Authors: Hunter Synan*, University of North Carolina Wilmington
Topics: Water Resources and Hydrology
Keywords: harmful algal blooms
Session Type: Poster
Start / End Time: 9:55 AM / 11:35 AM
Room: Lincoln 2, Marriott, Exhibition Level
Presentation File: No File Uploaded
Harmful algal blooms (HABs) are aquatic phenomena defined by a rapid increase in phytoplankton biomass that create adverse water quality conditions harmful to surrounding biota. Exposure to HABs can cause health-related illnesses to domestic animals and humans, which can be fatal. Since 2015 the Chowan River in North Carolina has experienced numerous HABs each year, costing state officials millions of dollars to fund HAB monitoring programs. Current HAB monitoring methods incorporate spatial and spectral analyses of multispectral satellite images to measure the extent and activity of HABs. However, satellite imagery collection is temporally inconsistent, atmospheric conditions hinder image quality, and spatial resolutions are coarse, limiting their reliability for the near-real time image acquisition needed for optimal HAB monitoring. Drones are operationally versatile and more capable of collecting near-real time multispectral imagery than satellites. I propose a new approach for HAB monitoring efforts that incorporates on-demand drone imagery collected as HABs conditions develop. My first goal is to implement historic in-situ water quality data from reported Chowan River HABs and ground-reference high-resolution multi-spectral satellite images. My second goal is to statistically fuse concurrent satellite imagery and drone data of Chowan River HABs during summer 2019. I will compare the observed water quality data to the relative accuracy of satellite vs. drone-based classifications using HAB specific spectral algorithms. I hypothesize that drone collected imagery will produce more accurate spatial and spectral classifications of HABs compared to satellite imagery.