Abstract

Abstract: The retrieval from space of a very weak fluorescence signal was studied in the O2A and O2B oxygen atmospheric absorption bands. The accuracy of the method was tested for the retrieval of the chlorophyll fluorescence and reflectance terms contributing to the sensor signal. The radiance at the top of the atmosphere was simulated by means of a commercial radiative-transfer program at a high resolution (0.1 cm−1). A test data set was generated in order to simulate sun-induced chlorophyll fluorescence at the top of the canopy. Reflectance terms were spectrally modeled using cubic splines and fluorescence by means of the sum of two Voigt functions. Sensor radiance residual minimization was performed in the presence of a multiplicative noise, thus ensuring that the sensor simulations were realistic. The study, which focused on the possibility of retrieving fluorescence with an accuracy better than 10%, was performed for instrument resolutions ranging from about 0.4 cm−1 to 2 cm−1 in order to test the algorithm for the characteristics of existing and planned hyper-spectral sensors. The algorithm was also used to retrieve fluorescence in the single O2A band at the OCO and TANSO-FTS instrument spectral resolutions.

© 2010 OSA

Full Article  |  PDF Article

References

  • View by:
  • |
  • |
  • |

  1. K. Smorenburg, G. B. Courreges-Lacoste, M. Berger, A. Court, U. del Bello, G. Langsdorf, H. Lichtentha-ler, C. Sioris, M. P. Stoll, and H. Visser, “Remote sensing of solar-induced fluorescence of vegetation,” Proc. SPIE 4542, 178–190 (2002).
    [CrossRef]
  2. C. Buschmann, “Variability and application of the chlorophyll fluorescence emission ratio red/far-red of leaves,” Photosynth. Res. 92(2), 261–271 (2007).
    [CrossRef] [PubMed]
  3. N. Subash and C. N. Mohanan, “Curve-fit Analysis of Chlorophyll Fluorescence Spectra: Application to Nutrient Stress Detection in Sunflower,” Remote Sens. Environ. 60(3), 347–356 (1997).
    [CrossRef]
  4. A. Kuze, H. Suto, M. Nakajima, and T. Hamazaki, “Thermal and near infrared sensor for carbon observation Fourier-transform spectrometer on the Greenhouse Gases Observing Satellite for greenhouse gases monitoring,” Appl. Opt. 48(35), 6716–6733 (2009).
    [CrossRef] [PubMed]
  5. H. Suto, A. Kuze, M. Nakajima, T. Hamazaki, T. Yokota, and G. Inoue, “Airborne SWIR FTS for GOSAT validation and calibration,” Proc. SPIE 7106, 71060M (2008).
    [CrossRef]
  6. R. Haring, R. Pollock, B. M. Sutin, and D. Crisp, “The Orbiting Carbon Observatory instrument optical design,” Proc. SPIE 5523, 51–62 (2004).
    [CrossRef]
  7. M. Meroni and R. Colombo, “Leaf level detection of solar induced chlorophyll fluorescence by means of a subnanometer resolution spectroradiometer,” Remote Sens. Environ. 103(4), 438–448 (2006).
    [CrossRef]
  8. J. R. Miller, M. Berger, Y. Goulas, S. Jacquemoud, J. Louis, N. Moise, G. Mohammed, J. Moreno, I. Moya, R. Pedrós, W. Verhoef, and P. J. Zarco-Tejada, “Development of a Vegetation Fluorescence Canopy Model,” ESTEC Contract No. 16365/02/NL/FF, Final Report, (2005).
  9. S. Jacquemoud and F. Baret, “PROSPECT: a model of leaf optical properties spectra,” Remote Sens. Environ. 34(2), 75–91 (1990).
    [CrossRef]
  10. W. Verhoef and H. Bach, “Coupled soil-leaf canopy and amosphere radiative transfer modelling to simulate hyperspectral multi-angular surface reflectance and TOA radiance data,” Remote Sens. Environ. 109(2), 166–182 (2007).
    [CrossRef]
  11. M. Meroni, M. Rossini, L. Guanter, L. Alonso, U. Rascher, R. Colombo, and J. Moreno, “Remote sensing of solar induced chlorophyll fluorescence: Review of methods and applications,” Remote Sens. Environ. 113(10), 2037–2051 (2009).
    [CrossRef]
  12. M. Mazzoni, P. Falorni, and S. Del Bianco, “Sun-induced leaf fluorescence retrieval in the O2-B atmospheric absorption band,” Opt. Express 16(10), 7014–7022 (2008).
    [CrossRef] [PubMed]
  13. S. Jacquemoud, F. Baret, B. Andrieu, F. M. Danson, and K. Jaggard, “Extraction of Vegetation Biophysical Parameters by Inversion of the PROSPECT+SAIL Models on Sugar Beet Canopy Reflectance Data. Application to TM and AVIRIS Sensors,” Remote Sens. Environ. 52(3), 163–172 (1995).
    [CrossRef]

