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Spectral analysis and identification of floating algal blooms in oceans and lakes based on HY-1C/D CZI observations

  • role： First author第一作者
  • Affiliation：

    College of Marine Science, University of South Florida, St. Petersburg 33701, USA

  • Email：lqi@usf.edu
  • Introduction：齐琳，研究方向为藻华遥感。E-mail： lqi@usf.edu
QI Lin1,  
  • role： Corresponding author通信作者
  • Affiliation：

    College of Marine Science, University of South Florida, St. Petersburg 33701, USA

  • Email：huc@usf.edu
  • Introduction：胡传民，研究方向为海洋光学与水色遥感。E-mail： huc@usf.edu
HU Chuanmin1*,  
  • Affiliation：

    International Institute for Earth System Science, Nanjing University, Nanjing 210023, China

LU Yingcheng2,  
  • Affiliation：

    Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210046, China

MA Ronghua3

Resümee

In recent years, various types of floating algal blooms have been reported in oceans and lakes around the world. These include “green tides” of Ulva, “golden tides” of Sargassum, “red tides” of Noctiluca, and cyanobacterial blooms, among others. These floating algal blooms not only represent hazards to the marine and lake ecosystems, but also cause economic losses and human health problems. The launch of new satellite ocean color sensors can improve the monitoring capability of existing satellites for floating algal blooms.to evaluate the capacity of HY-1C/D CZI sensors (50 m resolution, 3-day revisit) in detecting and differentiating various types of floating algal blooms, and to analyze the spectral characteristics of blooms of several major floating algae using CZI data. Based on the types and distributions of major floating algal blooms in the global oceans and lakes, CZI data are obtained and analyzed for their spectral characteristics from the visually identified bloom features in the CZI false-color Red-Green-Blue images. The spectral characteristics are presented from the difference spectra between the identified image features and the surrounding waters, thus minimizing the impact of atmospheric signals and water signals on the spectra. All floating algal blooms show elevated reflectance in the near infrared wavelengths. In the visible wavelength range, the spectral shapes of Ulva prolifera, Sargassum horneri, and red Noctiluca scintillas are different and therefore can be differentiated from each other. Other blooms, for example Trichodesmium blooms or Microcystis blooms, can also be differentiated once some ancillary information is available.Based on the spectral features and combined with the environmental characteristics, the multi-band Hy-1C/D CZI images are found to be able to detect and differentiate different floating algal blooms. This capacity is important for monitoring floating algal blooms in the Yellow Sea and East China Sea where “multi-tide outbreaks” of Ulva, Sargassum, and Noctiluca may occur at the same time. Because of the high spatial and temporal resolutions, such a capacity is expected to make HY-1C/D CZI an important satellite sensor in near real-time monitoring as well as in quantitative analysis of floating algal blooms in the near future.

