Algal Coverage Detection and Classification Using Envi: Correlation with Dissolved Oxygen Levels in Elkhorn Slough, CA

Author

Jason Dawson, Nova Southeastern UniversityFollow

Defense Date

8-5-2020

Document Type

Capstone

Degree Type

Master of Science

Degree Name

Marine Science

First Advisor

Dr. Bernhard Riegl

Second Advisor

Dr. Mara Orescanin

Keywords

Estuaries, Water Quality, Environmental Monitoring, Spectral Analysis, Elkhorn Slough, algae monitoring, dissolved oxygen, hypoxia, eutrophication

Abstract

Estuaries are exposed to varying stressors, whether they be physical, chemical, or environmental. The most notable of stressors is eutrophication of coastal and inland ecosystems. This is a result of increased supply of nutrients fueling production within the system. One outcome of this increased nutrient load to the system is that of algal blooms. These blooms can impact the aesthetic appearance and degrade the quality of health of the system. Many of these coastal zones and waterways are critical habitats for many biological (some endangered) species and serve as recreational areas for human populations. Elkhorn Slough, California is one of these critical habits. Over its history, land use and environmental changes have degraded the quality of the ecosystem. Elkhorn Slough National Estuarine Research Reserve (ESNERR) has been tasked with oversight and monitoring responsibilities to maintain the system at a suitable level for the native species to thrive. This study, in conjunction with ESNERR support, will use aerial imagery of designated restoration areas to investigate the ability to use spectral analysis techniques to identify, classify, and calculate the percent coverage of algae masses. The aim is to use the inherent spectral analysis toolboxes in Harris Geospatial’s ENVI to ingest 3-band RGB imagery and differentiate and accurately classify algal coverage. The goal is to compare ENVI’s performance and accuracy, using ground-truthed base-image against traditional, time-intensive hand analytics. There is an extensive imagery library that has not be analyzed. This study will assess the potential ability to automate the process and increase classification capabilities.

NSUWorks Citation

Jason Dawson. 2020. Algal Coverage Detection and Classification Using Envi: Correlation with Dissolved Oxygen Levels in Elkhorn Slough, CA. Capstone. Nova Southeastern University. Retrieved from NSUWorks, . (2)
https://nsuworks.nova.edu/hcas_etd_all/2.