Abstract

An inelastic hyperspectral Scheimpflug lidar system is developed for range-resolved oil pollution detection and discrimination. A theory of system parametric design is built for aquatic circumstances, and laser-induced fluorescence spectra with an excitation wavelength of 446 nm are employed to detect oil pollution. Seven kinds of typical oil samples are tested and well distinguished using the principal component analysis (PCA) and linear discriminant analysis (LDA) methods. It has been shown that blue laser diodes (LD) have great potential for oil pollution detection, and our system could be further utilized for more applications in both marine and terrestrial environments.

© 2017 Optical Society of America

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References

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  1. M. D. C. Martín, N. V. Yarovenko, C. P. Gómez, J. L. L. Soto, and J. M. T. Palenzuela, “Oil pollution detection using spectral fluorescent signatures (SFS),” Environ. Earth Sci. 73, 2909–2915 (2015).
  2. X.-l. Li, Y.-h. Chen, J. Li, J. Jiang, Z. Ni, and Z.-s. Liu, “Time-resolved fluorescence spectroscopy of oil spill detected by ocean lidar,” in Optical Measurement Technology and Instrumentation, (International Society for Optics and Photonics, 2016), 101550Q.
  3. M. Fingas and C. Brown, “Review of oil spill remote sensing,” Mar. Pollut. Bull. 83(1), 9–23 (2014).
    [PubMed]
  4. C. E. Brown and M. F. Fingas, “Review of the development of laser fluorosensors for oil spill application,” Mar. Pollut. Bull. 47(9-12), 477–484 (2003).
    [PubMed]
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    [PubMed]
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  7. S. Svanberg, “Fluorescence lidar monitoring of vegetation status,” Phys. Scripta 1995, 79 (1995).
  8. G. Cecchi, L. Pantani, V. Raimondi, L. Tomaselli, G. Lamenti, P. Tiano, and R. Chiari, “Fluorescence lidar technique for the remote sensing of stone monuments,” J. Cult. Herit. 1, 29–36 (2000).
  9. C. Brown, “Laser fluorosensors,” Oil Spill Sci. Technol, 171–184 (2011).
  10. M. Brydegaard, A. Gebru, and S. Svanberg, “Super Resolution Laser Radar with Blinking Atmospheric Particles----Application to Interacting Flying Insects,” Prog. Electromag. Res. 147, 141–151 (2014).
  11. L. Mei and M. Brydegaard, “Atmospheric aerosol monitoring by an elastic Scheimpflug lidar system,” Opt. Express 23(24), A1613–A1628 (2015).
    [PubMed]
  12. L. Mei and M. Brydegaard, “Continuous‐wave differential absorption lidar,” Laser Photonics Rev. 9, 629–636 (2015).
  13. E. Malmqvist, S. Jansson, S. Török, and M. Brydegaard, “Effective parameterization of laser radar observations of atmospheric fauna,” IEEE J. Sel. Top. Quantum Electron. 22, 327–334 (2016).
  14. G. Zhao, M. Ljungholm, E. Malmqvist, G. Bianco, L. A. Hansson, S. Svanberg, and M. Brydegaard, “Inelastic hyperspectral lidar for profiling aquatic ecosystems,” Laser Photonics Rev. 10, 807–813 (2016).
  15. M. Starzak and M. Mathlouthi, “Cluster composition of liquid water derived from laser-Raman spectra and molecular simulation data,” Food Chem. 82, 3–22 (2003).
  16. L. Mei, P. Lundin, M. Brydegaard, S. Gong, D. Tang, G. Somesfalean, S. He, and S. Svanberg, “Tea classification and quality assessment using laser-induced fluorescence and chemometric evaluation,” Appl. Opt. 51(7), 803–811 (2012).
    [PubMed]
  17. I. T. Jolliffe, “Principal Component Analysis and Factor Analysis,” in Principal component analysis (Springer, 1986), pp. 115–128.
  18. S. Wold, K. Esbensen, and P. Geladi, “Principal component analysis,” Chemometr. Intell. Lab. 2, 37–52 (1987).

2016 (2)

E. Malmqvist, S. Jansson, S. Török, and M. Brydegaard, “Effective parameterization of laser radar observations of atmospheric fauna,” IEEE J. Sel. Top. Quantum Electron. 22, 327–334 (2016).

G. Zhao, M. Ljungholm, E. Malmqvist, G. Bianco, L. A. Hansson, S. Svanberg, and M. Brydegaard, “Inelastic hyperspectral lidar for profiling aquatic ecosystems,” Laser Photonics Rev. 10, 807–813 (2016).

