Small hyperspectral imagers and lidars and their marine applications

He Sailing; Chen Xiang; Li Shuo; Yao Xinli; Xu Zhanpeng

doi:10.3788/IRLA202049.0203001

Volume 49 Issue 2

Mar. 2020

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He Sailing, Chen Xiang, Li Shuo, Yao Xinli, Xu Zhanpeng. Small hyperspectral imagers and lidars and their marine applications[J]. Infrared and Laser Engineering, 2020, 49(2): 0203001-0203001. doi: 10.3788/IRLA202049.0203001

Citation:

He Sailing, Chen Xiang, Li Shuo, Yao Xinli, Xu Zhanpeng. Small hyperspectral imagers and lidars and their marine applications[J]. Infrared and Laser Engineering, 2020, 49(2): 0203001-0203001. doi: 10.3788/IRLA202049.0203001

Small hyperspectral imagers and lidars and their marine applications

doi: 10.3788/IRLA202049.0203001

1. Zhejiang University Centre for Optical and Electromagnetic Research, National Engineering Research Center for Optical Instruments, Hangzhou 310058, China;
2. Ningbo Research Institute, Zhejiang University, Ningbo 315100, China

Received Date: 2019-11-05
Rev Recd Date: 2019-12-03
Publish Date: 2020-03-02

Abstract

Ocean is an important part of the earth's ecological environment. Exploration and exploitation of marine resources may easily cause serious damage to ocean, such as large-scale oil spill, pollution and red tide caused by oil and gas exploitation. Hyperspectral imaging technology can obtain both image information and spectral information at the same time, and has important applications in marine in-situ detection. In this paper, some recent works about hyperspectral imagers are reviewed, including a small-scale hyperspectral imager combined with fluorescence technology for the classification of oil spills and the estimation of oil film thickness, a multi-mode hyperspectral marine in-situ detection system (in three modes:common reflection or transmission imaging, telescopic imaging and microscopic imaging) for hyperspectral detection of different algae and spores of some fish infectious disease carriers. Hyperspectral technology combined with lidar technology has great potential in monitoring oil spill, red tide and other marine pollutants. An inelastic hyperspectral Scheimpflug lidar system and a ligh-sheet Scheimpflug lidar system are also reviewed. The former is for the type identification of oil spills through the fluorescence spectrum of oil spills, and the latter is for the detection of the 3D shapes of some manikin, shells and corals with the refraction correction at the air-water interface.
- hyperspectral imager,
- Scheimpflug lidar system,
- Scheimpflug imaging principle,
- oil spill,
- red tide,
- marine in-situ detection,
- 3D shape

