基于里海综合考察的水型图在上层透光带过程特征分析中的应用

作者

  • V. V. Rostovtseva Shirshov Institute of Oceanology, Russian Academy of Sciences

DOI:

https://doi.org/10.29006/1564-2291.JOR-2025.53(4).3

关键词:

近岸海域, 被动光学测深, 海水光谱辐射系数, 悬浮颗粒物浓度, 浮游植物色素浓度, 溶解有机, 物浓度, 外来杂质

摘要

通过对水型图中海水三种主要天然成分浓度数据所对应的点位进行分析,我们得以推断出中里海里海东 岸阿克套附近地区普遍存在的本地过程与外部输入过程。这些结论得到了综合科考船测站垂直剖面测量 结果的证实。

参考


  1. Alikas, K., I. Ansko, V. Vabson, A. Ansper, K. Kangro, K. Uudeberg, and M. Ligi, 2020: Consistency of radiometric satellite data over lakes and coastal waters with local field measurements. Remote Sens., 12 (4), 616, EDN: BSZQXX, https://doi.org/10.3390/rs12040616.

  2. Atwood, E. C., T. Jackson, A. Laurenson, B. F. Jönsson, E. Spyrakos, D. Jiang, G. Sent, N. Selmes, S. Simis, and O. Danne, 2024: Framework for Regional to Global Extension of Optical Water Types for Remote Sensing of Optically Complex Transitional Water Bodies. Remote Sens., 16 (17), 3267, EDN: WZMARH, https://doi.org/10.3390/rs16173267.

  3. Drozdova, A. N., V. V. Pelevin, I. N. Krylov, E. A. Streltsova, and B. V. Konovalov, 2022: Dissolved Organic Matter of the Surface Water Layer of Gelendzhik Bay in September 2021 according to Fluorimetry and Lidar Measurements. Oceanology, 62 (6), 765–772, EDN: YEDOOX, https://doi.org/10.1134/S0001437022060030.

  4. Eleveld, M. A., A. B. Ruescas, A. Hommersom, T. S. Moore, S. W. M. Peters, and C. Brockmann, 2017: An optical classification tool for global lake waters. Remote Sens, 9 (5), 420–444, https://doi.org/10.3390/rs9050420.

  5. Giannini, F., B. P. V. Hunt, D. Jacoby, and M. Costa, 2021: Performance of OLCI Sentinel-3A Satellite in the Northeast Pacific Coastal Waters. Remote Sens. Environ, 256, 112317, EDN: IDMMIC, https://doi.org/10.1016/j.rse.2021.112317.

  6. Khlebopashev, P. V., A. A. Polukhin, K. V. Litvinov, G. V. Borisenko, M. V. Bukhanov, A. B. Grabovsky, P. O. Zavyalov, O. Yu. Kalinina, A. V. Kostyleva, V. V. Kremenetskiy, A. M. Seliverstova, and S. V. Stepanova, 2022: Expeditionary Studies of the Current State of the Volga River Avandelta Ecosystem during the Flow Period. Oceanology, 62 (5), 733–734, EDN: LUYREM, https://doi.org/10.1134/s000143702205006x.

  7. Konovalov, B. V., M. D. Kravchishina, N. A. Belyaev, and A. N. Novigatsky, 2014: Determination of the Concentration of Mineral Particles and Suspended Organic Substance based on their Spectral Absorption. Oceanology, 54 (5), 660–667, EDN: UFGGAH, https://doi.org/10.1134/S0001437014040067.

  8. Kravchishina, M. D., A. A. Klyuvitkin, V. N. Lukashin, N. V. Politova, A. N. Novigatsky, and A. P. Lisitsyn, 2018: Distribution of suspended particulate matter in the Caspian Sea. Russian Meteorology and Hydrology, 43 (10), 697–705, EDN: HUOHYF, https://doi.org/10.3103/S1068373918100096.

