Next Article in Journal
Monitoring Human Visual Behavior during the Observation of Unmanned Aerial Vehicles (UAVs) Videos
Previous Article in Journal
Autonomous Landing of a UAV on a Moving Platform Using Model Predictive Control
Article Menu
Issue 4 (December) cover image

Export Article

Open AccessReview

UAVs in Support of Algal Bloom Research: A Review of Current Applications and Future Opportunities

1
Department of Environmental Sciences, Policy and Management, University of California, Berkeley, CA 94720, USA
2
Department of Landscape Architecture and Environmental Planning, University of California, Berkeley, CA 94720, USA
3
Division of Agriculture and Natural Resources, University of California, Berkeley, CA 94720, USA
*
Author to whom correspondence should be addressed.
Drones 2018, 2(4), 35; https://doi.org/10.3390/drones2040035
Received: 29 August 2018 / Revised: 11 October 2018 / Accepted: 12 October 2018 / Published: 17 October 2018
  |  
PDF [398 KB, uploaded 17 October 2018]
  |  

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. View Full-Text
Keywords: unmanned aerial vehicles (UAV); drones; algal blooms; remote sensing; phytoplankton unmanned aerial vehicles (UAV); drones; algal blooms; remote sensing; phytoplankton
Figures

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Kislik, C.; Dronova, I.; Kelly, M. UAVs in Support of Algal Bloom Research: A Review of Current Applications and Future Opportunities. Drones 2018, 2, 35.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Drones EISSN 2504-446X Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top