2009

M. Meroni, M. Rossini, L. Guanter, L. Alonso, U. Rascher, R. Colombo, and J. Moreno, “Remote sensing of solar induced chlorophyll fluorescence: Review of methods and applications,” Remote Sens. Environ. 113(10), 2037–2051 (2009).
[CrossRef]

A. Kuze, H. Suto, M. Nakajima, and T. Hamazaki, “Thermal and near infrared sensor for carbon observation Fourier-transform spectrometer on the Greenhouse Gases Observing Satellite for greenhouse gases monitoring,” Appl. Opt. 48(35), 6716–6733 (2009).
[CrossRef] [PubMed]

2008

M. Mazzoni, P. Falorni, and S. Del Bianco, “Sun-induced leaf fluorescence retrieval in the O2-B atmospheric absorption band,” Opt. Express 16(10), 7014–7022 (2008).
[CrossRef] [PubMed]

H. Suto, A. Kuze, M. Nakajima, T. Hamazaki, T. Yokota, and G. Inoue, “Airborne SWIR FTS for GOSAT validation and calibration,” Proc. SPIE 7106, 71060M (2008).
[CrossRef]

2007

C. Buschmann, “Variability and application of the chlorophyll fluorescence emission ratio red/far-red of leaves,” Photosynth. Res. 92(2), 261–271 (2007).
[CrossRef] [PubMed]

W. Verhoef and H. Bach, “Coupled soil-leaf canopy and amosphere radiative transfer modelling to simulate hyperspectral multi-angular surface reflectance and TOA radiance data,” Remote Sens. Environ. 109(2), 166–182 (2007).
[CrossRef]

2006

M. Meroni and R. Colombo, “Leaf level detection of solar induced chlorophyll fluorescence by means of a subnanometer resolution spectroradiometer,” Remote Sens. Environ. 103(4), 438–448 (2006).
[CrossRef]

2004

R. Haring, R. Pollock, B. M. Sutin, and D. Crisp, “The Orbiting Carbon Observatory instrument optical design,” Proc. SPIE 5523, 51–62 (2004).
[CrossRef]

2002

K. Smorenburg, G. B. Courreges-Lacoste, M. Berger, A. Court, U. del Bello, G. Langsdorf, H. Lichtentha-ler, C. Sioris, M. P. Stoll, and H. Visser, “Remote sensing of solar-induced fluorescence of vegetation,” Proc. SPIE 4542, 178–190 (2002).
[CrossRef]

1997

N. Subash and C. N. Mohanan, “Curve-fit Analysis of Chlorophyll Fluorescence Spectra: Application to Nutrient Stress Detection in Sunflower,” Remote Sens. Environ. 60(3), 347–356 (1997).
[CrossRef]

1995

S. Jacquemoud, F. Baret, B. Andrieu, F. M. Danson, and K. Jaggard, “Extraction of Vegetation Biophysical Parameters by Inversion of the PROSPECT+SAIL Models on Sugar Beet Canopy Reflectance Data. Application to TM and AVIRIS Sensors,” Remote Sens. Environ. 52(3), 163–172 (1995).
[CrossRef]

1990

S. Jacquemoud and F. Baret, “PROSPECT: a model of leaf optical properties spectra,” Remote Sens. Environ. 34(2), 75–91 (1990).
[CrossRef]

Alonso, L.

M. Meroni, M. Rossini, L. Guanter, L. Alonso, U. Rascher, R. Colombo, and J. Moreno, “Remote sensing of solar induced chlorophyll fluorescence: Review of methods and applications,” Remote Sens. Environ. 113(10), 2037–2051 (2009).
[CrossRef]

Andrieu, B.