  9. Makkaveev, P. N., V. V. Gordeev, P. O. Zavialov, and A. K. Kurbaniyazov, 2018: Hydrochemical and Hydrological Conditions in the Ural River Lower Reachers and in the Caspean Sea Mouth Region at the Beginning of the Spring Flood. Russian Meteorology and Hydrology, 43 (10), 706–712, EDN: JNZFAS, https://doi.org/10.3103/S1068373918100102.

  10. Pope, R. M. and E. S. Fry, 1997: Absorption spectrum (380–700 nm) of pure water. Integrating cavity measurements. Appl. Opt., 36 (33), 8710–8723, https://doi.org/10.1364/AO.36.008710.

  11. Rostovtseva, V. V., 2016: Method for sea water absorption estimation on the basis of shipboard passive remote sensing data and pure sea water properties. Atmospheric and Oceanic Optics, 29 (2), 162–170, EDN: WUJCRJ, https://doi.org/10.1134/S102485601602010X.

  12. Rostovtseva, V. V., I. V. Goncharenko, B. V. Konovalov, and A. F. Alukaeva, 2018: Rapid Estimation of the Ecological State of Coastal Water Areas Based on Shipboard Passive Remote Optical Sensing of the Water Surface. Atmospheric and Oceanic Optics, 31 (3), 225–231, EDN: MANUDB, https://doi.org/10.1134/S1024856018030132.

  13. Rostovtseva, V. V., A. S. Izhitskiy, I. V. Goncharenko, B. V. Konovalov, and P. O. Zavialov, 2021: On the Influence of Hydrophysical Conditions on Representativeness of Hydrooptical Measurements for Coastal Regions of the Middle Caspian Sea as an Example. Atmospheric and Oceanic Optics, 34 (6), 649–657, EDN: MHZWXN, https://doi.org/10.1134/S1024856021060208.

  14. Rostovtseva, V. V., 2025: Comparative analysis of coastal water types based on passive optical sensing data. Journal of Oceanological Research, 53 (1), 5–17, EDN: AFJRQL, https://doi.ocean.ru/10.29006/1564-2291.JOR-2025.53(1).1.

  15. Salama, M. S., L. Spaias, K. Poser, S. Peters, and M. Laanen, 2022: Validation of Sentinel-2 (MSI) and Sentinel-3 (OLCI) Water Quality Products in Turbid Estuaries Using Fixed Monitoring Stations. Front. Remote Sens, 2, 808287, EDN: SSIRSN, https://doi.org/10.3389/frsen.2021.808287.

  16. Spyrakos, E., R. O’Donnell, P. D. Hunter, C. Miller, M. Scott, S. G. H. Simis, C. Neil, C. C. F. Barbosa, C. E. Binding, and S. Bradt, 2018: Optical Types of Inland and Coastal Waters. Limnol. Oceanogr., 63 (2), 846–870, EDN: YFTMQH, https://doi.org/10.1002/lno.10674.

  17. Warren, M. A., S. G. H. Simis, V. Martinez-Vicente, K. Poser, M. Bresciani, K. Alikas, E. Spyrakos, C. Giardino, and A. Ansper, 2019: Assessment of Atmospheric Correction Algorithms for the Sentinel-2A MultiSpectral Imager over Coastal and Inland Waters. Remote Sens. Environ., 225, 267–289, EDN: WZJTIO, https://doi.org/10.1016/j.rse.2019.03.018.

  18. Wozniak, B. and J. Dera, 2007: Light Absorption in Sea Water. New York: Springer Science+Business Media, LLC. 453 p., EDN: YCTTSV, https://doi.org/10.1007/978-0-387-49560-6.

  19. Xue, K., R. Ma, D. Wang, and M. Shen, 2019: Optical Classification of the Remote Sensing Reflectance and Its Application in Deriving the Specific Phytoplankton Absorption in Optically Complex Lakes. Remote Sens., 11 (2), 184, https://doi.org/10.3390/rs11020184.

已出版

2025-12-21

期次

栏目

海洋物理学与气候

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