UAVs vs Satellites: Comparison of tools for water quality monitoring

Enzo Pacilio, Alejo Silvarrey, Alvaro Pardo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Cyanobacterial Harmful Algal Blooms (CyanoHABs) thrive in calm, shadow and warm On-Farm Reservoirs (OFRs) where the water is rich in nitrogen, phosphates, carbonates and organic matter. In addition, water toxicity can vary from hour-to-hour and day-to-day and it can remain toxic even after a bloom has disappeared. Thus, OFRs should be monitored frequently for outbreaks and establish assessment programs. Satellite-based remote sensing is a broadly used method for water quality assessment and CyanoHABs monitoring because of its specialized sensors and availability of historical data of the water body. However, the spatial and time resolution may not be enough in case of outbreaks in OFRs. On the other hand, Unmanned Aerial Vehicles (UAV) emerge as a cost-effective alternative with high spatial and temporal resolution. In this paper, a comparison between satellite and UAV remote sensing approaches for monitoring CyanoHABs in a small and shallow water reservoir is conducted. UAVs rise as a reliable complement to satellites thanks to their superior temporal and spatial resolution.

Original languageEnglish
Title of host publication2022 IEEE 13th Latin American Symposium on Circuits and Systems, LASCAS 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665420082
DOIs
StatePublished - 2022
Event13th IEEE Latin American Symposium on Circuits and Systems, LASCAS 2022 - Santiago, Chile
Duration: 1 Mar 20224 Mar 2022

Publication series

Name2022 IEEE 13th Latin American Symposium on Circuits and Systems, LASCAS 2022

Conference

Conference13th IEEE Latin American Symposium on Circuits and Systems, LASCAS 2022
Country/TerritoryChile
CitySantiago
Period1/03/224/03/22

Keywords

  • CyanoHABs
  • On-Farm Reservoirs
  • UAV
  • climate change
  • remote sensing
  • satellite

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