end-to-end simulation of sentinel-2 data with emphasis on...

Luis Guanter1, Karl Segl2, Hermann Kaufmann2

(1) Institute for Space Sciences, Freie Universität Berlin, Germany

(2) GFZ German Research Centre for Geosciences, Germany

End-to-End Simulation of Sentinel-2 Data with

Emphasis on Atmospheric Correction Methods

SENTINEL-2 for Science Workshop, ESA-ESRIN, 20-22 May 2014

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 spectroscopymission (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

Motivation


Calibration

Non-linearity

Dark Signal

Absolute Calibration

Output Data

(Reflectance)

Input Data(Reflectance)

DEM, CWV Map

Sentinel-2 Scene

Simulator

Spectral Module

Spatial Module

Atmospheric

Module

Radiometric Module

Sensor Data (DN)

Bac

kw

ard

Sim

ula

tion

Fo

rwa

rd S

imu

lati

on

L1 Processors

Radiometric

Correction

Orthorectification

L2A Processor

Atmospheric

Correction

Sentinel-2 End-to-End Simulation

Applications:

• Sensitivity analysis• Development of pre-processing algorithms• Cal/Val

Level 0/1a Digital Numbers, satellite projection

Level 1b TOA radiances, satellite projection

Level 1c TOA reflectance, geographical

projection, ortho-rec.

Level 2a BOA reflectance, geographical

projection, ortho-rec.


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 MSI-

like 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

Red-edge

Ref: CWV=2 gcm-2, AOT550=0.2

Aerosol

optical

thickness

(AOT)

Water

vapour

column

(CWV)


L1a

L1b

B8 (10m) B8a (20m) B9 (20x60m)

Level 1 processing: radiometric calibration & spatial resampling

B9 (60x60m)

The stripes result from different gains, digital offsets and non-linearity characteristics of each pixel.

Rad

iom

etr

ic c

ali

bra

tio

n


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)


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:

At this point AOT550 mosaic, pixel-wise CWV & elevation surface reflectance

retrieval (Lambertian surface assumed)

CWV=a+b*log(T)+c*log2(T)

T=L(B9)/L(B8a); a, b, c = f(air mass factor, B8 TOA refl.)

Atmospheric correction (Level 2a) – Water vapour & surf. reflec. retrieval

Guanter et al. RSE, 2008

B9

B8aB8


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)

B5B4

B6

B7



NDVI=

(r(B7)-r(B4))/(r(B7)+r(B4))

CI_red-edge=

r(B7)/r(B5) – 1



NDVI=

(r(B7)-r(B4))/(r(B7)+r(B4))

CI_red-edge =

r(B7)/r(B5) – 1



MTCI=

(r(B6)-r(B5))/(r(B5)-r(B4))

NDVI=

(r(B7)-r(B4))/(r(B7)+r(B4))


Synergy EnMAP + S-2

South Namibia

EnMAP L2 imagesR/G/B: 2.2/0.8/0.4 µm

GSD: 30 m

Bands: 242

Sentinel-2 L2A mosaicR/G/B: 2.2/0.8/0.5 µm

GSD: 20 m

Bands: 13

O-2 O-1 O+0 O+1 O+2

Spatial simulations & image mosaicing


An end-to-end simulation tool for Sentinel-2 has beenimplemented building on previous EnMAP models:

• Allows forward simulation of S-2 L1a/b/c images for a range ofatmospheric, 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/Valactivities.

Sensitivity analysis indicates that climatology values could be usedfor water vapour if processing time is an issue (avoid pixel-wisewater vapour retrieval).

Test of vegetation indices: different robustness againstatmospheric 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 runon the SPOT Take 5 data set if there is interest.

Summary


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.

end-to-end simulation of sentinel-2 data with emphasis on...

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