Schlüsselwort

floating algae;HY-1C/D CZI;Ulva;Sargassum;Noctiluca;cyanobacteria

References

  1. 1.
    Bi Y X, Zhang S Y, Wang W D and Wu Z L. 2014. Vertical distribution pattern of Sargassum horneri and its relationship with environmental factors around Gouqi Island. Acta Ecologica Sinica, 34(17): 4931-4937
  2. 2.
    Binding C E, Greenberg T A, Mccullough G, Watson S B and Page E. 2018. An analysis of satellite-derived chlorophyll and algal bloom indices on Lake Winnipeg. Journal of Great Lakes Research, 44(3): 436-446
  3. 3.
    Blondeau-Patissier D, Brando V E, Lønborg C, Leahy S M and Dekker A G. 2018. Phenology of Trichodesmium spp. blooms in the Great Barrier Reef lagoon, Australia, from the ESA-MERIS 10-year mission. PLoS One, 13(12): e0208010
  4. 4.
    Capone D G, Zehr J P, Paerl H W, Bergman B and Carpenter E J. 1997. Trichodesmium, a globally significant marine cyanobacterium. Science, 276(5316): 1221-1229
  5. 5.
    Chen Y L, Wan J H, Zhang J, Ma Y J, Wang L, Zhao J H and Wang Z Z. 2019. Spatial-temporal distribution of golden tide based on high-resolution satellite remote sensing in the South Yellow Sea. Journal of Coastal Research, 90: 221-227
  6. 6.
    Do Rosário Gomes H, Goes J I, Matondkar S G P, Buskey E J, Basu S, Parab S and Thoppil P. 2014. Massive outbreaks of Noctiluca scintillans blooms in the Arabian Sea due to spread of hypoxia. Nature Communications, 5: 4862
  7. 7.
    Elbraechter M and Qi Y. 1998. Aspects of noctiluca (Dinophyceae) population dynamics//Physiological Ecology of Harmful Algal Blooms. Berlin, Heidelberg: Springer-Verlag: 315-336
  8. 8.
    Ganf G G. 1974. Diurnal mixing and the vertical distribution of phytoplankton in a shallow equatorial lake (Lake George, Uganda). The Journal of Ecology, 62(2): 611-629
  9. 9.
    Gower J, Hu C M, Borstad G and King S. 2006. Ocean color satellites show extensive lines of floating Sargassum in the Gulf of Mexico. IEEE Transactions on Geoscience and Remote Sensing, 44(12): 3619-3625
  10. 10.
    Gower J, King S and Young E. 2014. Global remote sensing of Trichodesmium. International Journal of Remote Sensing, 35(14): 5459-5466
  11. 11.
    Granéli E and Turner J T. 2006. Ecology of Harmful Algae. Berlin Heidelberg: Springer
  12. 12.
    Hansen P J, Miranda L and Azanza R. 2004. Green Noctiluca scintillans: a dinoflagellate with its own greenhouse. Marine Ecology Progress Series, 275: 79-87
  13. 13.
    Harrison P J, Furuya K, Glibert P M, Xu J, Liu H B, Yin K, Lee J H W, Anderson D M, Gowen R, Al-Azri A R and Ho A Y T. 2011. Geographical distribution of red and green Noctiluca scintillans. Chinese Journal of Oceanology and Limnology, 29(4): 807-831
  14. 14.
    Hu C M, Feng L, Hardy R F and Hochberg E J. 2015. Spectral and spatial requirements of remote measurements of pelagic Sargassum macroalgae. Remote Sensing of Environment, 167: 229-246
  15. 15.
    Hu C M, Li D Q, Chen C S, Ge J Z, Muller-Karger F E, Liu J P, Yu F and He M X. 2010. On the recurrent Ulva prolifera blooms in the Yellow Sea and East China Sea. Journal of Geophysical Research: Oceans, 115(C5): C05017
  16. 16.
    Hu C M, Li X F, Pichel W G and Muller-Karger F. 2009. Detection of natural oil slicks in the NW Gulf of Mexico using MODIS imagery. Geophysical Research Letters, 36(1): L01604
  17. 17.
    Hu C M, Murch B, Barnes B B, Wang M Q, Maréchal J P, Franks J, Johnson D, Lapointe B, Goodwin D, Schell J and Siuda A. 2016. Sargassum watch warns of incoming seaweed. Eos, 97(22), 10-15
  18. 18.
    Hu C M, Wang M Q, Lapointe B E, Brewton R A and Hernandez F J. 2021. On the Atlantic pelagic Sargassum’s role in carbon fixation and sequestration. Science of the Total Environment, 781: 146801