S. Jacquemoud, F. Baret, B. Andrieu, F. M. Danson, and K. Jaggard, “Extraction of Vegetation Biophysical Parameters by Inversion of the PROSPECT+SAIL Models on Sugar Beet Canopy Reflectance Data. Application to TM and AVIRIS Sensors,” Remote Sens. Environ. 52(3), 163–172 (1995).
[CrossRef]

Bach, H.

W. Verhoef and H. Bach, “Coupled soil-leaf canopy and amosphere radiative transfer modelling to simulate hyperspectral multi-angular surface reflectance and TOA radiance data,” Remote Sens. Environ. 109(2), 166–182 (2007).
[CrossRef]

Baret, F.

S. Jacquemoud, F. Baret, B. Andrieu, F. M. Danson, and K. Jaggard, “Extraction of Vegetation Biophysical Parameters by Inversion of the PROSPECT+SAIL Models on Sugar Beet Canopy Reflectance Data. Application to TM and AVIRIS Sensors,” Remote Sens. Environ. 52(3), 163–172 (1995).
[CrossRef]

S. Jacquemoud and F. Baret, “PROSPECT: a model of leaf optical properties spectra,” Remote Sens. Environ. 34(2), 75–91 (1990).
[CrossRef]

Berger, M.

K. Smorenburg, G. B. Courreges-Lacoste, M. Berger, A. Court, U. del Bello, G. Langsdorf, H. Lichtentha-ler, C. Sioris, M. P. Stoll, and H. Visser, “Remote sensing of solar-induced fluorescence of vegetation,” Proc. SPIE 4542, 178–190 (2002).
[CrossRef]

Buschmann, C.

C. Buschmann, “Variability and application of the chlorophyll fluorescence emission ratio red/far-red of leaves,” Photosynth. Res. 92(2), 261–271 (2007).
[CrossRef] [PubMed]

Colombo, R.

M. Meroni, M. Rossini, L. Guanter, L. Alonso, U. Rascher, R. Colombo, and J. Moreno, “Remote sensing of solar induced chlorophyll fluorescence: Review of methods and applications,” Remote Sens. Environ. 113(10), 2037–2051 (2009).
[CrossRef]

M. Meroni and R. Colombo, “Leaf level detection of solar induced chlorophyll fluorescence by means of a subnanometer resolution spectroradiometer,” Remote Sens. Environ. 103(4), 438–448 (2006).
[CrossRef]

Courreges-Lacoste, G. B.

K. Smorenburg, G. B. Courreges-Lacoste, M. Berger, A. Court, U. del Bello, G. Langsdorf, H. Lichtentha-ler, C. Sioris, M. P. Stoll, and H. Visser, “Remote sensing of solar-induced fluorescence of vegetation,” Proc. SPIE 4542, 178–190 (2002).
[CrossRef]

Court, A.

K. Smorenburg, G. B. Courreges-Lacoste, M. Berger, A. Court, U. del Bello, G. Langsdorf, H. Lichtentha-ler, C. Sioris, M. P. Stoll, and H. Visser, “Remote sensing of solar-induced fluorescence of vegetation,” Proc. SPIE 4542, 178–190 (2002).
[CrossRef]

Crisp, D.

R. Haring, R. Pollock, B. M. Sutin, and D. Crisp, “The Orbiting Carbon Observatory instrument optical design,” Proc. SPIE 5523, 51–62 (2004).
[CrossRef]

Danson, F. M.

S. Jacquemoud, F. Baret, B. Andrieu, F. M. Danson, and K. Jaggard, “Extraction of Vegetation Biophysical Parameters by Inversion of the PROSPECT+SAIL Models on Sugar Beet Canopy Reflectance Data. Application to TM and AVIRIS Sensors,” Remote Sens. Environ. 52(3), 163–172 (1995).
[CrossRef]

del Bello, U.

K. Smorenburg, G. B. Courreges-Lacoste, M. Berger, A. Court, U. del Bello, G. Langsdorf, H. Lichtentha-ler, C. Sioris, M. P. Stoll, and H. Visser, “Remote sensing of solar-induced fluorescence of vegetation,” Proc. SPIE 4542, 178–190 (2002).
[CrossRef]

Del Bianco, S.

