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Utilization of Sentinel satellite series for monitoring the water quality of the Baltic Sea and Finnish lakes

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Basic project information

Sentinel2-kuva länsirannikolta 27.08.2016
Sentinel 2 satellite image from 27.8.2016 the west coast of Finland. ESA Sentinel program, prosessed by SYKE.


VESISEN-project aims at developing methods for utilizing EU/ESA Copernicus-program Sentinel-satellite series observations for determining water quality on Finnish lakes and on the coastal waters of Finland. VESISEN concentrates on determining chlorophyll a, turbidity, aCDOM and Secchi disk depth with accuracy estimate. The abovementioned parameters have been judged as the first step to utilize the new generation EO instruments for efficient monitoring of relevant water quality parameters for EU directive reporting, such as the Water Framework Directive.

To assess reliably and comprehensively eutrophication status of marine and lake waters compel to develop and implement joint use of data from several monitoring methods. The largest benefit for monitoring water quality using EO instruments is the spatial and temporal representativeness of the observations, which guarantees that monitoring is sufficient especially on areas and periods out of reach for traditional station monitoring.

During 2017, demonstration products of the water quality parameters will be made available for the users at SYKE and in ELY centers. By the end of VESISEN project (31.3.2018) the project has determined the accuracy for determining chl-a, turbidity, aCDOM and Secchi Disk depth using the new sensors onboard Sentinel-2 and Sentinel-3 satellite series. The project will utilize the first models/methods to start monitoring these parameters, but it is foreseen that along with the longer time series and method development, the accuracy of the models will improve further.

The project utilizes Sentinel-2 MSI-instrument for determining turbidity, aCDOM and Secchi disk depth especially on the coastal waters and on lakes. With the good spatial resolution (10-20m) of S2/MSI- instrument also small-structured and fragmented estuaries and small lakes can be covered. Sentinel-3 OLCI instrument will be utilized on the coastal and open Baltic Sea and on the largest Finnish lakes. The spectral configuration of OLCI is optimal for determining chl-a concentrations.

During the project, SYKE will also start using SLSTR onboard S3 satellite for determining sea surface temperatures (SST) on the Baltic Sea and on largest Finnish lakes. This will replace the earlier service using NOAA/AVHRR instrument.

The back-up instrument in this project is Landsat 8 -satellite (LC8) OLI -instrument. OLI observations can be used to determine mainly turbidity and Secchi disk depth.

Sub-tasks of the project

The project consists of EO algorithm development, validation and utilization of various types of field observations. The project utilizes especially flow-through measurements systems both on coastal vessels and autonomous Alg@line observations onboard ships-of opportunity. Furthermore, the routine monitoring station observation dates are optimized according to S2A overpasses to obtain match-ups. The project determines especially the EO algorithm functionality at high concentrations and on optically extreme conditions, such as on lakes with high CDOM absorption. The maintenance of automated station at lake Pyhäjärvi in Säkylä is part of the project.


  • S3 OLCI (Ocean and Land Color Instrument)
  • S2 MSI (MultiSpectral Instrument)
  • LC8 OLI (Operational Land Imager)
  • SLSTR (Sea and Land Surface Temperature Radiometer)

The project concentrates on determining the accuracy of various bio-optical models, but also the accuracy of most suitable band ratio algorithms will be evaluated especially on eutrophic lakes. The project also focuses on automated elimination of errors in the end-products, such as accurate detection of cloudy areas, areas covered by cloud shadows and shallow areas with influence from the seabed. Whitecaps and ships are identified and eliminated from the water quality estimates of S2/MSI.

The optical properties of Finnish lakes and estuaries along the coast are unique. Therefore, several field campaigns utilize e.g. the flow-through measurement system by Luode Consult Oy and optical instruments (ASD and BB3).

Connections to other projects

VESISEN is part of the chain of projects concentrating on Earth Observations of water quality. VESISEN utilizes and experiments ENVIBASE National Satellite Data Centre (NSDC) by the Finnish Meteorological Institute at Sodankylä receiving station. During ENVIBASE project, Calvalus parallel processing system by Brockmann Consult has been set up in Sodankylä. VESISEN utilizes the technical capabilities of CalFin and determines the water quality processing chains to be used after the end of the project. An EU project EOMORES will concentrate on utilization of EO in directive reporting.

