The vast majority of theses in this collection are open access and freely available. There are a small number of theses that have access restricted to the WWU campus. For off-campus access to a thesis labeled "Campus Only Access," please log in here with your WWU universal ID, or talk to your librarian about requesting the restricted thesis through interlibrary loan.

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

DOI

https://doi.org/10.25710/bhtn-6388

Publisher

Western Washington University

OCLC Number

863701395

Subject – LCSH

Riparian areas--Washington (State)--Nooksack River Watershed--Evaluation; Coarse woody debris--Washington (State)--Nooksack River Watershed; Stream restoration--Washington (State)--Nooksack River Watershed; Remote sensing--Environmental aspects--Washington (State)--Nooksack River Watershed; Optical radar--Environmental aspects--Washington (State)--Nooksack River Watershed

Geographic Coverage

Nooksack River Watershed (Wash.)

Format

application/pdf

Genre/Form

masters theses

Language

English

Rights

Copying of this document 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.

Download

Share

COinS