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«Submitted by Susan Barbara Kay to the University of Exeter as a thesis for the degree of Doctor of Philosophy in Biological Sciences In December ...»

-- [ Page 1 ] --

Radiative transfer modelling for

sun glint correction in marine

satellite imagery

Submitted by Susan Barbara Kay to the University of Exeter

as a thesis for the degree of

Doctor of Philosophy in Biological Sciences

In December 2011.

This thesis is available for Library use on the understanding that it is copyright

material and that no quotation from the thesis may be published without proper

acknowledgement.

I certify that all material in this thesis which is not my own work has been identified and that no material has previously been submitted and approved for the award of a degree by this or any other University.

Signature:.............................................

1 2 Abstract Remote sensing is a powerful tool for studying the marine environment; how- ever, many images are contaminated by sun glint, the specular reflection of light from the water surface. Improved radiative transfer modelling could lead to better methods for estimating and correcting sunglint. This thesis explores the effect of using detailed numerical models of the sea surface when investigating the transfer of light through the atmosphere-ocean system.

New numerical realisations that model both the shape and slope of the sea surface have been created; these contrast with existing radiative transfer models, where the air-water interface has slope but not elevation. Surface realisations including features on a scale from 3 mm to 200 m were created by a Fourier synthesis method, using up to date spectra of the wind-blown sea surface. The surfaces had mean square slopes and elevation variances in line with those of observed seas, for wind speeds up to 15 m s−1. Ray-tracing using the new surfaces gave estimates of reflected radiance that were similar to those made using slope statistics methods, but significantly different in 41% of cases tested. The mean difference in the reflected radiance at these points was 19%, median 7%. Elevation-based surfaces give increased sideways scattering and reduced forward scattering of light incident on the sea surface.

The elevation-based models have been applied to estimate pixel-pixel variation in ocean colour imagery and to simulate scenes viewed by three types of sensor. The simulations correctly estimated the size and position of the glint zone. Simulations of two ocean colour images gave a lower peak reflectance than the original values, but higher reflectance at the edge of the glint zone. The use of the simulation to test glint correction methods has been demonstrated, as have global Monte Carlo techniques for investigating sensitivity and uncertainty in sun glint correction.

This work has shown that elevation-based sea surface models can be created and tested using readily-available computer hardware. The new model can be used to simulate glint in a variety of situations, giving a tool for testing glint correction methods. It could also be used for glint correction directly, by predicting the level of sun glint in a given set of conditions.

3 Acknowledgments

I would like to thank all my supervisors for their advice and support: John Hedley for an endless flow of good ideas and constructive criticism, and for his patience in explaining PlanarRad more than a few times; Sam Lavender for big questions that led in fruitful directions; Alex Nimmo-Smith for valuable input on the sea surface and access to useful resources at the University of Plymouth; Peter Mumby for giving me the essential link to the University of Exeter, even via Brisbane – distance is no object these days.

This work was supported by Great Western Research, studentship number 363, with ARGANS Ltd as the industry partner. I am grateful to both organisations for their financial support.

My thanks go to colleagues at ARGANS and Exeter, whose questions and information provoked many useful thoughts and ideas. And thanks also to family and friends who let me look at waves for as long as I wanted.

Image and data acknowledgements

MERIS data, Figs. 1.1(a), 2.4, 5.3, 6.4 provided by the European Space Agency.

IKONOS data, Figs. 1.1(b), 2.7 c 2003, European Space Imaging GmbH, all rights reserved.

CASI images, Figs. 1.1(c), 2.6 based on digital spatial data licensed from the Natural Environment Research Council c NERC 1998.

–  –  –

1.1 Illustration of sun glint in a variety of optical imagery......... 25 1.2 (a) Effective shape of the surface when using a slope-statistics method;

(b) Visualisation of an elevation-based surface created using the method described in Ch. 4............................. 27

–  –  –

3.1 Wind-generated waves on the ocean surface, showing their characteristic wavenumbers, wavelengths and frequencies............. 71

3.2 The Pierson-Moskowitz, JONSWAP and Elfouhaily spectra plotted against wavenumber, for wind speed 10 m s−1.............. 81

–  –  –

4.1 Ratio of mean square slopes in the upwind and crosswind directions for various observations and models................... 94

4.2 Omnidirectional (a) slope and (b) elevation variance spectrum of Elfouhaily et al. (1997), labelled to show the wavenumber range included in the current model........................ 96 (a) Visualization of a sea surface for a wind speed of 3 m s−1. (b, c) 4.3 Elevation against position for a 5 m and a 20 cm line on the surface.. 97





4.4 Wind speed dependence of mean square slope and elevation standard deviation obtained from the modelled surface, empirical models and integration of the sea surface spectrum................. 99

4.5 Diagram to illustrate the division of the sphere used in ray tracing.. 100

4.6 The mean reflectance over several runs plotted against the number of runs..................................... 102

4.7 Reflected radiance estimated using elevation-based surfaces plotted against that estimated using a slope statistics method......... 104

4.8 Reflected radiance predicted using the elevation-based surfaces and the Cox-Munk slope-statistics model for various wind speeds and solar zenith angles................................ 104

4.9 Reflected radiance distribution estimated by (a, b) the new model with elevation-based surfaces and (c,d) the slope-statistics model... 105

4.10 Polar plots of reflected radiance as a function of viewing azimuth for viewing zenith 20◦ and various solar zenith angles........... 106

5.1 Clear sky reflected radiance as output by the new model with elevationbased surfaces, showing variation between surfaces........... 110

5.2 Diagram showing how the surface can be divided into sections in cases where the pixel size is smaller than the surface realisation....... 112