References

[1]	Lu Y, Li X, Tian Q, et al. Progress in marine oil spill optical remote sensing:detected targets, spectral response characteristics, and theories[J]. Marine Geodesy, 2013, 36(3):334-346.
[2]	Fingas M, Brown C E. A Review of oil spill remote sensing[J]. Sensors, 2017, 18(1):91.
[3]	Hu J, Wang D. Monitoring method of ocean oil spilling based on remote sensing[J]. Environment Protection Science, 2014, 40(1):68-73. (in Chinese)
[4]	Hu C, Müller-Karger F E, Taylor C, et al. MODIS detects oil spills in lake maracaibo, venezuela[J]. Eos, Transactions American Geophysical Union, 2003, 84(33):313-319.
[5]	Lu Y, Tian Q, Li X. The remote sensing inversion theory of offshore oil slick thickness based on a two-beam interference model[J]. Science China Earth Sciences, 2011, 54(5):678-685.
[6]	Lu Y, Tian Q, Wang X, et al. Determining oil slick thickness using hyperspectral remote sensing in the Bohai Sea of China[J]. International Journal of Digital Earth, 2013, 6(1):76-93.
[7]	Leifer I, Lehr W J, Simecek-Beatty D, et al. State of the art satellite and airborne marine oil spill remote sensing:application to the BP deepwater horizon oil spill[J]. Remote Sensing of Environment, 2012, 124:185-209.
[8]	Lu Y, Zhan W, Hu C. Detecting and quantifying oil slick thickness by thermal remote sensing:a ground-based experiment[J]. Remote Sensing of Environment, 2016, 181:207-217.
[9]	Brekke C, Solberg A H S. Oil spill detection by satellite remote sensing[J]. Remote Sensing of Environment, 2005, 95(1):1-13.
[10]	Keramitsoglou I, Cartalis C, Kiranoudis C T. Automatic identification of oil spills on satellite images[J]. Environmental Modelling & Software, 2006, 21(5):640-652.
[11]	Brown C E, Fingas M F. Review of the development of laser fluorosensors for oil spill application[J]. Marine Pollution Bulletin, 2003, 47(9):477-484.
[12]	Lennon M, Babichenko S, Thomas N, et al. Detection and mapping of oil slicks in the sea by comined use of hyperspectral imagery and laser induced fluorescence[J]. EARSeL eProceedings, 2006, 5:120-128.
[13]	Jiang W T, Li J W, Yao X L, et al. Fluorescence hyperspectral imaging of oil samples and its quantitative applications in component analysis and thickness estimation[J]. Sensors, 2018, 18(12):10.
[14]	Gao F, Li J, Lin H, et al. Oil pollution discrimination by an inelastic hyperspectral Scheimpflug lidar system[J]. Opt Express, 2017, 25(21):25515-25522.
[15]	He L, Song X, Yu F, et al. Potential risk and prevention of phytoplankton outbreak to water-cooling system in nuclear power plant in Fangchenggang, Guangxi[J]. Oceanologiaet Limnologia Sinica, 2019, 50(3):700-706.(in Chinese)
[16]	Stumpf R P, Culver M E, Tester P A, et al. Monitoring Karenia brevis blooms in the Gulf of Mexico using satellite ocean color imagery and other data[J]. Harmful Algae, 2003, 2(2):147-160.
[17]	Alexander R, Gikuma-Njuru P, Imberger J. Identifying spatial structure in phytoplankton communities using multi-wavelength fluorescence spectral data and principal component analysis[J]. Limnology and Oceanography:Methods, 2012, 10(6):402-415.
[18]	Escoffier N, Bernard C, Hamlaoui S, et al. Quantifying phytoplankton communities using spectral fluorescence:the effects of species composition and physiological state[J]. Journal of Plankton Research, 2014, 37(1):233-247.
[19]	Gao F, Lin H, Chen K, et al. Light-sheet based two-dimensional Scheimpflug lidar system for profile measurements[J]. Optics Express, 2018, 26(21):27179-27188.
[20]	Chen K, Gao F, Chen X, et al. Overwater light-sheet Scheimpflug lidar system for an underwater three-dimensional profile bathymetry[J]. Applied Optics, 2019, 58(27):7643-7648.
[21]	Dirk C W, Delgado M F, Olguin M, et al. A prism-grating-prism spectral imaging approach[J]. Studies in Conservation, 2009, 54(2):77-89.
[22]	Cai F, Wang D, Zhu M, et al. Pencil-like imaging spectrometer for bio-samples sensing[J]. Biomedical Optics Express, 2017, 8(12):5427-5436.
[23]	Chen J, Cai F, He R, et al. Experimental demonstration of remote and compact imaging spectrometer based on mobile devices[J]. Sensors, 2018, 18(7):1989.
[24]	Li J, Jiang W, Yao X, et al. Fast quantitative fluorescence authentication of milk powder and vanillin by a line-scan hyperspectral system[J]. Applied Optics, 2018, 57(22):6276-6282.
[25]	Huseynova T, Waring G O, Roberts C, et al. Corneal biomechanics as a function of intraocular pressure and pachymetry by dynamic infrared signal and scheimpflug imaging analysis in normal eyes[J]. American Journal of Ophthalmology, 2014, 157(4):885-893.
[26]	Faria-Correia F, Ambrósio Jr R. Clinical applications of the scheimpflug principle in ophthalmology[J]. Revista Brasileira de Oftalmologia, 2016, 75:160-165.
[27]	Miks A, Novak J, Novak P. Analysis of imaging for laser triangulation sensors under Scheimpflug rule[J]. Optics Express, 2013, 21(15):18225-18235.
[28]	Zhao G, Ljungholm M, Malmqvist E, et al. Inelastic hyperspectral lidar for profiling aquatic ecosystems[J]. Laser & Photonics Reviews, 2016, 10(5):807-813.
[29]	Nakamura S. Background story of the invention of efficient InGaN blue-light-emitting diodes (nobel lecture)[J]. Angewandte Chemie International Edition, 2015, 54(27):7770-7788.
[30]	Pope R M, Fry E S. Absorption spectrum (380-700 nm) of pure water. II. Integrating cavity measurements[J]. Applied Optics, 1997, 36(33):8710-8723.
[31]	Sun L. Research on remote sensing technology of ocean environmental parameters based on laser induced fluorescence[D]. Harbin:Harbin Institute of Technology, 2016. (in Chinese)
[32]	Hakala T, Suomalainen J, Kaasalainen S, et al. Full waveform hyperspectral LiDAR for terrestrial laser scanning[J]. Optics Express, 2012, 20(7):7119-7127.

