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N E W S
S T O R I E S
Data Sources
By using different sources of data and
combining those in a unique algorithm,
LG Sonic can forecast algal blooms 3
to 10 days in advance. This allows for
effective mitigation strategies through
the MPC-Buoy systems. The algorithm
can be fed by different data sources,
such as hydrological characteristics of
the water body and meteorological data
sources. The hydrological data consists
of streams of data generated by in-situ
water quality measurement and remote
sensing satellite imagery.
The use of remote sensing has an
unparalleled advantage when forecasting
algal blooms and specifically scum layers
because remote sensing is the only datasource
that provides a spatial overview of
water quality parameters over the entire
lake. For this forecast, mostly data from
Sentinel-2 and Landsat satellites are
used due to the resolution. Sentinel-2
and Landsat satellites can provide a
resolution between 10 and 30 meters and
provide images every 5-8 days. Other
satellites such as MODIS and Sentinel-3
show images on a more frequent basis,
but the resolution is generally lower, which
makes them unsuitable for smaller lakes
and reservoirs.
For the collection of in-situ water quality
data, near real-time sensors are used to
measure pH, Chlorophyll a, Phycocyanin,
Turbidity, Dissolved oxygen, Nitrogen,
and Phosphate. Nutrients, temperature,
and oxygen can be measured at different