## 1 Introduction  
Cyanobacteria, also known as blue-green algae, are aquatic bacteria infland and coastal communities around the world and are some of the oldest living organelles on the Earth. Cyanobacteria can be found in many different environments such as freshwater and marine ecosystems. A mature blue-green algae bloom often surfaces atop as a layer of scum which is an unpleasant sight with potentially serious economic and health-related impacts [1]. In recent years, blooms of cyanobacteria have been increasing in magnitude, frequency and in geographical spread, due to climate change and human activity [2]. Warmer temperatures indeed favor cyanobacteria that generally grow better at higher temperatures than do other phytoplankton species [3]. Moreover, the warmer is the water surface, the steepest is the vertical stratification of inland waters, with a consequent reduction of vertical mixing layer. Many cyanobacteria take advantage of these stratified conditions by forming intra-cellular gas vesicles, which make the cells buoyant and able to accumulate in dense surface blooms [4]. Furthermore, global warming has extended the optimal growth period since water column stratifies earlier in spring and destratifies later in autumn [5]. Therefore, on top of water temperature, factors like turbulence levels, nitrogen fixation, long day-light and the buoyant ability of cyanobacterial cells play their part in the occurrence of scums [6]. While further understanding of biological and physical growth dynamics of various algae species is still ongoing, water managers are interested in monitoring the state of lakes and lagoons to be able to raise a red flag in time. In-situ data is the most widely used data-set for monitoring inland water bodies such as lakes and canals. These data-sets provide highly accurate, precise and in depth information on the state of a location at a point in time but are limited to few local points and their maintenance often reduces the in-situ coverage of a water body. Satellite data have the advantage of taking frequent in time acquisitions and of providing a full spatial coverage at a coarse level, which allows trend detection in space and time. The Copernicus program, through Sentinel satellites constellations, ensures free, full and open access Earth Observation data availability for at least 20 years to come. Continuous, large scale studies of inland water ecosystems, biogeochemical processes and essential climate change variables can be performed for the very first time and with a spatial resolution suitable even for small lakes. These studies have the potential to tackle global scientific issues and to be a resource of information for management purposes [7]. Among the satellites of the Sentinels constellation, the recently launched Sentinel-1 (S1), Sentinel-2 (S2) and Sentinel-3 (S3) have the potential to provide information on bio-optical and physical properties of the waters. Optical remote sensing is a validated tool for sensing, monitoring and developing better understanding of the state phytoplankton blooms from inland for example, References [8; 9; 10], to oceanic waters for example, Reference [11], successful applications in different study areas such as the Baltic Sea for example, References [12; 13; 14; 15]. However, it is highly hindered by clouds. For regions with frequent cloud cover (such as the Baltic region) this means lack of data, which derails the purpose of sensing and makes difficult to spatially and temporally characterize any scum for a comprehensive ecological analysis. Moreover, cloudy conditions often favor the growth and aggregation of cyanobacteria on the surface since the consequent light reduction leads the algae to have excess buoyancy [16]. Therefore, the lack of data becomes even more serious with respect to the monitoring and management of aquatic environments and understanding of ecological phenomena in progress [17; 18].