End-to-End Simulation of Sentinel-2 Data with Emphasis on Atmospheric Correction Methods

Transcription

1 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

2 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

3 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

4 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

5 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

6 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

7 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.

8 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)

9 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

10 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

11 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

12 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

13 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

14 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))

15 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

16 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.

17 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.