Falorni, P.

Guanter, L.

M. Meroni, M. Rossini, L. Guanter, L. Alonso, U. Rascher, R. Colombo, and J. Moreno, “Remote sensing of solar induced chlorophyll fluorescence: Review of methods and applications,” Remote Sens. Environ. 113(10), 2037–2051 (2009).
[CrossRef]

Hamazaki, T.

Haring, R.

R. Haring, R. Pollock, B. M. Sutin, and D. Crisp, “The Orbiting Carbon Observatory instrument optical design,” Proc. SPIE 5523, 51–62 (2004).
[CrossRef]

Inoue, G.

H. Suto, A. Kuze, M. Nakajima, T. Hamazaki, T. Yokota, and G. Inoue, “Airborne SWIR FTS for GOSAT validation and calibration,” Proc. SPIE 7106, 71060M (2008).
[CrossRef]

Jacquemoud, S.

S. Jacquemoud, F. Baret, B. Andrieu, F. M. Danson, and K. Jaggard, “Extraction of Vegetation Biophysical Parameters by Inversion of the PROSPECT+SAIL Models on Sugar Beet Canopy Reflectance Data. Application to TM and AVIRIS Sensors,” Remote Sens. Environ. 52(3), 163–172 (1995).
[CrossRef]

S. Jacquemoud and F. Baret, “PROSPECT: a model of leaf optical properties spectra,” Remote Sens. Environ. 34(2), 75–91 (1990).
[CrossRef]

Jaggard, K.

S. Jacquemoud, F. Baret, B. Andrieu, F. M. Danson, and K. Jaggard, “Extraction of Vegetation Biophysical Parameters by Inversion of the PROSPECT+SAIL Models on Sugar Beet Canopy Reflectance Data. Application to TM and AVIRIS Sensors,” Remote Sens. Environ. 52(3), 163–172 (1995).
[CrossRef]

Kuze, A.

Langsdorf, G.

K. Smorenburg, G. B. Courreges-Lacoste, M. Berger, A. Court, U. del Bello, G. Langsdorf, H. Lichtentha-ler, C. Sioris, M. P. Stoll, and H. Visser, “Remote sensing of solar-induced fluorescence of vegetation,” Proc. SPIE 4542, 178–190 (2002).
[CrossRef]

Lichtentha-ler, H.

K. Smorenburg, G. B. Courreges-Lacoste, M. Berger, A. Court, U. del Bello, G. Langsdorf, H. Lichtentha-ler, C. Sioris, M. P. Stoll, and H. Visser, “Remote sensing of solar-induced fluorescence of vegetation,” Proc. SPIE 4542, 178–190 (2002).
[CrossRef]

Mazzoni, M.

Meroni, M.

M. Meroni, M. Rossini, L. Guanter, L. Alonso, U. Rascher, R. Colombo, and J. Moreno, “Remote sensing of solar induced chlorophyll fluorescence: Review of methods and applications,” Remote Sens. Environ. 113(10), 2037–2051 (2009).
[CrossRef]

M. Meroni and R. Colombo, “Leaf level detection of solar induced chlorophyll fluorescence by means of a subnanometer resolution spectroradiometer,” Remote Sens. Environ. 103(4), 438–448 (2006).
[CrossRef]

Mohanan, C. N.

N. Subash and C. N. Mohanan, “Curve-fit Analysis of Chlorophyll Fluorescence Spectra: Application to Nutrient Stress Detection in Sunflower,” Remote Sens. Environ. 60(3), 347–356 (1997).
[CrossRef]

Moreno, J.

M. Meroni, M. Rossini, L. Guanter, L. Alonso, U. Rascher, R. Colombo, and J. Moreno, “Remote sensing of solar induced chlorophyll fluorescence: Review of methods and applications,” Remote Sens. Environ. 113(10), 2037–2051 (2009).
[CrossRef]

Nakajima, M.

Pollock, R.

R. Haring, R. Pollock, B. M. Sutin, and D. Crisp, “The Orbiting Carbon Observatory instrument optical design,” Proc. SPIE 5523, 51–62 (2004).
[CrossRef]

Rascher, U.