5.3 Parts of two MERIS images, showing the lines chosen for simulation. 115 10

5.4 Level 1 radiance estimated by the model and reported for MERIS for the two image lines shown in Fig. 5.3.................. 119

5.5 Water leaving reflectance at five wavelengths estimated by the model and reported for MERIS for the two image lines shown in Fig. 5.3.. 120

5.6 Glint reflectance estimated by the model and sun glint reflectance calculated as in the MERIS sun glint algorithm for the two image lines shown in Fig. 5.3.......................... 121

5.7 The lower glint regions of Fig. 5.6 enlarged............... 122

5.8 Modelled glint reflectance at 443 nm for the standard, clear sky, model and for direct irradiance only...................... 123

5.9 Glint reflectance at 443 nm estimated by the model using the elevationbased sea surfaces and slope-statistics surfaces.............. 124

5.10 Glint reflectance at 443 nm estimated using the elevation-based sea surfaces and slope-statistics surfaces, with clear sky illumination and with direct irradiance only......................... 125

5.11 Glint reflectance for the two lines in Fig. 5.3, calculated by the MERIS method using various parameter values............. 126

5.12 Glint reflectance for CM surfaces, estimated by the ray-tracing model and using the MERIS method....................... 127

5.13 Atmosphere-dependent quantities estimated by the MERIS algorithm and by libRadtran plotted against wavelength for four pixels from each image................................. 129

5.14 Water-leaving reflectance calculated using five sets of IOPs, for wavelengths 412, 512 and 665 nm....................... 131

5.15 Glint reflectance and water-leaving reflectance at 443 nm estimated by the model using multiple surface scattering and single scattering.. 133

5.16 Glint and water-leaving reflectance at 443 nm estimated using the standard and high angular resolution models.............. 134

5.17 Glint reflectance at 443 nm for the two lines shown in Fig. 5.3, calculated every 10 pixels and every pixel................ 136 11

5.18 Glint and water-leaving reflectance at 443 nm, calculated using a single surface ray-traced 5 and 25 times, and the average, minimum and maximum for 10 surfaces ray-traced 5 times each......... 137

5.19 Water-leaving reflectance at 443 nm estimated by the model using the elevation-based sea surfaces and the slope-statistics method.... 138

5.20 Diagram to show the set-up used for the CASI simulation....... 140

5.21 Radiance along a line from a CASI image as in Fig. 2.6; (a) simulated radiance at the sensor for four wavelengths (b) measured radiance... 142 5.22 (a) Wavelength dependence of measured and simulated radiance for two pixels from the line in Fig. 5.21. (b) Simulated transmitted radiance just above the surface for these two pixels........... 142

5.23 Radiance just above the sea surface for the simulation in Fig. 5.21. (a) reflected and transmitted light (b) reflected light only (c) transmitted light only.................................. 143

5.24 Repeat of parts (ii) and (iii) of Fig. 2.6, for ease of comparison.... 145

5.25 Simulated upwelling radiance at 480 nm just above the water surface for an IKONOS-type image, plotted as a map over 50 × 29 pixels... 149

5.26 Simulated upwelling radiance at four wavelengths for one line from the image in Fig. 5.25........................... 149

5.27 Glint-corrected radiance at four wavelengths for the line in Fig. 5.26. 150

5.28 Scatterplots comparing the model estimate of water-leaving radiance to that obtained using three glint correction methods, for all pixels in Fig. 5.25................................. 150

5.29 The difference between the glint-corrected radiance and the simulated water-leaving radiance just above the surface, plotted as a map over 50 × 29 pixels................................ 151

6.1 Top of atmosphere glint reflectance for the OLCI instrument, calculated for values sampled uniformly across the full range of all input variables, plotted against each variable................. 158 12

6.2 Percentage change in OLCI top of atmosphere glint reflectance for a 5% change in each input variable, plotted against the TOA glint reflectance................................. 159

6.3 Absolute change in OLCI top of atmosphere glint reflectance for a 5% change in each input variable, plotted against the changing variable160

6.4 Extract from a MERIS image of the Pacific, showing the 6 pixels tested.161

6.5 Top of atmosphere glint reflectance for the 6 pixels shown in Fig. 6.4, calculated with each input varying randomly about its reported value. 163

6.6 2d histograms of (a) mean difference and (b) standard deviation from the original glint reflectance when the inputs are varied randomly about their original values, for the full range of OLCI input values.. 164

6.7 2d histograms of mean difference and standard deviation from original glint reflectance, as in Fig. 6.6, for different numbers of runs...... 166

6.8 Scatterplots showing the glint reflectance plotted against each input variable for a sample pixel from the MERIS Atlantic simulation.... 170

6.9 Scatterplots showing the water-leaving reflectance plotted against each input variable for a sample pixel from the MERIS Atlantic simulation................................... 171

6.10 As Fig. 6.8 for another pixel, showing the effect of the quad boundaries.................................... 172

6.11 Variation of reflectance at 443 nm along the image lines shown in Fig.

5.3, with all inputs varying randomly as described in the text..... 174

6.12 Variation of reflectance with wavelength for two medium-glint pixels from the Atlantic image in Fig. 5.3 and one from the Mediterranean image.................................... 175

7.1 Simulated downwelling radiance 5 m below the water surface for the IKONOS-type image simulated in section 5.6.............. 181

–  –  –

2.1 Contribution to the signal received at a satellite-borne sensor from various routes in non-glint conditions................... 33

2.2 Summary of published methods for sun glint correction........ 39

5.1 Values of water absorption coefficient a(λ) and scattering coefficient b(λ) used in the model presented in this section............. 117

–  –  –

tions contributing to this work This thesis includes material from two published papers and one in press.



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