Abstract
A method is considered for rendering coastal water depths according to multi- and hyperspectral remote sensing imagery in the visible and near-infrared spectral regions. The depth is recovered for each pixel on the basis of solution of the inverse problem, which consists in artificial neural network learning with the use of a semianalytical model of radiation transfer in water, taking into account the effects of light scattering and absorption in the underwater light field, at least in three informative spectral channels for each bottom type. A possibility of adjusting the learning process is provided by the use of regression algorithms for determining organic and mineral impurities in water from their in-situ measurements. We enriched the library of the spectral characteristics of different bottom types and found informative identifiers for them. The results are tested on aircraft and hyperspectral space imagery data.
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References
H. R. Gordon and W. R. McCluney, “Estimation of the depth of sunlight penetration in the sea for remote sensing,” Appl. Opt. 14 (2), 413–416 (1975).
D. R. Lyzenga, “Passive remote sensing techniques for mapping water depth and bottom features,” Appl. Opt. 17 (3), 379–383 (1978).
R. P. Stumpf and K. Holderied, “Determination of water depth with high-resolution satellite imagery over variable bottom types,” Liminol. Oceanogr. 48 (1), 547–556 (2003).
Remote Sensing in Meteorology, Oceanography and Hydrology, Ed. by A.P. Crackness (Ellis Horwood, Chichester, 1981).
Ocean Optics. Vol. 1. Physical Ocean Optics (Nauka, Moscow, 1983) (in Russian).
V. N. Adamenko, K. Ya. Kondrat’ev, D. V. Pozdnyakov, and L. V. Chekhin, Radiation Regime and Optical Properties of Lakes (Gidrometeoizdat, Leningrad, 1991) [in Russian].
V. G. Astafurov, T. V. Evsyutkin, K. V. Kuriyanovich, and A. V. Skorokhodov, “Statistical model of cirrus cloud textural features based on MODIS satellite images,” Opt. Atmos. Okeana 27 (7), 640–646 (2014).
Z. Lee, K. L. Carder, S. K. Hawes, R. G. Steward, T. G. Peacock, and C. O. Davis, “A model for interpretation of hyperspectral remote-sensing reflectance,” Appl. Opt. 33 (24), 5721–5732 (1994).
A. Bricaud, M. Babin, A. Morel, and H. Claustre, “Variability in the chlorophyll-specific absorption coefficients of natural phytoplankton: Analysis and parameterization,” J. Geophys. Res., C 100 (7), 13321–13332 (1995).
H. R. Gordon, O. B. Brown, R. H. Evans, J. W. Brown, R. C. Smith, K. S. Baker, and D. K. Clark, “A semianalytic radiance model of ocean color,” J. Geophys. Res., D 93 (9), 10909–10924 (1988).
K. L. Carder, F. R. Chen, Z. P. Lee, S. K. Hawes, and D. Kamykowski, “Semianalytic moderate-resolution imaging spectrometer algorithms for chlorophyll a and absorption with bio-optical domains based on nitratedepletion temperatures,” J. Geophys. Res., C 104 (3), 5403–5422 (1999).
http://zhurnal.mipt.ru.
A. Morel and B. Gentili, “Diffuse reflectance of oceanic waters. II. Bidirectional aspects,” Appl. Opt. 32 (33), 6864–6879 (1993).
O. V. Kopelevich, V. I. Burenkov, S. V. Vazyulya, S. V. Sheberstov, A. A. Terekhova, and A. P. Shibalkova, “Consideration of solar radiation shallow water bottom reflection in the processing of satellite color scanner data,” Sovrem. Probl. Distantsionnogo Zondirovaniya Zemli Kosmosa 5 (2), 117–127 (2008).
http://navionics.ru/katalog-kart/itemlist/category/33-navionics-gold-small-rossiya.
A. V. Markov, O. V. Grigorieva, A. G. Saidov, D. V. Zhukov, and V. F. Mochalov, “Estimation of the ecological state of the Saint Petersburg sea port water area with the use of the aerospace imagery thematic processing software complex,” Geomatika, 3, 17–21 (2013).
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Original Russian Text © O.V. Grigorieva, D.V. Zhukov, A.V. Markov, V.F. Mochalov, 2017, published in Optika Atmosfery i Okeana.
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Grigorieva, O.V., Zhukov, D.V., Markov, A.V. et al. The retrieval of the coastal water depths from data of multi- and hyperspectral remote sensing imagery. Atmos Ocean Opt 30, 7–12 (2017). https://doi.org/10.1134/S1024856017010067
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DOI: https://doi.org/10.1134/S1024856017010067