M. Meroni, M. Rossini, L. Guanter, L. Alonso, U. Rascher, R. Colombo, and J. Moreno, “Remote sensing of solar induced chlorophyll fluorescence: Review of methods and applications,” Remote Sens. Environ. 113(10), 2037–2051 (2009).
[CrossRef]

Rossini, M.

M. Meroni, M. Rossini, L. Guanter, L. Alonso, U. Rascher, R. Colombo, and J. Moreno, “Remote sensing of solar induced chlorophyll fluorescence: Review of methods and applications,” Remote Sens. Environ. 113(10), 2037–2051 (2009).
[CrossRef]

Sioris, C.

K. Smorenburg, G. B. Courreges-Lacoste, M. Berger, A. Court, U. del Bello, G. Langsdorf, H. Lichtentha-ler, C. Sioris, M. P. Stoll, and H. Visser, “Remote sensing of solar-induced fluorescence of vegetation,” Proc. SPIE 4542, 178–190 (2002).
[CrossRef]

Smorenburg, K.

K. Smorenburg, G. B. Courreges-Lacoste, M. Berger, A. Court, U. del Bello, G. Langsdorf, H. Lichtentha-ler, C. Sioris, M. P. Stoll, and H. Visser, “Remote sensing of solar-induced fluorescence of vegetation,” Proc. SPIE 4542, 178–190 (2002).
[CrossRef]

Stoll, M. P.

K. Smorenburg, G. B. Courreges-Lacoste, M. Berger, A. Court, U. del Bello, G. Langsdorf, H. Lichtentha-ler, C. Sioris, M. P. Stoll, and H. Visser, “Remote sensing of solar-induced fluorescence of vegetation,” Proc. SPIE 4542, 178–190 (2002).
[CrossRef]

Subash, N.

N. Subash and C. N. Mohanan, “Curve-fit Analysis of Chlorophyll Fluorescence Spectra: Application to Nutrient Stress Detection in Sunflower,” Remote Sens. Environ. 60(3), 347–356 (1997).
[CrossRef]

Sutin, B. M.

R. Haring, R. Pollock, B. M. Sutin, and D. Crisp, “The Orbiting Carbon Observatory instrument optical design,” Proc. SPIE 5523, 51–62 (2004).
[CrossRef]

Suto, H.

Verhoef, W.

W. Verhoef and H. Bach, “Coupled soil-leaf canopy and amosphere radiative transfer modelling to simulate hyperspectral multi-angular surface reflectance and TOA radiance data,” Remote Sens. Environ. 109(2), 166–182 (2007).
[CrossRef]

Visser, H.

K. Smorenburg, G. B. Courreges-Lacoste, M. Berger, A. Court, U. del Bello, G. Langsdorf, H. Lichtentha-ler, C. Sioris, M. P. Stoll, and H. Visser, “Remote sensing of solar-induced fluorescence of vegetation,” Proc. SPIE 4542, 178–190 (2002).
[CrossRef]

Yokota, T.

H. Suto, A. Kuze, M. Nakajima, T. Hamazaki, T. Yokota, and G. Inoue, “Airborne SWIR FTS for GOSAT validation and calibration,” Proc. SPIE 7106, 71060M (2008).
[CrossRef]

Appl. Opt.

Opt. Express

Photosynth. Res.

C. Buschmann, “Variability and application of the chlorophyll fluorescence emission ratio red/far-red of leaves,” Photosynth. Res. 92(2), 261–271 (2007).
[CrossRef] [PubMed]

Proc. SPIE

H. Suto, A. Kuze, M. Nakajima, T. Hamazaki, T. Yokota, and G. Inoue, “Airborne SWIR FTS for GOSAT validation and calibration,” Proc. SPIE 7106, 71060M (2008).
[CrossRef]

R. Haring, R. Pollock, B. M. Sutin, and D. Crisp, “The Orbiting Carbon Observatory instrument optical design,” Proc. SPIE 5523, 51–62 (2004).
[CrossRef]

K. Smorenburg, G. B. Courreges-Lacoste, M. Berger, A. Court, U. del Bello, G. Langsdorf, H. Lichtentha-ler, C. Sioris, M. P. Stoll, and H. Visser, “Remote sensing of solar-induced fluorescence of vegetation,” Proc. SPIE 4542, 178–190 (2002).
[CrossRef]

Remote Sens. Environ.