2015 (3)

M. D. C. Martín, N. V. Yarovenko, C. P. Gómez, J. L. L. Soto, and J. M. T. Palenzuela, “Oil pollution detection using spectral fluorescent signatures (SFS),” Environ. Earth Sci. 73, 2909–2915 (2015).

L. Mei and M. Brydegaard, “Continuous‐wave differential absorption lidar,” Laser Photonics Rev. 9, 629–636 (2015).

L. Mei and M. Brydegaard, “Atmospheric aerosol monitoring by an elastic Scheimpflug lidar system,” Opt. Express 23(24), A1613–A1628 (2015).
[PubMed]

2014 (2)

M. Brydegaard, A. Gebru, and S. Svanberg, “Super Resolution Laser Radar with Blinking Atmospheric Particles----Application to Interacting Flying Insects,” Prog. Electromag. Res. 147, 141–151 (2014).

M. Fingas and C. Brown, “Review of oil spill remote sensing,” Mar. Pollut. Bull. 83(1), 9–23 (2014).
[PubMed]

2012 (1)

2003 (2)

C. E. Brown and M. F. Fingas, “Review of the development of laser fluorosensors for oil spill application,” Mar. Pollut. Bull. 47(9-12), 477–484 (2003).
[PubMed]

M. Starzak and M. Mathlouthi, “Cluster composition of liquid water derived from laser-Raman spectra and molecular simulation data,” Food Chem. 82, 3–22 (2003).

2000 (1)

G. Cecchi, L. Pantani, V. Raimondi, L. Tomaselli, G. Lamenti, P. Tiano, and R. Chiari, “Fluorescence lidar technique for the remote sensing of stone monuments,” J. Cult. Herit. 1, 29–36 (2000).

1995 (1)

S. Svanberg, “Fluorescence lidar monitoring of vegetation status,” Phys. Scripta 1995, 79 (1995).

1990 (1)

1987 (1)

S. Wold, K. Esbensen, and P. Geladi, “Principal component analysis,” Chemometr. Intell. Lab. 2, 37–52 (1987).

Bianco, G.

G. Zhao, M. Ljungholm, E. Malmqvist, G. Bianco, L. A. Hansson, S. Svanberg, and M. Brydegaard, “Inelastic hyperspectral lidar for profiling aquatic ecosystems,” Laser Photonics Rev. 10, 807–813 (2016).

Brown, C.

M. Fingas and C. Brown, “Review of oil spill remote sensing,” Mar. Pollut. Bull. 83(1), 9–23 (2014).
[PubMed]

Brown, C. E.

C. E. Brown and M. F. Fingas, “Review of the development of laser fluorosensors for oil spill application,” Mar. Pollut. Bull. 47(9-12), 477–484 (2003).
[PubMed]

Brydegaard, M.

E. Malmqvist, S. Jansson, S. Török, and M. Brydegaard, “Effective parameterization of laser radar observations of atmospheric fauna,” IEEE J. Sel. Top. Quantum Electron. 22, 327–334 (2016).

G. Zhao, M. Ljungholm, E. Malmqvist, G. Bianco, L. A. Hansson, S. Svanberg, and M. Brydegaard, “Inelastic hyperspectral lidar for profiling aquatic ecosystems,” Laser Photonics Rev. 10, 807–813 (2016).

L. Mei and M. Brydegaard, “Atmospheric aerosol monitoring by an elastic Scheimpflug lidar system,” Opt. Express 23(24), A1613–A1628 (2015).
[PubMed]

L. Mei and M. Brydegaard, “Continuous‐wave differential absorption lidar,” Laser Photonics Rev. 9, 629–636 (2015).

M. Brydegaard, A. Gebru, and S. Svanberg, “Super Resolution Laser Radar with Blinking Atmospheric Particles----Application to Interacting Flying Insects,” Prog. Electromag. Res. 147, 141–151 (2014).

L. Mei, P. Lundin, M. Brydegaard, S. Gong, D. Tang, G. Somesfalean, S. He, and S. Svanberg, “Tea classification and quality assessment using laser-induced fluorescence and chemometric evaluation,” Appl. Opt. 51(7), 803–811 (2012).
[PubMed]

Cecchi, G.

G. Cecchi, L. Pantani, V. Raimondi, L. Tomaselli, G. Lamenti, P. Tiano, and R. Chiari, “Fluorescence lidar technique for the remote sensing of stone monuments,” J. Cult. Herit. 1, 29–36 (2000).