More information

Senior Researcher Jenni Attila, SYKE, first name.last

Scientific publications

  • Simis SGH, Ylöstalo P, Kallio KY, Spilling K11, Kutser T (2017). Contrasting seasonality in optical-biogeochemical properties of the Baltic Sea. PLoS ONE 12(4): e0173357.
  • Ligi, M., Kutser, T., Kallio, K., Attila, J., Koponen, S., Paavel, B., Soomets, T., Reinart, A., (2017). Testing the performance of empirical remote sensing algorithms in the Baltic Sea waters with modelled and in situ reflectance data. Oceanologia, Oceanologia 59: 57—68.
  • Kallio, K., Koponen, S., Ylöstalo, P., Kervinen, M., Pyhälahti, T., Attila, J.,(2015). Validation of MERIS spectral inversion processors using reflectance, IOP and water quality measurements in boreal lakes. Remote Sensing of Environment 157: 147–157.
  • Ylöstalo, P., Kallio, K. & Seppälä, J. (2014). Absorption properties of in-water constituents and their variation among various lake types in the boreal region. Remote Sensing of Environment 148: 190–205.
  • Attila, J., Koponen S., Kallio, K., Lindfors, A., Kaitala, S., Ylöstalo, P. (2013). MERIS Case II water processor comparison on coastal sites of the northern Baltic Sea. Remote Sensing of Environment 128: 138–149.
  • Kallio, K. 2012. Water quality estimation by optical remote sensing in boreal lakes. Monographs of the Boreal Environment Research no. 39: 1-54.
  • Lepistö, A., Huttula, T., Koponen, S., Kallio, K., Lindfors, A., Tarvainen, M. & Sarvala, J. (2010). Monitoring of spatial water quality in lakes by remote sensing and transect measurements. Aquatic Ecosystem Health & Management 13(2): 176-184.
  • Kallio, K., Attila, J., Härmä, P., Koponen, S., Pulliainen, J., Hyytiäinen, U.-M. & Pyhälahti, T. (2008). Landsat ETM+ Images in the Estimation of Seasonal Lake Water Quality in Boreal River Basins. Environmental Management 42: 511-522.
  • Koponen, S., Attila, J., Pulliainen, J., Kallio, K., Pyhälahti, T., Lindfors, A., Rasmus, K., Hallikainen, M., (2007). A case study of airborne and satellite remote sensing of a spring bloom event in the Gulf of Finland. Continental Shelf Research 27 (2): 228-244.
  • Attila, J., Pyhälahti, T., Hannonen, T., Kallio, K., Pulliainen, J., Koponen, S., Härmä, P., & Eloheimo, K. (2008). Analysis of turbid water quality using airborne spectrometer data with a numerical weather prediction model-aided atmospheric correction. Photogrammetric Engineering and Remote Sensing 74 (3): 363–374.
  • Kallio, K., (2006). Optical properties of Finnish lakes estimated with simple bio-optical models and water quality monitoring data. Nordic Hydrology, 37 (2), 183–204.
  • Kallio, K., Pulliainen, J., & Ylöstalo, P. (2005). MERIS, MODIS and ETM channel configurations in the estimation of lake water quality from subsurface reflectance with semi-analytical and empirical algorithms. Geophysica 41: 31-55. (pdf, 530 kB)
  • Kutser, T., Pierson, D. C., Kallio, K. Y., Reinart, A. & Sobek, S. (2005). Mapping lake CDOM by satellite remote sensing. Remote sensing of Environment 94: 535-540.
  • Kutser, T., Pierson, D., Tranvik, L., Reinart, A., Sobek, S. & Kallio, K. (2005). Estimating the colored dissolved organic matter absorption coefficient in lakes using satellite remote sensing. Ecosystems 8: 709-720.
  • Vepsäläinen, J., Pyhälahti, T., Rantajärvi, E., Kallio, K., Pertola, S., Stipa, T., Kiirikki, M., Pulliainen, J. & Seppälä, J. (2005). The combined use of optical remote sensing data and unattended flow-through fluorometer measurements in the Baltic Sea. International Journal of Remote Sensing 26 (2): 261-282.
  • Pulliainen, J., Vepsäläinen, J., Kaitala, S., Hallikainen, M., Kallio, K., Fleming, V., Maunula, P. (2004). Regional Water Quality Mapping through the Assimilation of Space-Borne Remote Sensing Data to Ship-Based Transect Observations. Journal of Geophysical Research, Vol. 109, No. C12, C12009.
  • Koponen, S., Kallio, K., Pulliainen, J., Vepsäläinen, J., Pyhälahti, T., Hallikainen, M. (2004). Water Quality Classification of Lakes Using 250-m MODIS Data. IEEE Geoscience and remote sensing letters 1(4): 287-291.
  • Kallio, K., Koponen, S., Pulliainen, J., (2003). Feasibility of airborne imaging spectrometry for lake monitoring—a case study of spatial chlorophyll a distribution in two meso-eutrophic lakes. International Journal of Remote Sensing 24 (19): 3771–3790.
  • Härmä, P., Vepsäläinen, J., Hannonen, T., Pyhälahti, T., Kämäri, J., Kallio, K., Eloheimo, K., Koponen, S. (2001). Detection of water quality using simulated satellite data and semi empirical algorithms in Finland. The Science of Total Environment 268 (1-3): 107-121.
  • Kallio, K., Kutser, T., Hannonen, T., Koponen, S., Pulliainen, J., Vepsäläinen, J., Pyhälahti, T. (2001). Retrieval of water quality from airborne imaging spectrometry of various lake types in different seasons. The Science of Total Environment 268 (1-3): 59-77.
  • Koponen, S., Pulliainen, J., Servomaa, H., Zhang, Y., Hallikainen, M., Kallio, K., Vepsäläinen, J., Pyhälahti, T., Hannonen, T. (2001). Analysis on the feasibility of multi source remote sensing observations for chl a monitoring in Finnish lakes. The Science of the Total Environment 263(1-3): 95-106.
  • Kutser, T., Herlevi, A., Kallio, K. & Arst, H., (2001). A hyperspectral model for interpretation of passive optical remote sensing data from turbid lakes. The Science of the Total Environment 268: 47-58.
  • Pulliainen, J., Kallio K., Eloheimo, K., Koponen, S., Servomaa, H., Hannonen, T., Tauriainen, S., Hallikainen, M. (2001). A semi-operative approach to water quality retrieval from remote sensing data. The Science of The Total Environment 268: 79-93.

Other publications

Published 2017-10-13 at 9:07, updated 2017-10-20 at 10:04