M. Meroni and R. Colombo, “Leaf level detection of solar induced chlorophyll fluorescence by means of a subnanometer resolution spectroradiometer,” Remote Sens. Environ. 103(4), 438–448 (2006).
[CrossRef]

N. Subash and C. N. Mohanan, “Curve-fit Analysis of Chlorophyll Fluorescence Spectra: Application to Nutrient Stress Detection in Sunflower,” Remote Sens. Environ. 60(3), 347–356 (1997).
[CrossRef]

S. Jacquemoud, F. Baret, B. Andrieu, F. M. Danson, and K. Jaggard, “Extraction of Vegetation Biophysical Parameters by Inversion of the PROSPECT+SAIL Models on Sugar Beet Canopy Reflectance Data. Application to TM and AVIRIS Sensors,” Remote Sens. Environ. 52(3), 163–172 (1995).
[CrossRef]

S. Jacquemoud and F. Baret, “PROSPECT: a model of leaf optical properties spectra,” Remote Sens. Environ. 34(2), 75–91 (1990).
[CrossRef]

W. Verhoef and H. Bach, “Coupled soil-leaf canopy and amosphere radiative transfer modelling to simulate hyperspectral multi-angular surface reflectance and TOA radiance data,” Remote Sens. Environ. 109(2), 166–182 (2007).
[CrossRef]

M. Meroni, M. Rossini, L. Guanter, L. Alonso, U. Rascher, R. Colombo, and J. Moreno, “Remote sensing of solar induced chlorophyll fluorescence: Review of methods and applications,” Remote Sens. Environ. 113(10), 2037–2051 (2009).
[CrossRef]

Other

J. R. Miller, M. Berger, Y. Goulas, S. Jacquemoud, J. Louis, N. Moise, G. Mohammed, J. Moreno, I. Moya, R. Pedrós, W. Verhoef, and P. J. Zarco-Tejada, “Development of a Vegetation Fluorescence Canopy Model,” ESTEC Contract No. 16365/02/NL/FF, Final Report, (2005).

Cited By

OSA participates in CrossRef's Cited-By Linking service. Citing articles from OSA journals and other participating publishers are listed here.

Alert me when this article is cited.


Figures (7)

Fig. 1
Fig. 1

Simulated canopy fluorescence for different Cab values

Fig. 2
Fig. 2

Simulated canopy fluorescence (red line) with retrieved fluorescence in the A and B bands (heavy green line) shown also outside (as a dotted line). Fluorescence was retrieved in the (A-AB) case reported in Table 4 for a resolution equal to 0.38 cm−1. Sensor radiance at TOA (blue line) in the A and B bands is also shown for the same ILS.

Fig. 3
Fig. 3

The images in the first row refer to the fluorescence retrieved in the two A and B bands in both bare (left) and same (right) cases for n = 10−6 and a resolution of 2 cm−1. A complete series of simulated and retrieved fluorescences (second row), simulated reflectances and retrieved RS term (third row), and residuals (fourth row) for a different randomly-generated noise of same n, for bare (first column) and same (second column) cases. DS were normalized to SENSOR-RAD. In the bare case, the difference between RS and rso (RSO) in the B band is significant. The two simulated adjacency reflectance terms were equal. In the same case, RS was found closer to rdo (RDO) than to rso (RSO), in the A band.

Fig. 4
Fig. 4

Some of the fluorescences (left) and paired reflectance terms (right) results of a series of 8 runs obtained for bare case at a resolution of 2 cm−1 and noise coefficient n = 10−6. DS derived from a normalization to SENSOR-RAD. The peak position and intensity of each Voigt are indicated by an asterisk. The two simulated adjacency reflectance terms were equal. The first row are the results of the first run for which reflectance terms variability range was set between 0 and 0.4 while the amplitude variability range of the two Voigts was set from 0 and 2 times the amplitude of the simulated fluorescence SFA. The second row are the results of the fourth run for which, according to the results of the third run, reflectance RSDO variability range was set between 0 and 0.36, reflectance RSDD variability range between 0.265 and 0.340 while the amplitude variability range of the Voigt A was set from 0.93 and 2 times SFA and that of Voigt B between 0.57 and 2 times SFA, respectively. The third row are the results of the last run and were obtained for an increased number of knots. According to the results of the previous runs, reflectance RSDO variability range was left between 0 and 0.36, the reflectance RSDD variability range was set between 0.268 and 0.340 while the amplitude variability range of the Voigt A was set between 0.98 and 2 times SFA and that of Voigt B between 0.65 and 2 times SFA, respectively.

