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Groetsch, Philipp M. M.; Gege, Peter; Simis, Stefan G. H.; Eleveld, Marieke A.; Peters, Steef (2017)
Publisher: dsfsdf
Languages: English
Types: Article
Subjects: Institut für Methodik der Fernerkundung, EA0, Experimentelle Verfahren
A three-component reflectance model (3C) is applied to above-water radiometric measurements to derive remote-sensing reflectance Rrs(l). 3C provides a spectrally resolved offset D(l) to correct for residual sun and sky radiance (Rayleigh- and aerosol-scattered) reflections on the water surface that were not represented by sky radiance measurements. 3C is validated with a data set of matching above- and below-water radiometric measurements collected in the Baltic Sea, and compared against a scalar offset correction D. Correction with D(l) instead of D consistently reduced the (mean normalized root-mean-square) deviation between Rrs(l) and reference reflectances to comparable levels for clear (D: 14.3 +- 2.5 %, D(l): 8.2 +- 1.7 %), partly clouded (D: 15.4 +- 2.1 %, D(l): 6.5 +- 1.4 %), and completely overcast (D: 10.8 +- 1.7 %, D(l): 6.3 +- 1.8 %) sky conditions. The improvement was most pronounced under inhomogeneous sky conditions when measurements of sky radiance tend to be less representative of surface-reflected radiance.Accounting for both sun glint and sky reflections also relaxes constraints on measurement geometry, which was demonstrated based on a semi-continuous daytime data set recorded in an eutrophic freshwater lake in the Netherlands. Rrs(l) that were derived throughout the day varied spectrally by less than 2 % relative standard deviation. Implications on measurement protocols are discussed. An open source software library for processing reflectance measurements was developed and is made publicly available.
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    • 9. K. G. Ruddick, V. De Cauwer, Y.-J. Park, and G. Moore, “Seaborne measurements of near infrared water-leaving reflectance: The similarity spectrum for turbid waters,” Limnol. Oceanog. 51, 1167-1179 (2006).
    • 10. S. G. Simis and J. Olsson, “Unattended processing of shipborne hyperspectral reflectance measurements,” Rem. Sens. Environ. 135, 202-212 (2013).
    • 11. V. Martinez-Vicente, S. G. H. Simis, R. Alegre, P. E. Land, and S. B. Groom, “Above-water reflectance for the evaluation of adjacency effects in earth observation data: Initial results and methods comparison for near-coastal waters in the western channel, UK,” J. Euro. Opt. Soc. 8, 13060 (2013).
    • 12. Z. Lee, Y.-h. Ahn, C. Mobley, and R. Arnone, “Removal of surface-reflected light for the measurement of remote-sensing reflectance from an above-surface platform,” Opt. Express 18, 171-182 (2010).
    • 13. T.-W. Cui, Q.-J. Song, J.-W. Tang, and J. Zhang, “Spectral variability of sea surface skylight reflectance and its effect on ocean color.” Opt. Express 21, 24929-24941 (2013).
    • 14. L. G. Sokoletsky and F. Shen, “Optical closure for remote-sensing reflectance based on accurate radiative transfer approximations: the case of the Changjiang (Yangtze) River Estuary and its adjacent coastal area, China,” Int. J. Rem. Sens. 35, 4193-4224 (2014).
    • 15. D. A. Toole, D. A. Siegel, D. W. Menzies, M. J. Neumann, and R. C. Smith, “Remote-sensing reflectance determinations in the coastal ocean environment: impact of instrumental characteristics and environmental variability.” Appl. Opt. 39, 456-469 (2000).
    • 16. X. Zhang, S. He, A. Shabani, P.-W. Zhai, and K. Du, “Spectral sea surface reflectance of skylight,” Opt. Express 25, A1 (2017).
    • 17. P. Gege, “The water color simulator WASI: an integrating software tool for analysis and simulation of optical in situ spectra,” Comput. Geosci. 30, 523-532 (2004).
