The Bidirectional Reflectance Distribution Function (BRDF) describes angular reflection properties. If the illuminated area was opaque, such as dry land, the BRDF effect would only be driven by the optical characteristics of the reflecting surface. In the ocean, the BRDF also depends on the optical properties of the illuminated volume. The BRDF correction aims to minimise the dependence of the measured water reflectance on the solar and viewing geometry, improving the quality of ocean colour data products.
The development of BRDF correction methods has been a matter of various investigations, yet the ocean colour community recognises the need for improvements. The underlying difficulty is the lack of an exact radiative transfer solution that fully accounts for environmental conditions, and allows correcting BRDF effects in a remote sensing image on a pixel basis. Hence, the need to formulate an approximated BRDF correction as a trade-off between accuracy requirements and operational constraints.
This study has analysed reference BRDF correction schemes presented in the literature, and evaluated their performance with satellite and in situ data, considering both clear and optically complex waters. The main outcomes are:
Objectives
The study's objective is to analyse the performance of reference BRDF correction methods presented in the literature — including potential enhancements of such methods — and select the most appropriate for operational S3 OLCI data processing over clear and optically complex waters.
Overview
1. Study framework
The BRDF effect of interest in ocean colour remote sensing is changes in the water reflectance as a function of the sun zenith angle, the viewing zenith angle, and the relative azimuth angle between the sun and the observer. The scope of the BRDF correction is to minimise these variations of the water reflectance. Morel and Gentili (1996) gave the following definition of the fully (or exact) normalised water reflectance: the reflectance that a nadir-viewing instrument would measure if the sun were at the zenith, in the absence of any atmospheric loss and when the Earth is at its mean distance from the sun (Figure 1).
The BRDF correction schemes investigated in this study for the processing of OLCI data are those proposed by:
- Morel et al. (2002), termed M02
- Park and Ruddick (2005), termed P05
- Lee et al. (2011), termed L11
- He et al. (2017), termed H17
- Twardowski and Tonizzo (2018), termed T18—the original study denotes this scheme as ZTT for Zaneveld-Twardowski-Tonizzo (Zaneveld, 1995)
Results
All methods were implemented in the OLCI operational Instrument Processing Facility (IPF) as a sub-module, except the H17 method, due to limited spectral applicability.
The validation of the M02, P05 and L11 BRDF corrections was based on:
- Measurements acquired with Optical Floating System (OFS, Talone et al., 2018) in the Mediterranean and the Black Sea (Figure 2), as well as measurements performed with two TriOS RAMSES systems at the NIOZ Jetty Station (NJS) in the Dutch Wadden Sea.
- EUMETSAT Matchup Data Dase (MDB) with S3 OLCI and coincident field measurements at the AERONET-OC (Zibordi et al., 2021) and MOBY sites (Clark et al., 2002; Voss et al., 2018).
- Overlapping OLCI A and B images acquired during and outside the tandem phase (the former as a benchmark and the latter to account for different viewing geometries).
No BRDF | M02 | P05 | L11 | |
---|---|---|---|---|
Field measurements | Third option | Second option | Second option | Best option |
Match-up data | Best option | Third option | Second option | Second option |
OLCI-A and B images | Third option | Second option | Second option | Best option |
Assessment results are summarised in Table 1. The study recommendations are to:
- rely on L11 BRDF correction implementation in the IPF for the operational processing of OLCI data (Figure 3);
- enable access to OLCI data that are not BRDF corrected as a user’s post-processing option.
The assessments based on in situ OFS data are reported in Figure 2. An application example of the L11 BRDF correction to OLCI data is presented in Figure 3.
The study also implemented novel methods (Figure 4) to:
- Identify the BRDF correction validity based on the projection of input IOPs into a 2D vector space expressing the relative contribution of 1) molecules versus particle scattering and 2) single versus multiple scattering.
- Estimate the accuracy of the BRDF corrections based on a repeatability analysis.
Future developments
The following guidelines have been identified for future developments:
- Adopt the L11 main design.
- Use Fournier-Forand scattering phase functions (Fournier, 2007; Fournier and Forand, 1994) for both phytoplankton and non-algal scattering.
- Extend the IOPs variability in comparison to L11 (Lee et al., 2002, 2011), for instance, by referring to the Coastcolour data (Nechad et al., 2015).
- Revise the empirical steps of the QAA to retrieve the IOPs from the water reflectance and provide a performance assessment.
- Account for Raman scattering (but also verify the performance when Raman verify the performance when Raman is excluded).
- Complement BRDF correction results with the accuracy estimates.
Phase | Details |
---|---|
Kick-Off | 24/01/2022 |
Duration | 12 months |
Status | Ongoing |
Work Package 1 | Review and requirements consolidation |
Work Package 2 | BRDF-correction algorithm development |
Work Package 3 | Product generation |
Work Package 4 | Algorithm evaluation and validation |
Work Package 5 | Project outreach |
Study reports
Algorithm Theoretical Basis Document - Final version
Product Validation report - Final version
Technical documents
Concha J.A., Bracaglia M., and Brando V.E. (2021).Assessing the influence of different validation protocols on Ocean Colour match-up analyses. Remote Sensing of Environment, 259, 112415, DOI: 10.1016/j.rse.2021.112415.
