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Burggraaff, O, Werther, M, Boss, ES, Simis, SGH and Snik, F 2022 Accuracy and Reproducibility of Above-Water Radiometry With Calibrated Smartphone Cameras Using RAW Data. Frontiers in Remote Sensing, 3. https://doi.org/10.3389/frsen.2022.940096
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Abstract/Summary
Consumer cameras, especially on smartphones, are popular and effective instruments for above-water radiometry. The remote sensing reflectance Rrs is measured above the water surface and used to estimate inherent optical properties and constituent concentrations. Two smartphone apps, HydroColor and EyeOnWater, are used worldwide by professional and citizen scientists alike. However, consumer camera data have problems with accuracy and reproducibility between cameras, with systematic differences of up to 40% in intercomparisons. These problems stem from the need, until recently, to use JPEG data. Lossless data, in the RAW format, and calibrations of the spectral and radiometric response of consumer cameras can now be used to significantly improve the data quality. Here, we apply these methods to above-water radiometry. The resulting accuracy in Rrs is around 10% in the red, green, and blue (RGB) bands and 2% in the RGB band ratios, similar to professional instruments and up to 9 times better than existing smartphone-based methods. Data from different smartphones are reproducible to within measurement uncertainties, which are on the percent level. The primary sources of uncertainty are environmental factors and sensor noise. We conclude that using RAW data, smartphones and other consumer cameras are complementary to professional instruments in terms of data quality. We offer practical recommendations for using consumer cameras in professional and citizen science
| Item Type: | Publication - Article |
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| Additional Keywords: | citizen science, eyeonwater, hydrocolor, lake balaton, ocean color, reflectance, smartphone, validation |
| Divisions: | Plymouth Marine Laboratory > Science Areas > Earth Observation Science and Applications |
| Depositing User: | S Hawkins |
| Date made live: | 14 Jul 2022 09:16 |
| Last Modified: | 14 Jul 2022 09:16 |
| URI: | https://plymsea.ac.uk/id/eprint/9732 |
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