The science behind the EyeOnWater APP

The science in citizen science

Involvement of the general public in the collection of observations of the environment has gained momentum under the term “citizen science”. These observations help scientists in their understanding of local processes, and create awareness and commitment in the environmental stewardship of the general public. Fundamental to citizen science is not only a healthy participation, but also the scientific merit of the observations made. In these pages we briefly highlight the science behind the Eye On Water App and give reference to publicly available information, including open-access peer-reviewed journal articles.

A prime sensation

Colour is a sensation that originates in the human perception of radiation that reaches our eyes between the wavelengths of 380 and720 nm. Since the beginning of the 20th century, the science of human colour perception (colourimetry) has been well studied [1]. Since that time, colour has become more and more important in societal communication, as is evident from the development in colour printing, colour screens (television, computer monitors, tablets), digital cameras, and smartphones. Therefore, colour was chosen in the European Citclops (Citizens’ observatories for coast and ocean optical monitoring) project [2,3] as a primary parameter to involve citizens in the monitoring of natural waters.

Water has a colour

The intrinsic colour of natural waters is determined by the spectral absorption and scattering characteristics and the concentrations of dissolved and suspended coloured compounds. There are three main components that alter the colour of oceans, coastal- and inland waters: 1) Coloured dissolved organic matter (CDOM), 2) Sediment load (Total suspended material, TSM) and 3) Gross biological activity (estimated generally through the chlorophyll-a concentration, Chl-a). These components are important water quality indicators [4] and commonly monitored by water managers to comply with the European water directives [5].

Colour changes every day, month and year

Changes in the optical compounds in aquatic systems result in a change of colour and can be detected. These changes can be due to natural causes, such as plankton blooms, river outflows (transport of organic materials, nutrients and minerals), changing meteorological conditions or can be linked to anthropogenic activities. To determine if a change in colour is due to a particular anthropogenic activity, it is important to collect long-term data on the colour and clarity of water bodies with high accuracy [6]. Water colour is measured now for over 130 years and surprising large changes in colour have been recorded worldwide [7]. The Global Climate Observing System (GCOS) defined a number of essential climate variables (ECVs), which are physical, chemical or biological variables that critically contribute to the characterization of Earth's climate. Ocean Colour (OC) is one of the ECV.

The 21 values of colour

This high accuracy can only be obtained if colour can be quantified beyond descriptive words like “green”, “green-blue”, “brown”, and so on. Around 1900 scientist like Forel and Ule found a way for a consistent measure of ‘the water colour’ by using human perception to compare the colour of chemical solutions to colours of natural waters. This Forel-Ule (FU) scale is a historical standard that has recently been calibrated with state-of-the-art spectrometers [8]. The scale was developed because of technological limitations that existed at the end of the 19th century. Although trained observers can discriminate many colours, the FU scale is limited to just 21 very different colours that span the colours from the clearest oceans to the colours from the muddiest dark pools and rivers. It was proven that the colour-comparison methodology can be transferred and expanded to nowadays measuring techniques using Smartphones, like in EoW!

behind the science1 // 1.jpg (190 K)  behind the science2 // 2.jpg (201 K)  behind the science3 // 3.jpg (309 K)

Quality Control

Smartphones have cameras and displays that collect and show images. After an initial assessment of the quality of colour measurements with Smart phones [9] the App was developed. Since that time many campaigns and laboratory tests have been carried out up to the present day. Results have been submitted to peer-reviewed journals and published. Below a quick reference guide is given to these publications:

What is described, where?

Validation: Measurements with one- or more well calibrated spectrometers, taken at the same time and location as the EoW app, form the backbone of validation measurements. These were carried out at the North Sea, Dutch inland waters [10] plus 13 lakes, reservoirs and one river in Australia [11].

Image processing: An image from a Smart phone camera does not provide the same colour as a spectrometer. Multiple software steps must be taken before these two colours can be matched. The required algorithms are described in the Water Colour from Digital Images (WACODI) article [11]. The original software was written in Matlab, but subsequently rewritten and upgraded in Python. The latest version is freely available ‘here’ [12].

Hue angle: The transmission spectra of the original 21 FU scales were calibrated in the laboratory, see [8] and references therein. The spectra can be transformed to 21 discrete positions in the chromaticity diagram. It was realized already in 2013 that the colour derived from spectrometers can have a continuous value in the chromaticity diagram, instead of the 21 discrete values. In [13] the hue angle is defined, as well as in many other papers that subsequently use this parameter.[14,15,16] Satellites.

Satellites: Since the launch of the NASA’s instrument SeaWiFs in 1997, the oceans have been observed continuously by so-called polar-orbiting satellites that make a full image of the surface in less than 3 days. Normally, the pixel size of these observations has dimensions in the order of 1 km. That is really more than sufficient to monitor the ocean’s biological activity. It was proven in [14] that the hue angle and FU index can be deduced from SeaWiFS and subsequent ocean-colour instruments (MODIS, MERIS, OLCI) with high accuracy.

