Monitoring Cyanobacteria Blooms in Freshwater Lakes using Remote Sensing Methods
Katarzyna Anna Kubiak 1, 2  
,   Jan Kotlarz 1, 3  
,   Paweł Czapski 1,   Anna Maria Mazur 1  
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Institute of Aviation, Al. Krakowska 110/114, 02-256 Warsaw, Poland
Forest Research Institute, Sękocin Stary, 3 Braci Leśnej, 05-090 Raszyn, Poland
Warsaw University Observatory, Al. Ujazdowskie 4, 00-478 Warszawa, Poland
Anna Maria Mazur   

Institute of Aviation, al. Krakowska 110/114, 02-256 Warszawa, Poland
Submission date: 2015-08-06
Final revision date: 2015-10-14
Acceptance date: 2015-10-14
Publication date: 2016-01-25
Pol. J. Environ. Stud. 2016;25(1):27–35
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.