  19. 19.
    Hu L B, Hu C M and He M X. 2017. Remote estimation of biomass of Ulva prolifera macroalgae in the Yellow Sea. Remote Sensing of Environment, 192: 217-227
  20. 20.
    Hu Z M, Uwai S, Yu S H, Komatsu T, Ajisaka T and Duan D L. 2011. Phylogeographic heterogeneity of the brown macroalga Sargassum horneri (Fucaceae) in the northwestern Pacific in relation to late Pleistocene glaciation and tectonic configurations. Molecular Ecology, 20(18): 3894-3909
  21. 21.
    Huang X G, Wang D F, Bao M L, Gong F and Bai Y. 2018. Spectral characteristics of Sargassum horneri in seawater//Proceedings Volume 10850, Ocean Optics and Information Technology. Beijing, China: SPIE
  22. 22.
    Kang Y. 2020. The ocean sheds “blue tears”, who is she crying for? Contemporary Tourism, 18(15): 3-5
  23. 23.
    Karl D, Letelier R, Tupas L, Dore J, Christian J and Hebel D. 1997. The role of nitrogen fixation in biogeochemical cycling in the subtropical North Pacific Ocean. Nature, 388(6642): 533-538
  24. 24.
    Kiφrboe T and Titelman J. 1998. Feeding, prey selection and prey encounter mechanisms in the heterotrophic dinoflagellate Noctiluca scintillans. Journal of Plankton Research, 20(8): 1615-1636
  25. 25.
    Komatsu T, Mizuno S, Natheer A, Kantachumpoo A, Tanaka K, Morimoto A, Hsiao S T, Rothäusler E A, Shishidou H, Aoki M and Ajisaka T. 2014. Unusual distribution of floating seaweeds in the East China Sea in the early spring of 2012. Journal of Applied Phycology, 26(2): 1169-1179
  26. 26.
    Komatsu T, Tatsukawa K, Filippi J B, Sagawa T, Matsunaga D, Mikami A, Ishida K, Ajisaka T, Tanaka K, Aoki M, Wang W D, Liu H F, Zhang S D, Zhou M D and Sugimoto T. 2007. Distribution of drifting seaweeds in eastern East China Sea. Journal of Marine Systems, 67(3/4): 245-252
  27. 27.
    Lapointe B E, Brewton R A, Herren L W, Wang M, Hu C, Mcgillicuddy D J, Lindell S, Hernandez F J and Morton P L. 2021. Nutrient content and stoichiometry of pelagic Sargassum reflects increasing nitrogen availability in the Atlantic Basin. Nature Communications, 12: 3060
  28. 28.
    Li Y S, Chen S G, Xue C, Zhang T L and Zhang Y X. 2020. Distribution of bioluminescence intensity and the driving factor analysis in the Yellow sea and Bohai sea in summer. Oceanologia et Limnologia Sinica, 51(6): 1391-1401
  29. 29.
    Liang C, Liu L, Liu J Q, Zou B, Zou Y R and Cui S X. 2020. Extracting mangrove information using MNF transformation based on HY-1C CZI spectral indices reconstruction data. Haiyang Xuebao, 42(4): 104-112
  30. 30.
    Liang S, Qian H L and Qi Y Z. 2000. Problem on the red tide in coastal China sea. Ecological Science, 19(4) : 44-50
  31. 31.
    Liu D Y, Keesing J K, Dong Z J, Zhen Y, Di B P, Shi Y J, Fearns P and Shi P. 2010. Recurrence of the world’s largest green-tide in 2009 in Yellow Sea, China: porphyra yezoensis aquaculture rafts confirmed as nursery for macroalgal blooms. Marine Pollution Bulletin, 60(9): 1423-1432
  32. 32.
    Liu J Q, Zeng T, Ye X M, Liu J P and Ma X F. 2021. Monitoring of ice crack changes and fracture processes on the Antarctic Brent Ice Shelf by HY-1C/D satellite. Haiyang Xuebao, 43(7): 205-206
  33. 33.
    Ma R H, Tang J W, Duan H T and Pan D L. 2009. Progress in lake water color remote sensing. Journal of Lake Sciences, 21(2): 143-158
  34. 34.
    Ma X Y. 2020. The gift and warning of the sea - "blue tears". Knowledge is Power, (6) : 28-29
  35. 35.
    McKinna L I W. 2015. Three decades of ocean-color remote-sensing Trichodesmium spp. in the World’s oceans: a review. Progress in Oceanography, 131: 177-199