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通讯作者: 陈斌, bchen63@163.com

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Small hyperspectral imagers and lidars and their marine applications

1. Zhejiang University Centre for Optical and Electromagnetic Research, National Engineering Research Center for Optical Instruments, Hangzhou 310058, China;

2. Ningbo Research Institute, Zhejiang University, Ningbo 315100, China

Received Date: 2019-11-05

Rev Recd Date: 2019-12-03

Publish Date: 2020-03-02

Key words:

Abstract: Ocean is an important part of the earth's ecological environment. Exploration and exploitation of marine resources may easily cause serious damage to ocean, such as large-scale oil spill, pollution and red tide caused by oil and gas exploitation. Hyperspectral imaging technology can obtain both image information and spectral information at the same time, and has important applications in marine in-situ detection. In this paper, some recent works about hyperspectral imagers are reviewed, including a small-scale hyperspectral imager combined with fluorescence technology for the classification of oil spills and the estimation of oil film thickness, a multi-mode hyperspectral marine in-situ detection system (in three modes:common reflection or transmission imaging, telescopic imaging and microscopic imaging) for hyperspectral detection of different algae and spores of some fish infectious disease carriers. Hyperspectral technology combined with lidar technology has great potential in monitoring oil spill, red tide and other marine pollutants. An inelastic hyperspectral Scheimpflug lidar system and a ligh-sheet Scheimpflug lidar system are also reviewed. The former is for the type identification of oil spills through the fluorescence spectrum of oil spills, and the latter is for the detection of the 3D shapes of some manikin, shells and corals with the refraction correction at the air-water interface.

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Reference (32)