Fig. 5
Fig. 5

Single-run retrieval of fluorescence, reflectance terms, and residuals for bare case at a resolution of 0.38 cm−1, sampling 0.2 cm−1, and noise coefficient n = 10−6. The corresponding SNR is also reported. The peak position and intensity of each Voigt are indicated by an asterisk. DS derived from a normalization to SENSOR-RAD. The peak position and intensity of each Voigt is indicated by an asterisk. The two simulated adjacency reflectance terms were equal.

Fig. 6
Fig. 6

Last-run retrieval of fluorescence, reflectance terms and residuals for bare case at a resolution of 0.38 cm−1, sampling of 0.2 cm−1, and noise coefficient nl = 3.30 10−6. The corresponding SNR is also reported. DS derived from a normalization to SENSOR-RAD. The peak position and intensity of each Voigt are indicated by an asterisk. The two simulated adjacency reflectance terms were equal.

Fig. 7
Fig. 7

Simulated and retrieved fluorescence in the A band, residuals, and SNR corresponding to an n = 5.10 10−6 noise coefficient for bare case at a resolution of 0.38 cm−1, and a sampling of 0.2 cm−1. The peak position and intensity of each Voigt are indicated by an asterisk. The two simulated adjacency reflectance terms were equal. DS derived from a normalization to the square root of SENSOR_RAD.

Tables (4)

Tables Icon

Table 1 Fluorescence accuracy in the A and B bands for different noise coefficients

Tables Icon

Table 2 Limiting nl values and residuals in the A and B bands for the (AB) retrieval

Tables Icon

Table 3 Limiting nl values and residuals in the (A) retrieval

Tables Icon

Table 4 Residuals in A and B bands for the (A-AB) retrieval

Equations (8)

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

L o TOA = L 0 + F s τ o o + E s o cos θ s π [ ( τ s s r s o + τ s d + τ s s r s d ¯ ρ d d 1 r d d ¯ ρ d d     r d o ) τ o o + τ s s r s d ¯ + τ s d r d d ¯ 1 r d d ¯ ρ d d     τ d o ]
r s d ¯ = 0.45 r s d ( target) +  0 .55 r s d ( surr .)    r d d ¯ = 0.45 r d d ( target) +  0 .55 r d d ( surr .)
< L o TOA >     =     < L 0 > + < τ o o > F s                                                     + cos θ s π ( < E s o τ s s τ o o > r s o + < E s o τ s d τ o o > + < E s o τ s s τ o o ρ d d > r s d ¯ 1 r d d ¯ < ρ d d > r d o )                                                     + cos θ s π ( < E s o τ s s τ d o > r s d ¯ + < E s o τ s d τ d o > r d d ¯ 1 r d d ¯ < ρ d d > )
t 1 =     < L 0 > t 2 =     < τ o o > t 3 =     < ρ d d > t 4 =     < E s o τ s s τ o o > cos θ s / π t 5 =     < E s o τ s d τ o o > cos θ s / π t 6 =     < E s o τ s s τ o o ρ d d > cos θ s / π t 7 =     < E s o τ s s τ d o > cos θ s / π t 8 =     < E s o τ s d τ d o > cos θ s / π
L o TOA     = t 1 + t 2 F + t 4 r s o + t 5 + t 6 r s d ¯ ( 1 t 3 r d d ¯ ) r d o + t 7 r s d ¯ + t 8 r d d ¯ 1 t 3 r d d ¯
S E N S O R _ R A D = [ L o TOA ] I L S
S N R   =   S E N S O R _ R A D / r m s   ( S E N S O R _ R A D   S E N S O R _ R A D n )
DS  =  NSENSOR _ R ADn N S E N S O R _ R A D m

Metrics