Satellites for Citizen science

Most people live and observe their environment close to shore or close to inland waters, like rivers, lakes and reservoirs. There are satellites that have the spatial resolution and spectral information to provide the hue angle [16]. These instruments do not have an overpass within days, but have the huge advantage that they provide information on a scale that is perfect for the local measurements by citizens; 10-30 meters. We foresee that these maps of hue angle over a lake, river or reservoir [17] can be combined with local measurements by the EoW app.

References (Open Access, unless otherwise stated)

  1. CIE, 1931. https://en.wikipedia.org/wiki/CIE_1931_color_space (accessed on 18 February 2021).
  2. Citclops (Citizens’ Observatory for Coast and Ocean Optical Monitoring). Available online: www.citclops.eu (accessed on 18 February 2021).
  3. Ceccaroni, L., Piera, J. , Wernand, M.R., Zielinski, O., Busch, J.A., Van Der Woerd, H.J., Bardaji, R., Friedrichs, A., Novoa, S., Thijsse, P., Velickovski, F., Blaas, M., Dubsky, K. Citclops: A next-generation sensor system for the monitoring of natural waters and a citizens' observatory for the assessment of ecosystems’ status. PLoS ONE 2020, 15(3): e0230084. https://doi.org/10.1371/journal.pone.0230084
  4. IOCCG. Why Ocean Color ? The Societal Benefits of Ocean- Color Technology. Eds: Platt T, Hoepffner N, Stuart V, Brown C. editors. 2007. https://ioccg.org/wp-content/uploads/2015/10/ioccg-report-07.pdf
  5. European Water Framework Directive. 2006. See for example https://ec.europa.eu/environment/water/water-framework/index_en.html
  6. WMO. The second report on the adequacy of the global observing systems for climate in support of the UNFCCC. World Meteorological Organization. 2003. Executive summary, WMO/TD No. 1143. 85 p.
  7. Wernand, M.R.; Van der Woerd, H.J.; Gieskes. W.W.C. Trends in ocean colour and chlorophyll concentration from 1889 to present. PLoS ONE 2013, doi:10.1371/journal.pone.0063766.
  8. Novoa, S.; Wernand, M.R.; Van der Woerd, H.J. The Forel-Ule scale revisited spectrally: Preparation protocols, transmission measurements and chromaticity. J. Eur. Opt. Soc. RP 2013, 8, 13057, doi:10.2971/jeos.2013.13057.
  9. QR Report, 2013. See http://citclops.eu/the-project/public-deliverables and open the “Key scientific aspects of quality control” report.
  10. Novoa, S.; Wernand, M.R.; Van der Woerd, H.J. WACODI: A generic algorithm to derive the intrinsic color of natural waters from digital images. Limnol. Oceanogr. Methods 2015, 13, 697–711. See https://www.researchgate.net/profile/Hans-Woerd
  11. Malthus, T.J.; Ohmsen, R.; Van der Woerd, H.J. An Evaluation of Citizen Science Smartphone Apps for Inland Water Quality Assessment. Remote Sens. 2020, 12, 1578. https://doi.org/10.3390/rs12101578
  12. WACODY Python code, 2021https://bitbucket.csiro.au/projects/ASC/repos/wacodi/browse/python
  13. Wernand, M.R.; Hommersom, A.; van der Woerd, H.J. MERIS-based ocean colour classification with the discrete Forel-Ule scale. Ocean Sci. 2013, 9, 477–487.
  14. Van der Woerd, H.J.; Wernand, M.R. Hue angle product for low to medium spectral resolution optical satellite sensors. Remote Sens. 2018, 10, 180; doi:10.3390/rs10020180.
  15. Busch, J.A.; Badají, R.; Ceccaroni, L.; Friedrichs, A.; Piera, J.; Simon, C.; Thijsse, P.; Wernand, M.; Van der Woerd, H.J.; Zielinski, O. Citizen bio-optical observations from coast- and ocean and their compatibility with ocean colour satellite measurements. Remote Sens. 2016, 8, 879, doi:10.3390/rs8110879.
  16. Van der Woerd, H.J., Wernand, M.R., 2018. Hue-Angle Product for Low to Medium Spatial Resolution Optical Satellite Sensors. Remote Sens. 2018, 10, 180. doi:10.3390/rs10020180
  17. Lehmann, M.K., Nguyen, U., Allan, M., Van der Woerd, H.J. Colour Classification of 1,486 Lakes Across a Wide Range of Optical Water Types. Remote Sens. 2018, 10, 1273; doi:10.3390/rs10081273