End-to-End Simulation of Sentinel-2 Data with Emphasis on Atmospheric Correction Methods Luis Guanter 1, Karl Segl 2, Hermann Kaufmann 2 (1) Institute for Space Sciences, Freie Universität Berlin, Germany (2) GFZ German Research Centre for Geosciences, Germany
Motivation Background activities: 1. Consolidate requirements for Sentinel-2/MSI. 2. Develop and test methods for atmospheric correction (AC) of S-2 data. 3. Explore synergy between Sentinel-2 and the EnMAP imaging spectroscopy mission (VNIR-SWIR, GSD~30m). We have adapted the end-to-end scene simulator of EnMAP to S-2. This talk: overview of methodology and some tests. Raw data (digital numbers) Calibrated Radiance Orthorectification Surface reflectance
Forward Simulation Level 0/1a Level 1b Level 1c Level 2a Digital Numbers, satellite projection TOA radiances, satellite projection TOA reflectance, geographical projection, ortho-rec. BOA reflectance, geographical projection, ortho-rec. Calibration Non-linearity Dark Signal Absolute Calibration Sentinel-2 End-to-End Simulation Applications: Sensitivity analysis Development of preprocessing algorithms Cal/Val Sensor Data (DN) Sentinel-2 Scene Simulator Radiometric Module Spectral Module Atmospheric Module Spatial Module Input Data(Reflectance) DEM, CWV Map L1 Processors Radiometric Correction Orthorectification L2A Processor Atmospheric Correction Output Data (Reflectance) Backward Simulation
Forward simulation: reflectance + atmospheric radiative transfer Input: 1) Reflectance: (1) hyperspectral reflectance data covering the VNIR-SWIR or (2) multi/hyperspectral VNIR reflectance data + spectral library. 2) Other: DEM, water vapour map, AOT550 (average). Reflectance propagated to TOA radiance (Lambertian) in high spectral resolution (and high spatial resolution for the spatial simulator). Synthetic DEM Synthetic WV
Forward simulation: instrument module Hyperspectral output convolved with the MSI spectral response functions MSIlike TOA radiance data, Level 1b Radiometric module: linearity, striping, noise, 12-bit quantisation - according to missions specifications DNs, Level 1a (Optional) Spatial module: - pixel-wise instrument MTF, real acquisition geometry, band-specific GSD (10m & bin.) complex, time consuming, requires input data with high spatial resolution only for particular tests
Forward simulation: atmospheric effects on TOA radiance data Water vapour column (CWV) Aerosol optical thickness (AOT) Red-edge Ref: CWV=2 gcm-2, AOT550=0.2
Radiometric calibration Level 1 processing: radiometric calibration & spatial resampling L1a B8 (10m) B8a (20m) B9 (20x60m) L1b B9 (60x60m) The stripes result from different gains, digital offsets and non-linearity characteristics of each pixel.
Atmospheric correction (Level 2a) Aerosol optical thickness retrieval Level 1c, starting point: top-of-atmosphere reflectance AOT retrieval from MERIS (SCAPE-M, Guanter et al, 2008): - Retrieval over 10km cells AOT550 mosaic as an output - Maximum AOT threshold calculated from darkest pixels in the image - Refinement through the inversion of AOT + vegetation/soil endmembers - Aerosol type fixed (rural). - VNIR so far: MODIS DDV/2.2 um approach can also be implemented. - Atmospheric radiative transfer simulations from a look-up table (MODTRAN4)
Atmospheric correction (Level 2a) Water vapour & surf. reflec. retrieval Differential absorption technique: pair reference + measurement channel Exploits the ratio of bands B9 to B8a (broad B8 affected by WV, not a reference) CWV retrieval per-pixel: CWV=a+b*log(T)+c*log 2 (T) T=L(B9)/L(B8a); a, b, c = f(air mass factor, B8 TOA refl.) At this point AOT550 mosaic, pixel-wise CWV & elevation surface reflectance retrieval (Lambertian surface assumed) B8 B8a B9 Guanter et al. RSE, 2008
Atmospheric correction End-to-end simulation (noise free) Test of consistency: end-to-end simulation run for an agricultual site (Demmin, Germany) - Tests for different AOT550 and CWV levels - Ideal case: only unknowns AOT, CWV and surface reflectance (many assumptions...) - Offset in CWV retrieval, but very low impact on reflectance retrieval. - Almost perfect AOT retrieval, possibly due to some very dark areas (and assumptions!). Water vapour Aerosol optical thickness Surface reflectance
Test: effect of atmospheric correction on S-2 vegetation indices Motivation: Sentinel-2 to deliver an enormous amount of data. Question: when working with vegetation indices, can we use TOA reflectance (L1c) data? Test: calculated vegetation indices from TOA and BOA reflectance data and analysed the differences NDVI =(r(b7)-r(b4))/(r(b7)+r(b4)) (Tucker, 1979) CI_red-edge =(r(b7)/r(b5) 1 (Gitelson et al, 2003, 2006) MTCI = r(b6)-r(b5))/(r(b5)-r(b4)) (Dash & Curran, 2004) B6 B7 B4 B5
Test: effect of atmospheric correction on S-2 vegetation indices NDVI= (r(b7)-r(b4))/(r(b7)+r(b4)) CI_red-edge= r(b7)/r(b5) 1
Test: effect of atmospheric correction on S-2 vegetation indices NDVI= (r(b7)-r(b4))/(r(b7)+r(b4)) CI_red-edge = r(b7)/r(b5) 1
Test: effect of atmospheric correction on S-2 vegetation indices NDVI= (r(b7)-r(b4))/(r(b7)+r(b4)) MTCI= (r(b6)-r(b5))/(r(b5)-r(b4))
Spatial simulations & image mosaicing Synergy EnMAP + S-2 South Namibia O-2 O-1 O+0 O+1 O+2 EnMAP L2 images R/G/B: 2.2/0.8/0.4 µm GSD: 30 m Bands: 242 Sentinel-2 L2A mosaic R/G/B: 2.2/0.8/0.5 µm GSD: 20 m Bands: 13
Summary An end-to-end simulation tool for Sentinel-2 has been implemented building on previous EnMAP models: Allows forward simulation of S-2 L1a/b/c images for a range of atmospheric, surface and instrumental configurations. The backward simulation is based on a fully automatic processing chain. Potential for the investigation of S-2/EnMAP synergy and Cal/Val activities. Sensitivity analysis indicates that climatology values could be used for water vapour if processing time is an issue (avoid pixel-wise water vapour retrieval). Test of vegetation indices: different robustness against atmospheric effects, MTCI highly affected. End-to-end simulator already used to produce S2-like + EnMAP data for a number of sites and users. Could also be run on the SPOT Take 5 data set if there is interest.
Thank you for your attention!! and in particular to F. Gascon, P. Martimort and C. Isola for detailed information on S-2/MSI & to the German Federal Ministry of Economic Affairs and Technology and the German Research Foundation (DFG) for funding.