Donlon C. (2011). Sentinel-3 Mission Requirements Traceability Document (MRTD). ESA.
Sentinel-3 OLCI Inherent Optical Properties Algorithm Theoretical Basis Document (ATBD) and gitlab toolbox.
Fan Y., Li W., Voss K.J., Gatebe C.K., and Stamnes K. (2016). Neural network method to correct bidirectional effects in water-leaving radiance. Applied Optics, 55, 1, 10, DOI: 10.1364/AO.55.000010.
Gleason A.C.R., Voss K.J., Gordon H.R., Twardowski M., Sullivan J., Trees C., Weidemann A., Berthon J.-F., Clark D., and Lee Z.-P. (2012). Detailed validation of the bidirectional effect in various Case I and Case II waters. Optics Express, 20, 7, 7630, DOI: 10.1364/OE.20.007630.
He, S., Zhang, X., Xiong, Y., Gray, D., 2017. A Bidirectional Subsurface Remote Sensing Reflectance Model Explicitly Accounting for Particle Backscattering Shapes. J. Geophys. Res. Oceans 122, 8614–8626. https://doi.org/10.1002/2017JC013313
Lee Z.P., Du K., Voss K.J., Zibordi G., Lubac B., Arnone R., and Weidemann A. (2011). An inherent-optical-property-centered approach to correct the angular effects in water-leaving radiance. Applied Optics, 50, 19, 3155, DOI: 10.1364/AO.50.003155.
McClain C.R. and Meister G. (2012). Mission Requirements for Future Ocean-Colour Sensors. International Ocean Colour Coordinating Group (IOCCG). N 13.,. DOI: 10.25607/OBP-104. https://ioccg.org/wp-content/uploads/2015/10/ioccg-report-13.pdf.
Mélin F. (2019). Uncertainties in Ocean Colour Remote Sensing. Ocean Colour Coordinating Group (IOCCG). N. 18. DOI: 10.25607/OBP-696. https://ioccg.org/wp-content/uploads/2020/01/ioccg-report-18-uncertainties-rr.pdf.
Mobley C.D., Werdell J., Franz B., Ziauddin Ahmad, and Bailey S. (2016). Atmospheric Correction for Satellite Ocean Color Radiometry. NASA/TM-2016-217551, DOI: 10.13140/RG.2.2.23016.78081.
Morel A. and Gentili B. (1991). Diffuse reflectance of oceanic waters: its dependence on Sun angle as influenced by the molecular scattering contribution. Applied Optics, 30, 30, 4427, DOI: 10.1364/AO.30.004427.
Morel A. and Gentili B. (1993). Diffuse reflectance of oceanic waters II Bidirectional aspects. Applied Optics, 32, 33, 6864, DOI: 10.1364/AO.32.006864.
Morel A. and Gentili B. (1996). Diffuse reflectance of oceanic waters III Implication of bidirectionality for the remote-sensing problem. Applied Optics, 35, 24, 4850, DOI: 10.1364/AO.35.004850.
Morel A., Antoine D., and Gentili B. (2002). Bidirectional reflectance of oceanic waters: accounting for Raman emission and varying particle scattering phase function. Applied Optics, 41, 30, 6289, DOI: 10.1364/AO.41.006289.
Park Y.-J. and Ruddick K. (2005). Model of remote-sensing reflectance including bidirectional effects for case 1 and case 2 waters. Applied Optics, 44, 7, 1236–1249, DOI: 10.1364/AO.44.001236.
Talone M., Zibordi G., and Lee Z. (2018). Correction for the non-nadir viewing geometry of AERONET-OC above water radiometry data: an estimate of uncertainties. Optics Express, 26, 10, A541, DOI: 10.1364/OE.26.00A541.
Twardowski M. and Tonizzo A. (2018). Ocean Color Analytical Model Explicitly Dependent on the Volume Scattering Function. Applied Sciences, 8, 12, 2684, DOI: 10.3390/app8122684.
Presentations
BRDF correction of S3 OLCI water reflectance products poster, 2-7 October 2022: Ocean Optics XXV, ICISE, Quy Nhon, Binh Dinh (Vietnam)
BRDF correction of S3 OLCI water reflectance products presentation, 2-7 October 2022: S3VT, ESA-ESRIN, Frascati (Rm), Italy
The Ocean Colour In-Situ Database (OCBD) is the reference dataset for the validation of the BRDF-correction scheme. This dataset includes matchups of OLCI L2 marine reflectance with concurrent in situ measurements. Relevant applications include OLCI calibration and validation activities.
Phase | Date and location |
---|---|
Kick-Off | 24/01/2022, Telecon |
Progress Meeting 1 | K0 + 2 months, Telecon |
Progress Meeting 2 | K0 + 4 months, Telecon |
Progress Meeting 3 | K0 + 6 months, EUMETSAT |
Progress Meeting 4 | K0 + 9 months, Telecon |
Progress Meeting 5 | K0 + 11 months, EUMETSAT |
Close -out meeting | K0 + 12 months, Telecon |
