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Date of Award
Spring 2023
Document Type
Masters Thesis
Department or Program Affiliation
Environmental Sciences
Degree Name
Master of Science (MS)
Department
Environmental Sciences
First Advisor
Wallin, David O.
Second Advisor
Yang, Sylvia
Third Advisor
Rybczyk, John M.
Abstract
There are two primary species of eelgrass at the Padilla Bay National Estuarine Research Reserve, Zostera marina, a native eelgrass, and Zostera japonica, a nonnative. Unoccupied Aerial Systems (UAS) have been frequently used for eelgrass monitoring and mapping, especially for large populations like those in Padilla Bay. UAS imagery have resolutions of 10 cm or better and are much more cost and time effective than aerial surveys via traditional aircraft that may provide similar image resolutions. In this project, multispectral UAS imagery was coupled with a centimeter level Digital Elevation Model (DEM), created from Real Time Kinematic GNSS measurements via regression kriging (vertical error of 4.3 cm), to predict Z. marina and Z. japonica cover from April-September 2022. Optimal UAS imagery was obtained when wind speeds were less than 5 m sec-1, sun angles were between 30-52°, tide stage was around -2.5ft, and there was less than 10% cloud cover. Multispectral imagery, using Random Forest (2,000 trees) classification were used to predict eelgrass cover. Then, multispectral imagery and elevation data, derived from the DEM, were combined to improve classification accuracy. The overall accuracy predicting Z. japonica dominant, mixed, and Z. marina dominant cover was 71.3% using multispectral imagery alone, while the accuracy raised to 89.6% when elevation data and multispectral imagery were combined. Although elevation alone was a strong predictor for eelgrass cover, multispectral imagery provided insight on seasonal changes among cover type. Z. japonica and Z. marina can be differentiated using the methods of this project, but uniformity in environmental conditions during image capture is crucial for comparative analysis.
Type
Text
Keywords
unoccupied aerial systems, eelgrass, Zostera marina, Zostera japonica
Publisher
Western Washington University
OCLC Number
1380360523
Subject – LCSH
Zostera marina--Washington (State)--Padilla Bay; Eelgrass--Washington (State)--Padilla Bay; Multispectral imaging--Washington (State)--Padilla Bay; Digital elevation models--Washington (State)--Padilla Bay; Aerial surveys in wildlife management--Washington (State)--Padilla Bay
Geographic Coverage
Padilla Bay (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 document for commercial purposes, or for financial gain, shall not be allowed without the author’s written permission.
Recommended Citation
Bergner, Jacqui, "Coupling Unoccupied Aerial System Surveys and Elevation Measurements to Predict Native and Nonnative Eelgrass Cover in Padilla Bay" (2023). WWU Graduate School Collection. 1175.
https://cedar.wwu.edu/wwuet/1175