8-Band World View-2 Image compared to the traditional four spectral bands provided from conventional high resolution multi-spectral imagery. Using the Random Forest algorithm, I developed classification and regression models to predict the features of interest across the study area. The classification results from the 8-Band WV-2 image were improved over the traditional 4-Band WV-2 image that is comparable to other high resolution sensors such as IKONOS and Quickbird. Analyzing the combined LiDAR and 8-Band WV-2 spectral data improved the results for landcover classification but did not improve the results for riparian forest structural predictions. However, the results generated from the LiDAR only image was comparable to the 8-Band WV-2 spectral imagery at classifying forest classes and remarkably better at predicting forest structure data. The overall results indicate that classification of forested cover type and structural properties of riparian forest stands can be determined accurately for relatively large study areas with LiDAR-based approaches. From the final LiDAR image output, I applied the models to categorize the riparian forest based on forest class, size, and density to show one application of the results generated in this study. The categorized map provides a tool to prioritize restoration and preservation needs within the riparian forest landscape in the Nooksack River Basin study area.

Type

Text

Publisher

Western Washington University

OCLC Number

863701395

Digital Format

application/pdf

Geographic Coverage

Nooksack River Watershed (Wash.)

Genre/Form

Academic theses

Language

English

Rights

Copying of this thesis in whole or in part is allowable only for scholarly purposes. It is understood, however, that any copying or publication of this thesis for commercial purposes, or for financial gain, shall not be allowed without the author's written permission.

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