Is Ocean Reflectance Acquired by Citizen Scientists Robust for Science Applications?
AbstractMonitoring the dynamics of the productivity of ocean water and how it affects fisheries is essential for management. It requires data on proper spatial and temporal scales, which can be provided by operational ocean colour satellites. However, accurate productivity data from ocean colour imagery is only possible with proper validation of, for instance, the atmospheric correction applied to the images. In situ water reflectance data are of great value due to the requirements for validation and reflectance is traditionally measured with the Surface Acquisition System (SAS) solar tracker system. Recently, an application for mobile devices, “HydroColor”, was developed to acquire water reflectance data. We examined the accuracy of the water reflectance measures acquired by HydroColor with the help of both trained and untrained citizens, under different environmental conditions. We used water reflectance data acquired by SAS solar tracker and by HydroColor onboard the BC ferry Queen of Oak Bay from July to September 2016. Monte Carlo permutation F tests were used to assess whether the differences between measurements collected by SAS solar tracker and HydroColor with citizens were significant. Results showed that citizen HydroColor measurements were accurate in red, green, and blue bands, as well as red/green and red/blue ratios under different environmental conditions. In addition, we found that a trained citizen obtained higher quality HydroColor data especially under clear skies at noon. View Full-Text
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Yang, Y.; Cowen, L.L.; Costa, M. Is Ocean Reflectance Acquired by Citizen Scientists Robust for Science Applications? Remote Sens. 2018, 10, 835.
Yang Y, Cowen LL, Costa M. Is Ocean Reflectance Acquired by Citizen Scientists Robust for Science Applications? Remote Sensing. 2018; 10(6):835.Chicago/Turabian Style
Yang, Yuyan; Cowen, Laura L.; Costa, Maycira. 2018. "Is Ocean Reflectance Acquired by Citizen Scientists Robust for Science Applications?" Remote Sens. 10, no. 6: 835.
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