Adjustment of Sentinel-2 Multi-Spectral Instrument (MSI) Red-Edge Band Reflectance to Nadir BRDF Adjusted Reflectance (NBAR) and Quantification of Red-Edge Band BRDF Effects

Optical wavelength satellite data have directional reflectance effects over non-Lambertian surfaces, described by the bidirectional reflectance distribution function (BRDF). The Sentinel-2 multi-spectral instrument (MSI) acquires data over a 20.6° field of view that have been shown to have non-negligible BRDF effects in the visible, near-infrared, and short wave infrared bands. MSI red-edge BRDF effects have not been investigated. In this study, they are quantified by an examination of 6.6 million (January 2016) and 10.7 million (April 2016) pairs of forward and back scatter reflectance observations extracted over approximately 20° × 10° of southern Africa. Non-negligible MSI red-edge BRDF effects up to 0.08 (reflectance units) across the 290 km wide MSI swath are documented. A recently published MODIS BRDF parameter c-factor approach to adjust MSI visible, near-infrared, and short wave infrared reflectance to nadir BRDF-adjusted reflectance (NBAR) is adapted for application to the MSI red-edge bands. The red-edge band BRDF parameters needed to implement the algorithm are provided. The parameters are derived by a linear wavelength interpolation of fixed global MODIS red and NIR BRDF model parameters. The efficacy of the interpolation is investigated using POLDER red, red-edge, and NIR BRDF model parameters, and is shown to be appropriate for the c-factor NBAR generation approach. After adjustment to NBAR, red-edge MSI BRDF effects were reduced for the January data (acquired close to the solar principal where BRDF effects are maximal) and the April data (acquired close to the orthogonal plane) for all the MSI red-edge bands.

[1]  Matthias Drusch,et al.  Sentinel-2: ESA's Optical High-Resolution Mission for GMES Operational Services , 2012 .

[2]  David P. Roy,et al.  Separability Analysis of Sentinel-2A Multi-Spectral Instrument (MSI) Data for Burned Area Discrimination , 2016, Remote. Sens..

[3]  D. Roy,et al.  Continental-scale Validation of MODIS-based and LEDAPS Landsat ETM+ Atmospheric Correction Methods , 2012 .

[4]  Alan H. Strahler,et al.  Geometric-optical bidirectional reflectance modeling of the discrete crown vegetation canopy: effect of crown shape and mutual shadowing , 1992, IEEE Trans. Geosci. Remote. Sens..

[5]  D. Jupp,et al.  A physics-based atmospheric and BRDF correction for Landsat data over mountainous terrain , 2012 .

[6]  N. C. Strugnell,et al.  First operational BRDF, albedo nadir reflectance products from MODIS , 2002 .

[7]  B. Hapke,et al.  The cause of the hot spot in vegetation canopies and soils: Shadow-hiding versus coherent backscatter , 1996 .

[8]  P. Oliva,et al.  Burned area mapping with MERIS post-fire image , 2011 .

[9]  José A. Sobrino,et al.  Analysis of directional effects on atmospheric correction , 2013 .

[10]  Lin Yan,et al.  Sentinel-2A multi-temporal misregistration characterization and an orbit-based sub-pixel registration methodology , 2018, Remote Sensing of Environment.

[11]  Bernard Pinty,et al.  Multi-angle Imaging SpectroRadiometer (MISR) instrument description and experiment overview , 1998, IEEE Trans. Geosci. Remote. Sens..

[12]  J. Dash,et al.  The MERIS terrestrial chlorophyll index , 2004 .

[13]  J. Roujean,et al.  A bidirectional reflectance model of the Earth's surface for the correction of remote sensing data , 1992 .

[14]  Hankui K. Zhang,et al.  A general method to normalize Landsat reflectance data to nadir BRDF adjusted reflectance , 2016 .

[15]  Bernhard Geiger,et al.  Use of a Kalman filter for the retrieval of surface BRDF coefficients with a time-evolving model based on the ECOCLIMAP land cover classification , 2008 .

[16]  Alan H. Strahler,et al.  An algorithm for the retrieval of albedo from space using semiempirical BRDF models , 2000, IEEE Trans. Geosci. Remote. Sens..

[17]  J. J. Colls,et al.  Use of hyperspectral derivative ratios in the red-edge region to identify plant stress responses to gas leaks , 2004 .

[18]  Alan H. Strahler,et al.  The interrelationship of atmospheric correction of reflectances and surface BRDF retrieval: a sensitivity study , 1999, IEEE Trans. Geosci. Remote. Sens..

[19]  S. Sandmeier,et al.  The potential of hyperspectral bidirectional reflectance distribution function data for grass canopy characterization , 1999 .

[20]  Stéphane Jacquemoud,et al.  PROSPECT-D: towards modeling leaf optical properties through a complete lifecycle , 2017 .

[21]  W. Lucht,et al.  Considerations in the parametric modeling of BRDF and albedo from multiangular satellite sensor observations , 2000 .