  36. 36.
    McKinna L I W, Furnas M J and Ridd P V. 2011. A simple, binary classification algorithm for the detection of Trichodesmium spp. within the Great Barrier Reef using MODIS imagery. Limnology and Oceanography: Methods, 9(2): 50-66
  37. 37.
    Mikelsons K and Wang M H. 2018. Interactive online maps make satellite ocean data accessible. Eos, 99 (10.1029).
  38. 38.
    Paerl H W and Huisman J. 2008. Blooms like it hot. Science, 320(5872): 57-58
  39. 39.
    Paerl H W and Huisman J. 2009. Climate change: a catalyst for global expansion of harmful cyanobacterial blooms. Environmental Microbiology Reports, 1(1): 27-37
  40. 40.
    Paerl H W, Xu H, McCarthy M J, Zhu G W, Qin B Q, Li Y P and Gardner W S. 2011. Controlling harmful cyanobacterial blooms in a hyper-eutrophic lake (Lake Taihu, China): the need for a dual nutrient (N and P) management strategy. Water Research, 45(5): 1973-1983
  41. 41.
    Qi L and Hu C M. 2021. To what extent can Ulva and Sargassum be detected and separated in satellite imagery?. Harmful Algae, 103: 102001
  42. 42.
    Qi L, Hu C M, Duan H T, Cannizzaro J and Ma R H. 2014. A novel MERIS algorithm to derive cyanobacterial phycocyanin pigment concentrations in a eutrophic lake: theoretical basis and practical considerations. Remote Sensing of Environment, 154: 298-317
  43. 43.
    Qi L, Hu C M, Barnes B B, Lapointe B E, Chen Y L, Xie Y Y and Wang M H. 2022a. Climate and Anthropogenic Controls of Seaweed Expansions in the East China Sea and Yellow Sea. Geophysical Research Letters, 49: e2022GL098185
  44. 44.
    Qi L, Hu C M, Liu J Q, Ma R H, Zhang Y J and Zhang S. 2022b. Noctiluca blooms in the East China Sea bounded by ocean fronts. Harmful Algae, 112: 102172
  45. 45.
    Qi L, Hu C M, Mikelsons K, Wang M H, Lance V, Sun S J, Barnes B B, Zhao J and Van Der Zande D. 2020. In search of floating algae and other organisms in global oceans and lakes. Remote Sensing of Environment, 239: 111659
  46. 46.
    Qi L, Hu C M, Visser P M and Ma R H. 2018. Diurnal changes of cyanobacteria blooms in Taihu Lake as derived from GOCI observations. Limnology and Oceanography, 63(4): 1711-1726
  47. 47.
    Qi L, Hu C M, Wang M Q, Shang S L and Wilson C. 2017. Floating algae blooms in the East China Sea. Geophysical Research Letters, 44(22): 11501-11509
  48. 48.
    Qi L, Hu C M, Xing Q G and Shang S L. 2016. Long-term trend of Ulva prolifera blooms in the western Yellow Sea. Harmful Algae, 58: 35-44
  49. 49.
    Qi L, Tsai S F, Chen Y L, Le C F and Hu C M. 2019. In search of red Noctiluca scintillans blooms in the East China Sea. Geophysical Research Letters, 46(11): 5997-6004
  50. 50.
    Qi Y Z, Huang W J and Qiu X H. 1991. Population dynamic time series models of Noctiluca scintillans in Da-Pong Bay South China Sea. Journal of Jinan University, 12(3): 96-103
  51. 51.
    Qin B Q, Yang G J, Ma J R, Deng J M, Li W, Wu T F, Liu L Z, Gao G, Zhu G W, Zhang Y L. 2016. Dynamics of variability and mechanism of harmful cyanobacteria bloom in Lake Taihu, China. Chinese Science Bulletin, 61(7) : 759-770
  52. 52.
    Shen Y F, Liu J Q, Ding J, Jiao J N, Sun S J and Lu Y C. 2020. HY-1C COCTS and CZI observation of marine oil spills in the South China Sea. Journal of Remote Sensing (Chinese), 24(8): 933-944
  53. 53.
    Smetacek V and Zingone A. 2013. Green and golden seaweed tides on the rise. Nature, 504(7478): 84-88
  54. 54.
    Su L, Shan T F, Pang S J and Li J. 2018. Analyses of the genetic structure of Sargassum horneri in the Yellow Sea: implications of the temporal and spatial relations among floating and benthic populations. Journal of Applied Phycology, 30(2): 1417-1424
