# Presentation: 816665

## MERIS US Workshop14 July 2008

- MERIS Level 1b processing
- Ludovic Bourg

## Table Of Content

- Functional Breakdown
- Data extraction and saturation checks
- Radiometric model and calibration
- Stray-light correction
- Product grid and geo-location
- Spatial re-sampling
- Pixels classification
- Meteo Annotations
- Product summary

## Functional Breakdown

## Data Extraction & Saturation Checks 

- data is extracted from L0 according to products limits computations
- time continuity is checked, overlaps removed and gaps filled (if any)
- each sample is checked for saturation and flagged

## Radiometric Model

- L: incoming radiance
- X: raw counts
- b,k,m,f: band, pixel, camera, frame
- A: instrument gain
- C: dark signal
- Sm: smearing effect
- SL: stray-light (within spectrometer)
- g, gc: temperature dependency of gain and dark signal
- NonLin: non-linearity

## Radiometric Calibration

- Invert radiometric model using:
- Sm 		from dedicated virtual band
- NonLin	from on-ground characterisation
- C & A 	from on-board measurements
- g, gc	from on-ground characterisation
- Provides

## Non-linearity look-up tables

- It  has been characterized as V=f(E)
- Converted into dV=g(V) using calibration line drawn between null illumination and the calibration point (on-orbit data) and modeled
- Scaled to counts using actual gain and band settings

## Smearing effect

- CCD

- t0: reset

- [t1,t2]: in position for exposure

- t0t1: transfer to exposure: integrates blue part of spectrum

- t2t3 : transfer to storage: integrates red part

- (t3-t2 ) + (t1-t0) = 1.3 ms ; t2-t1 = 42.7 ms

- Actual channel:

- Virtual smear channel:

- t0: reset

- t0+1.3: storage

- t0t0+1.3: transfer to storage: integrates whole spectrum

- 

**Notes:**
Exposure lasts 33 times longer than transfer

## Smearing effect and correction

- _Acquisition timeline:_
- The virtual smear band integrates spectra acquired at ~t1
- Each actual channel of wavelength  integrates during transfer:
- From UV to  at ~t1 (start of exp.)
- From  to NIR at ~t2 (end of exp.)
- The (next) virtual smear band integrates spectra acquired at ~t2
- _Correction scheme:_
- Each actual channel is corrected by a weighted average of smear channel values at t1 and t2, weights being derived according to channel wavelength:

## Instrument gain includes:

- Solar Irradiance model

- Absolute characterization of reference diffuser reflectivity (on-ground)

- On-board diffuser measurements

- Instrument spectral model from on-ground + on-orbit spectral characterization

## Instrument gain includes:

- Solar Irradiance model

- Absolute characterization of reference diffuser reflectivity (on-ground)

- Instrument spectral model from on-ground + on-orbit spectral characterization

- On-board diffuser measurements

**Notes:**
20 % in-FOV

## Instrument gain includes:

- Solar Irradiance model

- Absolute characterization of reference diffuser reflectivity (on-ground)

- Instrument spectral model from on-ground + on-orbit spectral characterization

- On-board diffuser measurements

## Instrument gain includes:

- Solar Irradiance model

- Absolute characterization of reference diffuser reflectivity (on-ground)

- Instrument spectral model from on-ground + on-orbit spectral characterization

- On-board diffuser measurements

**Notes:**
20% in FOV too!

## Straylight Correction

- Source is scattering & reflection within spectrometer
- Small contribution  can be estimated from degraded signal

- Can be modelled as a point spread function  convolutive process
- Correction using modelled PSF and approximate de-convolution

## Product Grid and Geolocation 

**Product grid definition:** re-built “ideal instrument” swath
- Across-track: perfectly aligned cameras along **** to track, inter-camera overlaps removed, regular on-ground distance sampling (geodesic at WGS-84 ellipsoid surface)
- Along-track: instrument time sampling, gives quasi-regular distance
**Geo-location:**
- At **Tie Points**: every 16 pixels in RR, 64 in FR, in both directions (17 x 19 km)
- Geo-location (longitude, geodetic latitude) at ellipsoid surface (WGS-84)
- Altitude and its variability  (h, h from GTOPO-05/GTOPO-30)
- Illumination and observation geometry: SZA, SAA, VZA, VAA
- Approximate parallax correction provided over land

## Product limits: RR & FR segments 

- MER_RR__1⁄2P		 MER_FRS_1⁄2P

## Product limits: FR Scene

- MER_FR__1⁄2P

## Spatial Re-sampling

- Re-builds ideal swath from actual MERIS FOV: slightly misaligned plane + inter-camera dispersion (see figure)
- Keep instrument measurements: nearest neighbour
- To fill-in a given product pixel:

- Across-track: detector column selected comparing across-track pointing angles
- Along-track: frame offset determined from known de-pointing of selected column

## Pixels Classification

**Land/water** and **coastline** based on an atlas
**Bright** based on radiometry (geometry dependant threshold on reflectance at 443 nm)
**Glint risk** based on angular distance to Sun specular reflection direction
**Invalid** when no data available (out of swath, gap, all bands saturated)

## Meteo Annotations

- Are added to geolocation annotations:
- u & v wind components at 10 m
- mean sea level pressure
- Relative humidity at 1000 hPa
- Total column ozone
- 	Interpolated at TP location from ECMWF data (1x1 degree regular grid)

## Level 1b product summary

- 1121 pixel wide (1300 km) wide, up to 15000 pixels long (2241x2241 pixels or 560x670 km for FR scenes,4481 pixels wide, up to 12800 long for FR segment)

- Classification and quality flags provided at each pixel

- Detector index provided at each pixel

- Geolocation and meteo provided on a 16x16 sub-grid(64x64 sub-grid in FR)

## Accurate geo-referencing for MERIS

- Land community expressed concerns about geo-location accuracy

- A specific post-processing tool was developed to respond to this need: **AMORGOS**, that adds to MERIS FR per pixel geo-location accounting for Earth surface elevation
- Inclusion in operational processing is considered