[22]  Luis Alonso,et al.  Evaluation of Sentinel-2 Red-Edge Bands for Empirical Estimation of Green LAI and Chlorophyll Content , 2011, Sensors.

[23]  J. J. Settle,et al.  On the dimensionality of multi-view hyperspectral measurements of vegetation , 2004 .

[24]  David P. Roy,et al.  The Global Impact of Clouds on the Production of MODIS Bidirectional Reflectance Model-Based Composites for Terrestrial Monitoring , 2006, IEEE Geoscience and Remote Sensing Letters.

[25]  Jan G. P. W. Clevers,et al.  Using Sentinel-2 Data for Retrieving LAI and Leaf and Canopy Chlorophyll Content of a Potato Crop , 2017, Remote. Sens..

[26]  Thomas S. Pagano,et al.  Prelaunch characteristics of the Moderate Resolution Imaging Spectroradiometer (MODIS) on EOS-AM1 , 1998, IEEE Trans. Geosci. Remote. Sens..

[27]  Xiaowen Li,et al.  An Anisotropic Flat Index (AFX) to derive BRDF archetypes from MODIS , 2014 .

[28]  Deric J Gray,et al.  Wavelength dependence of the bidirectional reflectance distribution function (BRDF) of beach sands. , 2015, Applied optics.

[29]  Hankui K. Zhang,et al.  Examination of Sentinel-2A Multi-spectral Instrument (MSI) Reflectance Anisotropy and the Suitability of a General Method to Normalize MSI Reflectance to Nadir BRDF Adjusted Reflectance , 2017 .

[30]  Ruiliang Pu,et al.  Extraction of red edge optical parameters from Hyperion data for estimation of forest leaf area index , 2003, IEEE Trans. Geosci. Remote. Sens..

[31]  M. S. Moran,et al.  Bidirectional measurements of surface reflectance for view angle corrections of oblique imagery , 1990 .

[32]  A. Strahler,et al.  BRDF laboratory measurements , 2000 .

[33]  Andrew K. Skidmore,et al.  Potential of Sentinel-2 spectral configuration to assess rangeland quality , 2015 .

[34]  Fabienne Maignan,et al.  A BRDF–BPDF database for the analysis of Earth target reflectances , 2016 .

[35]  David P. Roy,et al.  A Global Analysis of Sentinel-2A, Sentinel-2B and Landsat-8 Data Revisit Intervals and Implications for Terrestrial Monitoring , 2017, Remote. Sens..

[36]  Serhiy Skakun,et al.  Automatic sub-pixel co-registration of Landsat-8 Operational Land Imager and Sentinel-2A Multi-Spectral Instrument images using phase correlation and machine learning based mapping , 2017, Int. J. Digit. Earth.

[37]  Alan H. Strahler,et al.  Using a multikernel least-variance approach to retrieve and evaluate albedo from limited bidirectional measurements , 2001 .

[38]  H. Rahman,et al.  Coupled surface‐atmosphere reflectance (CSAR) model: 1. Model description and inversion on synthetic data , 1993 .

[39]  Jan G. P. W. Clevers,et al.  Remote estimation of crop and grass chlorophyll and nitrogen content using red-edge bands on Sentinel-2 and -3 , 2013, Int. J. Appl. Earth Obs. Geoinformation.

[40]  Nadine Gobron,et al.  Uniqueness of multiangular measurements. I. An indicator of subpixel surface heterogeneity from MISR , 2002, IEEE Trans. Geosci. Remote. Sens..

[41]  Yujie Wang,et al.  Multiangle implementation of atmospheric correction (MAIAC): 1. Radiative transfer basis and look-up tables , 2011 .

[42]  Alan H. Strahler,et al.  Bidirectional NDVI and atmospherically resistant BRDF inversion for vegetation canopy , 2002, IEEE Trans. Geosci. Remote. Sens..

[43]  Annick Bricaud,et al.  The POLDER mission: instrument characteristics and scientific objectives , 1994, IEEE Trans. Geosci. Remote. Sens..

[44]  J. Roujean,et al.  Retrieval of atmospheric properties and surface bidirectional reflectances over land from POLDER/ADEOS , 1997 .

[45]  D. Kimes Dynamics of directional reflectance factor distributions for vegetation canopies. , 1983, Applied optics.

[46]  T. F. Eck,et al.  Bidirectional reflectances of selected desert surfaces and their three-parameter soil characterization , 1990 .

[47]  R. Houborg,et al.  Impacts of dust aerosol and adjacency effects on the accuracy of Landsat 8 and RapidEye surface reflectances , 2017 .

[48]  Zhan Li,et al.  Evaluation of the global MODIS 30 arc-second spatially and temporally complete snow-free land surface albedo and reflectance anisotropy dataset , 2017, Int. J. Appl. Earth Obs. Geoinformation.

[49]  I. Herrmann,et al.  LAI assessment of wheat and potato crops by VENμS and Sentinel-2 bands , 2011 .

[50]  M. Cho,et al.  A new technique for extracting the red edge position from hyperspectral data: The linear extrapolation method , 2006 .