Chiari, R.

G. Cecchi, L. Pantani, V. Raimondi, L. Tomaselli, G. Lamenti, P. Tiano, and R. Chiari, “Fluorescence lidar technique for the remote sensing of stone monuments,” J. Cult. Herit. 1, 29–36 (2000).

Esbensen, K.

S. Wold, K. Esbensen, and P. Geladi, “Principal component analysis,” Chemometr. Intell. Lab. 2, 37–52 (1987).

Fingas, M.

M. Fingas and C. Brown, “Review of oil spill remote sensing,” Mar. Pollut. Bull. 83(1), 9–23 (2014).
[PubMed]

Fingas, M. F.

C. E. Brown and M. F. Fingas, “Review of the development of laser fluorosensors for oil spill application,” Mar. Pollut. Bull. 47(9-12), 477–484 (2003).
[PubMed]

Gebru, A.

M. Brydegaard, A. Gebru, and S. Svanberg, “Super Resolution Laser Radar with Blinking Atmospheric Particles----Application to Interacting Flying Insects,” Prog. Electromag. Res. 147, 141–151 (2014).

Geladi, P.

S. Wold, K. Esbensen, and P. Geladi, “Principal component analysis,” Chemometr. Intell. Lab. 2, 37–52 (1987).

Gómez, C. P.

M. D. C. Martín, N. V. Yarovenko, C. P. Gómez, J. L. L. Soto, and J. M. T. Palenzuela, “Oil pollution detection using spectral fluorescent signatures (SFS),” Environ. Earth Sci. 73, 2909–2915 (2015).

Gong, S.

Hansson, L. A.

G. Zhao, M. Ljungholm, E. Malmqvist, G. Bianco, L. A. Hansson, S. Svanberg, and M. Brydegaard, “Inelastic hyperspectral lidar for profiling aquatic ecosystems,” Laser Photonics Rev. 10, 807–813 (2016).

He, S.

Hengstermann, T.

Jansson, S.

E. Malmqvist, S. Jansson, S. Török, and M. Brydegaard, “Effective parameterization of laser radar observations of atmospheric fauna,” IEEE J. Sel. Top. Quantum Electron. 22, 327–334 (2016).

Lamenti, G.

G. Cecchi, L. Pantani, V. Raimondi, L. Tomaselli, G. Lamenti, P. Tiano, and R. Chiari, “Fluorescence lidar technique for the remote sensing of stone monuments,” J. Cult. Herit. 1, 29–36 (2000).

Ljungholm, M.

G. Zhao, M. Ljungholm, E. Malmqvist, G. Bianco, L. A. Hansson, S. Svanberg, and M. Brydegaard, “Inelastic hyperspectral lidar for profiling aquatic ecosystems,” Laser Photonics Rev. 10, 807–813 (2016).

Lundin, P.

Malmqvist, E.

G. Zhao, M. Ljungholm, E. Malmqvist, G. Bianco, L. A. Hansson, S. Svanberg, and M. Brydegaard, “Inelastic hyperspectral lidar for profiling aquatic ecosystems,” Laser Photonics Rev. 10, 807–813 (2016).

E. Malmqvist, S. Jansson, S. Török, and M. Brydegaard, “Effective parameterization of laser radar observations of atmospheric fauna,” IEEE J. Sel. Top. Quantum Electron. 22, 327–334 (2016).

Martín, M. D. C.

M. D. C. Martín, N. V. Yarovenko, C. P. Gómez, J. L. L. Soto, and J. M. T. Palenzuela, “Oil pollution detection using spectral fluorescent signatures (SFS),” Environ. Earth Sci. 73, 2909–2915 (2015).

Mathlouthi, M.

M. Starzak and M. Mathlouthi, “Cluster composition of liquid water derived from laser-Raman spectra and molecular simulation data,” Food Chem. 82, 3–22 (2003).

Mei, L.

Palenzuela, J. M. T.

M. D. C. Martín, N. V. Yarovenko, C. P. Gómez, J. L. L. Soto, and J. M. T. Palenzuela, “Oil pollution detection using spectral fluorescent signatures (SFS),” Environ. Earth Sci. 73, 2909–2915 (2015).

Pantani, L.

G. Cecchi, L. Pantani, V. Raimondi, L. Tomaselli, G. Lamenti, P. Tiano, and R. Chiari, “Fluorescence lidar technique for the remote sensing of stone monuments,” J. Cult. Herit. 1, 29–36 (2000).

Raimondi, V.

