The geolocation problem encompasses all processing that is directly related to the location on Earth of the MERIS measurement data.
The points where the MERIS radiance samples have been measured are determined by the projection on Earth of the line of sight of every pixel. That projection depends on
· the shape of the Earth
· the altitude of the sample
· the position of the ENVISAT satellite at the time of acquisition
· the orientation of the MERIS modules
· the optics of each MERIS module
In order to simplify product handling, the MERIS radiance samples are relocated by nearest neighbour interpolation to the MERIS product grid, which has the following characteristics (FR grid):
· central column: subsatellite point track on Earth
· line orientation: perpendicular to spacecraft velocity, projected on Earth
· columns spacing: fixed for one product, 260 m (with very small variations)
· number of columns: 4,481
· line spacing: variable with time and orbit altitude, fixed by the MERIS frame time of 0.044s (mean » 292 m)
The RR-grid is a 4 x 4 subsampled version of that grid.
The surface of altitude 0 on Earth is approximated by a geoid model. The model WGS-84 used by the ENVISAT orbit propagator shall be used.
Knowledge of the ENVISAT platform and attitude relies on:
· prediction or estimation of the satellite position and attitude; the ESA CFI software is used:
- po_ppforb or po_interpol for orbit propagation
- pp_target for attitude modelling
· accurate datation of the MERIS samples, to the MJD2000 time reference used by the orbit and attitude prediction/estimation.
The interpolation algorithm for resampling MERIS data to the grid may use characterisation data defining the MERIS pixels de-pointing. Neglecting the surface elevation causes an error in pixel location, proportional to altitude and to the tangent of the observer zenith angle. That error is estimated at the tie points.
Sun zenith and azimuth angle, observer zenith and azimuth angle, may be computed for any pixel knowing pixel location and Sun direction in a common frame but are stored only at the product tie points.
Sun glint, because of the high radiance values measured there, has an impact on both the direct usage of L1b data and on L2 processing. A first estimate of the affected pixels is performed. The location of the potential Sun glint can be predicted for each pixel, from the illumination and observation geometry.
Geolocation processing is broken down into 5 main algorithm steps:
· product limits
· tie points Earth location
· altitude retrieval
· Sun glint