REVIEW PAPER
Monitoring Cyanobacteria Blooms
in Freshwater Lakes using Remote
Sensing Methods
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1
Institute of Aviation,
Al. Krakowska 110/114, 02-256 Warsaw, Poland
2
Forest Research Institute, Sękocin Stary,
3 Braci Leśnej, 05-090 Raszyn, Poland
3
Warsaw University Observatory,
Al. Ujazdowskie 4, 00-478 Warszawa, Poland
Submission date: 2015-08-06
Final revision date: 2015-10-14
Acceptance date: 2015-10-14
Publication date: 2016-01-25
Corresponding author
Anna Maria Mazur
Institute of Aviation, al. Krakowska 110/114, 02-256 Warszawa, Poland
Pol. J. Environ. Stud. 2016;25(1):27-35
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ABSTRACT
Anthropogenic lake eutrophication can allow toxic cyanobacteria (blue-green algae) to grow uncontrollably,
resulting in harmful algal blooms with potentially serious economic and health-related impacts. Development
of monitoring methods for predicting bloom events is an important goal of monitoring programs
and is one of the fundamental interests to those examining the ecology of aquatic ecosystems. Implementation
of new monitoring methods complies with the provisions of national and community laws for the protection
and restoration of good chemical and ecological status of water reservoirs and dependent ecosystems,
and allows for the fulfilment of obligations of legislation policy of European Union (WFD 2000/60/EC)
and Polish Water Law Acts, and The Environmental Protection Law. Our paper investigates a comparison
between aerial remote sensing methods and currently used technology, and presents advantages of the proposed
monitoring as an accurate, flexible, cheap, and fast method of detecting and predicting eutrophication
and therefore cyanobacteria bloom in water reservoirs, taking into account the complexity and dynamics
of an ecosystem. The article also states that aerial remote sensing technology represents an innovative tool
strongly supporting traditional methods for continuous monitoring application and an early warning system
against algal bloom. Therefore, it is reasonable to continue remote sensing methods development in order to
precisely determine the cyanobacteria blooms in lakes. It is also necessary to improve satellite algorithms and
the use of both satellite images and those taken from unmanned aerial vehicles (UAVs) and manned planes.