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

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