    • 18. W. Gregg and K. Carder, “A simple spectral solar irradiance model for cloudless maritime atmospheres,” Limonol. Oceanog. 35, 1657-1675 (1990).
    • 19. P. Gege, “Analytic model for the direct and diffuse components of downwelling spectral irradiance in water.” Appl. Opt. 51, 1407-1419 (2012).
    • 20. K. Dörnhöfer, A. Göritz, P. Gege, B. Pflug, and N. Oppelt, “Water Constituents and Water Depth Retrieval from Sentinel-2A - A First Evaluation in an Oligotrophic Lake,” Rem. Sens. 8, 941 (2016).
    • 21. P. Gege, “WASI-2D: A software tool for regionally optimized analysis of imaging spectrometer data from deep and shallow waters,” Comput. Geosci. 62, 208-215 (2014).
    • 22. P. Gege, “A Case Study at Starnberger See for Hyperspectral Bathymetry Mapping Using Inverse Modeling,” in “WHISPERS 2014,” (2014), pp. 1-4.
    • 23. J. T. O. Kirk, Light and photosynthesis in aquatic ecosystems (Cambridge University, 1994).
    • 24. C. Stedmon, S. Markager, and H. Kaas, “Optical Properties and Signatures of Chromophoric Dissolved Organic Matter (CDOM) in Danish Coastal Waters,” Estuar. Coastal Shelf Sci. 51, 267-278 (2000).
    • 25. A. Albert and Mobley, “An analytical model for subsurface irradiance and remote sensing reflectance in deep and shallow case-2 waters,” Opt. Express 11, 2873-2890 (2003).
    • 26. H. Buiteveld, J. H. M. Hakvoort, and M. Donze, “Optical properties of pure water,” Proc. SPIE 174, 2258 (1994).
    • 27. A. Morel, “Optical properties of pure water and pure sea water,” in “Optical Aspects of Oceanography,” , N. G. Jerlov and E. Steemann Nielsen, eds. (Academic Press, 1974), Chap. 1, pp. 1-24.
    • 28. P. Gege, “Characterization of the phytoplankton in Lake Constance for classification by remote sensing,” Arch. Hydrobiol. Spec. Issues Advanc. Limnol. 0, 179-193 (1998).
    • 29. T. Heege, “Flugzeuggestutzte Fernerkundung von Wasserinhaltsstoffen im Bodensee,” Ph.D. thesis, Freie Universitat Berlin (2000).
    • 30. Z. Lee, K. L. Carder, C. D. Mobley, R. G. Steward, and J. S. Patch, “Hyperspectral remote sensing for shallow waters. I. A semianalytical model.” Appl. Opt. 37, 6329-6338 (1998).
    • 31. H. R. Gordon, J. W. Brown, O. B. Brown, R. H. Evans, and R. C. Smith, “A semianalytic radiance model of ocean color,” J. Coastal Res. 93, 10909-10924 (1988).
    • 32. P. Gege and P. Groetsch, “A spectral model for correcting sun glint and sky glint,” in “Proceedings of Ocean Optics XXIII” (2016).
    • 33. R. H. Byrd, P. Lu, J. Nocedal, and C. Zhu, “A Limited Memory Algorithm for Bound Constrained Optimization,” SIAM J. Sci. Comput. 16, 1190-1208 (1995).
    • 34. H. J. Gons, “Optical teledetection of chlorophyll a in turbid inland waters,” Environ. Sci. Technol. 33, 1127-1132 (1999).
    • 35. D. Stramski and J. Dera, “On the mechanism for producing flashing light under a wind-disturbed water surface,” Oceanologia 25 (1988).
    • 36. Y. You, D. Stramski, M. Darecki, and G. W. Kattawar, “Modeling of wave-induced irradiance fluctuations at near-surface depths in the ocean: a comparison with measurements,” Appl. Opt. 49, 1041-1053 (2010).
    • 37. M. Hieronymi and A. Macke, “Spatiotemporal underwater light field fluctuations in the open ocean,” J. Euro. Opt. Soc. Rapid Publ. 5, 1-8 (2010).
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