Abstract
Algal blooms have become major public health and ecosystem vitality concerns globally. The prevalence of blooms has increased due to warming water and additional nutrient inputs into aquatic systems. In response, various remotely-sensed methods of detection, analysis, and forecasting have been developed. Satellite imaging has proven successful in the identification of various inland and coastal blooms at large spatial and temporal scales, and airborne platforms offer higher spatial and often spectral resolution at targeted temporal frequencies. Unmanned aerial vehicles (UAVs) have recently emerged as another tool for algal bloom detection, providing users with on-demand high spatial and temporal resolution at lower costs. However, due to the challenges of processing images of water, payload costs and limitations, and a lack of standardized methods, UAV-based algal bloom studies have not gained critical traction. This literature review explores the current state of this field, and highlights opportunities that could promote its growth. By understanding the technical parameters required to identify algal blooms with airborne platforms, and comparing these capabilities to current UAV technology, such knowledge will assist managers, researchers, and public health officials in utilizing UAVs to monitor and predict blooms at greater spatial and temporal precision, reducing exposure to potentially toxic events.
Highlights
Through a Google Scholar search using the search terms “unmanned aerial vehicles algal blooms”, “Unmanned aerial vehicles (UAVs) algal blooms”, “algal blooms drones”, “Harmful algal blooms (HABs) drones”, “HABs UAVs”, “unmanned aerial vehicles eutrophication”, “unmanned aerial vehicles red tide”, “cyanobacteria unmanned aerial vehicles”, and “phytoplankton unmanned aerial vehicles”, we found 193 relevant papers that focused on the remote sensing of algal blooms and the application of UAVs
Since 2012, there has been a rapid increase in use of UAVs for water resource management applications in freshwater and marine ecosystems [17], and this will continue to increase as UAV hardware, sensors, and processing software become cheaper
As hyperspectral and Light Detection and Ranging (LiDAR) sensors diminish in price, and algorithms specific to freshwater and marine environments are established, UAV-based algal bloom research will continue to flourish
Summary
Algal BloomsAlgal blooms are natural phenomena that occur in marine and freshwater ecosystems in response to environmental factors such as nutrient and light availability, water pH, wind intensity, and water temperatures [1]. Algae create the foundation for aquatic food structures and higher trophic cascades and are essential to aquatic ecosystems [2,3,4]. Proliferations of both toxic and non-toxic algal species can have deleterious effects on aquatic life by clogging fish gills, depleting the water’s oxygen levels, and killing fish and other organisms [5,6]. Harmful algal blooms (HABs) are primarily caused by dinoflagellates, diatoms, and cyanobacteria ( they are technically photosynthesizing prokaryotic bacteria, they are included as algal blooms in this study); each of these phytoplankton groups can produce toxins that are harmful to aquatic and terrestrial species [1,7,8].
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