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EyeOnWater | HydroColor |
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(a) Required image(s) |
Water surface image | Gray card, sky, and water surface images |
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(b) Reference material |
Digitalized FU colour comparator scale as reference material. The user can add information on modern FU scale and Secchi disc measurements | No reference material is required |
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(c) RGB transfer function |
From sRGB of water surface image to xyz chromaticity coordinates | From sRGB of gray card, sky, and water surface images to π
πΊπ΅ |
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(d) Colour space conditions |
XYZ colour space; not dependent on the device used. Also, the resulting chromaticity coordinates do not depend on the illumination condition of which the image was taken | π
πΊπ΅ colour space; dependent on the device used. This is because it is influenced by the specific spectral response function of the capturing device. Also, it depends on the illumination condition of which the image was taken |
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(e) Estimated water quality variables |
Water surface colour translated to FUI | Water turbidity (0β80 NTU), SPM (g/m3), and backscattering coefficient in the red (mβ1) |
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(f) Advantages |
It is only the upwelling light from the water surface that carries any useful information on the water body. By this, it only requires an image of the water surface which would be easier for citizen monitoring | In deriving the π
πΊπ΅ using the three images, error incurred from each image as a result of the smartphone cancels out. Thus, the phone camera needs no calibration |
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(g) Disadvantages |
The weather conditions of the location are given as parameter values to be selected by the user concerning the location and not of the pertaining condition of the location. This can result in an optimistic estimate of water quality variables without correcting sun-sky glint effects on the water surface image | Does not take into account the weather conditions such as the wind which can affect the resulting output. It is cumbersome for citizens who would like to take random measurements without the availability of a gray card |
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