[1]	Lu Y, Li X, Tian Q, et al. Progress in marine oil spill optical remote sensing:detected targets, spectral response characteristics, and theories[J]. Marine Geodesy, 2013, 36(3):334-346.
[2]	Fingas M, Brown C E. A Review of oil spill remote sensing[J]. Sensors, 2017, 18(1):91.
[3]	Hu J, Wang D. Monitoring method of ocean oil spilling based on remote sensing[J]. Environment Protection Science, 2014, 40(1):68-73. (in Chinese)
[4]	Hu C, Müller-Karger F E, Taylor C, et al. MODIS detects oil spills in lake maracaibo, venezuela[J]. Eos, Transactions American Geophysical Union, 2003, 84(33):313-319.
[5]	Lu Y, Tian Q, Li X. The remote sensing inversion theory of offshore oil slick thickness based on a two-beam interference model[J]. Science China Earth Sciences, 2011, 54(5):678-685.
[6]	Lu Y, Tian Q, Wang X, et al. Determining oil slick thickness using hyperspectral remote sensing in the Bohai Sea of China[J]. International Journal of Digital Earth, 2013, 6(1):76-93.
[7]	Leifer I, Lehr W J, Simecek-Beatty D, et al. State of the art satellite and airborne marine oil spill remote sensing:application to the BP deepwater horizon oil spill[J]. Remote Sensing of Environment, 2012, 124:185-209.
[8]	Lu Y, Zhan W, Hu C. Detecting and quantifying oil slick thickness by thermal remote sensing:a ground-based experiment[J]. Remote Sensing of Environment, 2016, 181:207-217.
[9]	Brekke C, Solberg A H S. Oil spill detection by satellite remote sensing[J]. Remote Sensing of Environment, 2005, 95(1):1-13.
[10]	Keramitsoglou I, Cartalis C, Kiranoudis C T. Automatic identification of oil spills on satellite images[J]. Environmental Modelling & Software, 2006, 21(5):640-652.
[11]	Brown C E, Fingas M F. Review of the development of laser fluorosensors for oil spill application[J]. Marine Pollution Bulletin, 2003, 47(9):477-484.
[12]	Lennon M, Babichenko S, Thomas N, et al. Detection and mapping of oil slicks in the sea by comined use of hyperspectral imagery and laser induced fluorescence[J]. EARSeL eProceedings, 2006, 5:120-128.
[13]	Jiang W T, Li J W, Yao X L, et al. Fluorescence hyperspectral imaging of oil samples and its quantitative applications in component analysis and thickness estimation[J]. Sensors, 2018, 18(12):10.
[14]	Gao F, Li J, Lin H, et al. Oil pollution discrimination by an inelastic hyperspectral Scheimpflug lidar system[J]. Opt Express, 2017, 25(21):25515-25522.
[15]	He L, Song X, Yu F, et al. Potential risk and prevention of phytoplankton outbreak to water-cooling system in nuclear power plant in Fangchenggang, Guangxi[J]. Oceanologiaet Limnologia Sinica, 2019, 50(3):700-706.(in Chinese)
[16]	Stumpf R P, Culver M E, Tester P A, et al. Monitoring Karenia brevis blooms in the Gulf of Mexico using satellite ocean color imagery and other data[J]. Harmful Algae, 2003, 2(2):147-160.
[17]	Alexander R, Gikuma-Njuru P, Imberger J. Identifying spatial structure in phytoplankton communities using multi-wavelength fluorescence spectral data and principal component analysis[J]. Limnology and Oceanography:Methods, 2012, 10(6):402-415.
[18]	Escoffier N, Bernard C, Hamlaoui S, et al. Quantifying phytoplankton communities using spectral fluorescence:the effects of species composition and physiological state[J]. Journal of Plankton Research, 2014, 37(1):233-247.
[19]	Gao F, Lin H, Chen K, et al. Light-sheet based two-dimensional Scheimpflug lidar system for profile measurements[J]. Optics Express, 2018, 26(21):27179-27188.
[20]	Chen K, Gao F, Chen X, et al. Overwater light-sheet Scheimpflug lidar system for an underwater three-dimensional profile bathymetry[J]. Applied Optics, 2019, 58(27):7643-7648.
[21]	Dirk C W, Delgado M F, Olguin M, et al. A prism-grating-prism spectral imaging approach[J]. Studies in Conservation, 2009, 54(2):77-89.
[22]	Cai F, Wang D, Zhu M, et al. Pencil-like imaging spectrometer for bio-samples sensing[J]. Biomedical Optics Express, 2017, 8(12):5427-5436.
[23]	Chen J, Cai F, He R, et al. Experimental demonstration of remote and compact imaging spectrometer based on mobile devices[J]. Sensors, 2018, 18(7):1989.
[24]	Li J, Jiang W, Yao X, et al. Fast quantitative fluorescence authentication of milk powder and vanillin by a line-scan hyperspectral system[J]. Applied Optics, 2018, 57(22):6276-6282.
[25]	Huseynova T, Waring G O, Roberts C, et al. Corneal biomechanics as a function of intraocular pressure and pachymetry by dynamic infrared signal and scheimpflug imaging analysis in normal eyes[J]. American Journal of Ophthalmology, 2014, 157(4):885-893.
[26]	Faria-Correia F, Ambrósio Jr R. Clinical applications of the scheimpflug principle in ophthalmology[J]. Revista Brasileira de Oftalmologia, 2016, 75:160-165.
[27]	Miks A, Novak J, Novak P. Analysis of imaging for laser triangulation sensors under Scheimpflug rule[J]. Optics Express, 2013, 21(15):18225-18235.
[28]	Zhao G, Ljungholm M, Malmqvist E, et al. Inelastic hyperspectral lidar for profiling aquatic ecosystems[J]. Laser & Photonics Reviews, 2016, 10(5):807-813.
[29]	Nakamura S. Background story of the invention of efficient InGaN blue-light-emitting diodes (nobel lecture)[J]. Angewandte Chemie International Edition, 2015, 54(27):7770-7788.
[30]	Pope R M, Fry E S. Absorption spectrum (380-700 nm) of pure water. II. Integrating cavity measurements[J]. Applied Optics, 1997, 36(33):8710-8723.
[31]	Sun L. Research on remote sensing technology of ocean environmental parameters based on laser induced fluorescence[D]. Harbin:Harbin Institute of Technology, 2016. (in Chinese)
[32]	Hakala T, Suomalainen J, Kaasalainen S, et al. Full waveform hyperspectral LiDAR for terrestrial laser scanning[J]. Optics Express, 2012, 20(7):7119-7127.

Small hyperspectral imagers and lidars and their marine applications

doi: 10.3788/IRLA202049.0203001

Abstract

References

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通讯作者: 陈斌, bchen63@163.com

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