Water is all around us and is vital for all aspects of life. Studying the various compounds and life forms that inhabit natural waters lets us better understand the world around us.Remote sensing... Show moreWater is all around us and is vital for all aspects of life. Studying the various compounds and life forms that inhabit natural waters lets us better understand the world around us.Remote sensing enables global measurements with rapid response and high consistency. Citizen science provides new knowledge and greatly increases the scientific and social impact of research.In this thesis, we investigate several aspects of citizen science and remote sensing of water, with a focus on uncertainty and accessibility. We improve existing techniques and develop new methods to use smartphone cameras for accessible remote sensing of water. Show less
Burggraaff, O.; Werther, M.; Boss E.S.; Simis, S.G.H.; Snik, F. 2022
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... Show moreConsumer 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. Show less