G. Cecchi, L. Pantani, V. Raimondi, L. Tomaselli, G. Lamenti, P. Tiano, and R. Chiari, “Fluorescence lidar technique for the remote sensing of stone monuments,” J. Cult. Herit. 1, 29–36 (2000).

Reuter, R.

Somesfalean, G.

Soto, J. L. L.

M. D. C. Martín, N. V. Yarovenko, C. P. Gómez, J. L. L. Soto, and J. M. T. Palenzuela, “Oil pollution detection using spectral fluorescent signatures (SFS),” Environ. Earth Sci. 73, 2909–2915 (2015).

Starzak, M.

M. Starzak and M. Mathlouthi, “Cluster composition of liquid water derived from laser-Raman spectra and molecular simulation data,” Food Chem. 82, 3–22 (2003).

Svanberg, S.

G. Zhao, M. Ljungholm, E. Malmqvist, G. Bianco, L. A. Hansson, S. Svanberg, and M. Brydegaard, “Inelastic hyperspectral lidar for profiling aquatic ecosystems,” Laser Photonics Rev. 10, 807–813 (2016).

M. Brydegaard, A. Gebru, and S. Svanberg, “Super Resolution Laser Radar with Blinking Atmospheric Particles----Application to Interacting Flying Insects,” Prog. Electromag. Res. 147, 141–151 (2014).

L. Mei, P. Lundin, M. Brydegaard, S. Gong, D. Tang, G. Somesfalean, S. He, and S. Svanberg, “Tea classification and quality assessment using laser-induced fluorescence and chemometric evaluation,” Appl. Opt. 51(7), 803–811 (2012).
[PubMed]

S. Svanberg, “Fluorescence lidar monitoring of vegetation status,” Phys. Scripta 1995, 79 (1995).

Tang, D.

Tiano, P.

G. Cecchi, L. Pantani, V. Raimondi, L. Tomaselli, G. Lamenti, P. Tiano, and R. Chiari, “Fluorescence lidar technique for the remote sensing of stone monuments,” J. Cult. Herit. 1, 29–36 (2000).

Tomaselli, L.

G. Cecchi, L. Pantani, V. Raimondi, L. Tomaselli, G. Lamenti, P. Tiano, and R. Chiari, “Fluorescence lidar technique for the remote sensing of stone monuments,” J. Cult. Herit. 1, 29–36 (2000).

Török, S.

E. Malmqvist, S. Jansson, S. Török, and M. Brydegaard, “Effective parameterization of laser radar observations of atmospheric fauna,” IEEE J. Sel. Top. Quantum Electron. 22, 327–334 (2016).

Wold, S.

S. Wold, K. Esbensen, and P. Geladi, “Principal component analysis,” Chemometr. Intell. Lab. 2, 37–52 (1987).

Yarovenko, N. V.

M. D. C. Martín, N. V. Yarovenko, C. P. Gómez, J. L. L. Soto, and J. M. T. Palenzuela, “Oil pollution detection using spectral fluorescent signatures (SFS),” Environ. Earth Sci. 73, 2909–2915 (2015).

Zhao, G.

G. Zhao, M. Ljungholm, E. Malmqvist, G. Bianco, L. A. Hansson, S. Svanberg, and M. Brydegaard, “Inelastic hyperspectral lidar for profiling aquatic ecosystems,” Laser Photonics Rev. 10, 807–813 (2016).

Appl. Opt. (2)

Chemometr. Intell. Lab. (1)

S. Wold, K. Esbensen, and P. Geladi, “Principal component analysis,” Chemometr. Intell. Lab. 2, 37–52 (1987).

Environ. Earth Sci. (1)

M. D. C. Martín, N. V. Yarovenko, C. P. Gómez, J. L. L. Soto, and J. M. T. Palenzuela, “Oil pollution detection using spectral fluorescent signatures (SFS),” Environ. Earth Sci. 73, 2909–2915 (2015).

Food Chem. (1)

M. Starzak and M. Mathlouthi, “Cluster composition of liquid water derived from laser-Raman spectra and molecular simulation data,” Food Chem. 82, 3–22 (2003).

IEEE J. Sel. Top. Quantum Electron. (1)

E. Malmqvist, S. Jansson, S. Török, and M. Brydegaard, “Effective parameterization of laser radar observations of atmospheric fauna,” IEEE J. Sel. Top. Quantum Electron. 22, 327–334 (2016).

J. Cult. Herit. (1)

G. Cecchi, L. Pantani, V. Raimondi, L. Tomaselli, G. Lamenti, P. Tiano, and R. Chiari, “Fluorescence lidar technique for the remote sensing of stone monuments,” J. Cult. Herit. 1, 29–36 (2000).

