Graduation Date
Spring 2021
Document Type
Thesis
Program
Master of Science degree with a major in Natural Resources: option Environmental Science and Management
Committee Chair Name
James Graham
Committee Chair Affiliation
HSU Faculty or Staff
Second Committee Member Name
David Gwenzi
Second Committee Member Affiliation
HSU Faculty or Staff
Third Committee Member Name
Buddhika Madurapperuma
Third Committee Member Affiliation
HSU Faculty or Staff
Keywords
UAV, Remote sensing, Riparian, NDVI, Mono Lake, Desert, GIS
Subject Categories
Natural Resources
Abstract
Mono Lake is a terminal lake in the Eastern Sierra Nevada Mountains. The streams that feed Mono Lake support a unique desert riparian ecosystem. Rush Creek was the stream of interest for this study. The objective of this research is to determine if remotely sensed imagery can be used to determine vegetation vigor and measure stream morphologic features in a desert riparian area. The goals were to evaluate different sources of remotely sensed imagery to make these determinations. The Normalized Difference Vegetation Index (NDVI) was used to monitor vegetation vigor along Rush Creek. Google Earth imagery and UAV derived imagery were used to measure various morphologic stream features such as channel width, floodplain width, location and width of meanders, and location and width of pools. Initially, seventeen years (1999 – 2016) of NASA Landsat derived NDVI values were analyzed. Next, NDVI from USDA National Agriculture Imagery Program (NAIP) imagery was analyzed. Finally, an Unmanned Aerial Vehicle (UAV) was flown over Rush Creek during the summer of 2017 and color and multispectral imagery was collected from which the NDVI index was calculated. The UAV derived imagery provided the most detail for vegetation vigor with 7-centimeter resolution. Google Earth Imagery and UAV derived color imagery were effective at measuring stream morphology. Overall, the UAV imagery outperformed the other sources of imagery for determining vegetation vigor and measuring morphologic features. Based on these results, UAV derived color and multispectral imagery should be included in the long-term vegetation monitoring at lower rush creek.
Citation Style
APA
Recommended Citation
Adair, Jordan Bradley, "Using UAV and traditional remote sensing data to detect vegetation vigor and monitor stream morphology in a desert riparian ecosystem" (2021). Cal Poly Humboldt theses and projects. 480.
https://digitalcommons.humboldt.edu/etd/480