  55. 55.
    Sun D Y, Chen Y, Wang S Q, Zhang H L, Qiu Z F, Mao Z H and He Y J. 2021. Using Landsat 8 OLI data to differentiate Sargassum and Ulva prolifera blooms in the South Yellow Sea. International Journal of Applied Earth Observation and Geoinformation, 98: 102302
  56. 56.
    Sun J and Guo S J. 2011. Dinoflagellate heterotrophy. Acta Ecologica Sinica, 31(20): 6270-6286
  57. 57.
    Tian Y, Li T, Hu S M, Xie X D and Liu S. 2020. Temporal and spatial characteristics of harmful algal blooms in Guangdong coastal area. Marine Environmental Science, 39(1): 1-8
  58. 58.
    Uhlig G and Sahling G. 1990. Long-term studies on Noctiluca scintillans in the German Bight population dynamics and red tide phenomena 1968-1988. Netherlands Journal of Sea Research, 25(1/2): 101-112
  59. 59.
    Umezaki I. 1984. Ecological studies of Sargassum horneri (Turner) C. Agardh in Obama Bay, Japan Sea. Bulletin of the Japanese Society of Scientific Fisheries, 50(7): 1193-1200
  60. 60.
    Van Mol B, Ruddick K, Astoreca R, Park Y and Nechad B. 2007. Optical detection of a Noctiluca scintillans bloom. EARSeL eProceedings, 6: 130-137
  61. 61.
    Walsby A E. 1994. Gas vesicles. Microbiological Reviews, 58(1): 94-144
  62. 62.
    Wang L, Lin X, Goes J I and Lin S J. 2016. Phylogenetic analyses of three genes of Pedinomonas noctilucae, the green endosymbiont of the marine dinoflagellate Noctiluca scintillans, reveal its affiliation to the order Marsupiomonadales (Chlorophyta, Pedinophyceae) under the reinstated name Protoeuglena noctilucae. Protist, 167(2): 205-216
  63. 63.
    Wang M Q and Hu C M. 2016. Mapping and quantifying Sargassum distribution and coverage in the Central West Atlantic using MODIS observations. Remote Sensing of Environment, 183: 350-367
  64. 64.
    Xing Q G, An D Y, Zheng X Y, Wei Z N, Wang X H, Li L, Tian L Q and Chen J. 2019. Monitoring seaweed aquaculture in the Yellow Sea with multiple sensors for managing the disaster of macroalgal blooms. Remote Sensing of Environment, 231: 111279
  65. 65.
    Xing Q G, Guo R H, Wu L L, An D Y, Cong M, Qin S and Li X R. 2017. High-resolution satellite observations of a new hazard of golden tides caused by floating sargassum in winter in the Yellow Sea. IEEE Geoscience and Remote Sensing Letters, 14(10): 1815-1819
  66. 66.
    Yang X X, Yang Y, Xu C Y, Ji H H and Cheng X S. 2019. Changes of red tide of nocturnal algae in Fujian and Zhejiang waters from 2009 to 2019 and analysis of main environmental factors//Third Annual Conference on Ocean Development and Management. Hefei: 71-78
  67. 67.
    Zhang Y Y, He P M, Li H M, Li G, Liu J H, Jiao F L, Zhang J H, Huo Y Z, Shi X Y, Su R G, Ye N H, Liu D Y, Yu R C, Wang Z L, Zhou M J and Jiao N Z. 2019. Ulva prolifera green-tide outbreaks and their environmental impact in the Yellow Sea, China. National Science Review, 6(4): 825-838
  68. 68.
    Zhang Y L, Van Dijk M A, Liu M L, Zhu G W and Qin B Q. 2009. The contribution of phytoplankton degradation to chromophoric dissolved organic matter (CDOM) in eutrophic shallow lakes: field and experimental evidence. Water Research, 43(18): 4685-4697
  69. 69.
    Zhou Q, Liu J Q, Wang J R, Deng S Q and Tian L Q. 2020. Study on turbidity monitoring of Zhiyin Lake and Huangjia Lake in Wuhan during the COVID-19 epidemic using HY-1C satellite CZI data. Geomatics and Information Science of Wuhan Universit, 45(5): 676-681
  70. 70.
    Zohary T and Robarts R D. 1990. Hyperscums and the population dynamics of Microcystis aeruginosa. Journal of Plankton Research, 12(2): 423-432

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