Laser Photonics Rev. (2)

G. Zhao, M. Ljungholm, E. Malmqvist, G. Bianco, L. A. Hansson, S. Svanberg, and M. Brydegaard, “Inelastic hyperspectral lidar for profiling aquatic ecosystems,” Laser Photonics Rev. 10, 807–813 (2016).

L. Mei and M. Brydegaard, “Continuous‐wave differential absorption lidar,” Laser Photonics Rev. 9, 629–636 (2015).

Mar. Pollut. Bull. (2)

M. Fingas and C. Brown, “Review of oil spill remote sensing,” Mar. Pollut. Bull. 83(1), 9–23 (2014).
[PubMed]

C. E. Brown and M. F. Fingas, “Review of the development of laser fluorosensors for oil spill application,” Mar. Pollut. Bull. 47(9-12), 477–484 (2003).
[PubMed]

Opt. Express (1)

Phys. Scripta (1)

S. Svanberg, “Fluorescence lidar monitoring of vegetation status,” Phys. Scripta 1995, 79 (1995).

Prog. Electromag. Res. (1)

M. Brydegaard, A. Gebru, and S. Svanberg, “Super Resolution Laser Radar with Blinking Atmospheric Particles----Application to Interacting Flying Insects,” Prog. Electromag. Res. 147, 141–151 (2014).

Other (4)

C. Brown, “Laser fluorosensors,” Oil Spill Sci. Technol, 171–184 (2011).

S. D. Christesen, C. N. Merrow, M. S. DeSha, A. Wong, M. W. Wilson, and J. C. Butler, “Ultraviolet fluorescence LIDAR detection of bioaerosols,” in SPIE's International Symposium on Optical Engineering and Photonics in Aerospace Sensing, (International Society for Optics and Photonics, 1994), 228–237.

X.-l. Li, Y.-h. Chen, J. Li, J. Jiang, Z. Ni, and Z.-s. Liu, “Time-resolved fluorescence spectroscopy of oil spill detected by ocean lidar,” in Optical Measurement Technology and Instrumentation, (International Society for Optics and Photonics, 2016), 101550Q.

I. T. Jolliffe, “Principal Component Analysis and Factor Analysis,” in Principal component analysis (Springer, 1986), pp. 115–128.

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Figures (6)

Fig. 1
Fig. 1 Scheimpflug principle: the image plane intersects both the lens and object planes when the object plane is not parallel to the lens plane. Oʹ and Oʹʹ are the origins of the lens and image planes, respectively; p I - the pixel position of the image sensor on the image plane, d -the distance to the lens from the object plane, α - the tilt angle of the lens plane to the object plane, β - the tilt angle of the image plane to the lens plane. M is the object point and Mʹ is the image point accordingly, which satisfies the lens equation, i.e., 1/u+1/v=1/f.
Fig. 2
Fig. 2 Scheimpflug principle applied to the underwater environment. (a) The light path which indicates that refraction of the laser beam must be taken into consideration. (b) The relationship between pixel number and distance with optical parameters: d = 0.306 m, f = 55 mm, α = 84°.
Fig. 3
Fig. 3 Schematic diagram of the inelastic hyperspectral Scheimpflug lidar system; the figure on the top left corner is the top view of the system. L1 and L2 are collimated lenses, and OF is the 450 nm long-pass optical filter. P1 and P2 are two symmetrical wedge prisms, and G is a transmission grating with 300 grooves per mm.
Fig. 4
Fig. 4 Light distribution as it appears at one occasion on the 2D-CMOS camera. An oil sample was measured at the range of 3.69 m. The effective spectral response curve is shown on top. The fluorescence spectra are obtained without instrument spectral response compensation.
Fig. 5
Fig. 5 Normalized spectra of seven kinds of oil samples
Fig. 6
Fig. 6 The relationship between PC1 and PC2 of seven kinds of oil samples

Tables (1)

Tables Icon

Table 1 Sources of the Oil Samples

Equations (6)

Equations on this page are rendered with MathJax. Learn more.

z = d[ p I ( sinβcosβcotα )+ v 0 ] p I ( cosβ+sinβcotα )+ v 0 cotα
v 0 = fd dfcosα
β=arctan( fsinα dfcosα )
M ' z = zf dcosα+zsinαf
M ' y = d( dcosα+zsinα ) dcosα+zsinαf
z cor = z M +( z z M ) cos θ 1 cos θ 2

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