Geolocation and co-registration of the EarthCARE
CPR and ATLID instruments
Bernat Puigdomènech Treserras and Pavlos Kollias
McGill UniversityIntroduction
Instrument geolocation plays a critical role in achieving the objectives of the EarthCARE mission
Introduction
The Attitude Determination System (ADS) is designed to deliver
precise satellite geolocation and pointing information. However, errors orfactors like thermoelastic distortions can lead to miscalibration errors.

Actual measurements can help validate and assess the geolocation ofeach instrument. Co-registration is especially important, as themeasurements are combined in the synergistic algorithms.
A detailed analysis will be conducted on data collected over NaturalTargets, such as coastlines and areas with significant elevation
gradients, to asses and validate the geolocation of each instrument.

Objectives
The absolute geolocation error for the EarthCARE L1b products shouldbe less than 500m and 350m (goal 200m) for the co-registration* source: esa.int

Data Acquisition
Establish a reliable representation of the Earth's surface / test with actual measurements
Digital Elevation ModelCoastlinesMeasurements

ASTER
Advanced Spaceborne Thermal
Emission and Reflection Radiometer(NASA’s Terra satellite)

GSHHG
A Global Self-consistent, Hierarchical,
High-resolution Geography Database

CloudSat
2B-GEOPROF(2006-2019)
Good quality profiles / no clouds

ASTER and Copernicus
Water Body Masks (ocean, rivers and lakes)

CALIPSO
LID_L2_333mMLay-Standard-V4-51(2006-2019)
Good quality profiles / surface detection

Copernicus
EU Space Programme (TanDEM-Xsatellite)

1-arc seconds resolution (~30m)

ToolsFootprint Characterization
Real-time extraction of geospatial information along a specified orbit
path; coastline identification and convoluted DEM

Orbit Mapper
Real-time tracking of EarthCARE’s sun-synchronous orbit
location and phase (utilizing TLE information)

Sunlit = ascending / eclipse = descendingToolsFootprint Characterization
Real-time extraction of geospatial
information along a specified orbit
path; coastline identification andconvoluted DEM

Orbit Mapper
Real-time tracking of EarthCARE’s
sun-synchronous orbit location andphase (utilizing TLE information)

The signal captured by theinstrument over the coastline
is not always useful, it isoften excessively noisyTools
Footprint Characterization
Real-time extraction of geospatial
information along a specified orbit
path; coastline identification andconvoluted DEM

Orbit Mapper
Real-time tracking of EarthCARE’s
sun-synchronous orbit location andphase (utilizing TLE information)

The signal captured by theinstrument over the coastline
is not always useful, it isoften excessively noisy

ToolsFootprint Characterization
Real-time extraction of geospatial
information along a specified orbit
path; coastline identification andconvoluted DEM

Orbit Mapper
Real-time tracking of EarthCARE’s
sun-synchronous orbit location andphase (utilizing TLE information)

AThe
clear
signalocean/land
capturedgradientby theinstrument
must be available
over theincoastline
order toeffectively
is not always
use theuseful,signalit isfortheoftengeolocation
excessively
studiesnoisy

Identification of areas of interest
Clear coastlines

Land

Identify coastal scenes with high gradients (i.e. flat deserts adjacent to ocean), using the CloudSat measured surface backscatter (σ0)

The sigma-zero distributions for land and ocean are characterized by theirµ and σ. Optimal coastal scenes are identified by analyzing the distribution
intersection, searching for regions with minimal overlap

Distribution overlapping area

South Australia

Ocean

Normalized value [0-1]

Ocean

Land

The coastline signature is modelled using a cubic
fit. The inflection point is considered to be theactual location of the coastline

CALIPSO

CloudSat

2007/12 - 2019/12
3º off-nadir along-track

2006/09 - 2019/12
0.16º off-nadir along-track

Eclipse35070 detections
Geolocation offset: 41m

Eclipse19328 detections
Geolocation offset: 197m

Surface Integrated
Depolarization Ratio [] (x10)Surface Integrated
Depolarization Ratio []Coastline geolocation

Coastline geolocation
Downhill simplex minimization approach
Fit an ensemble of detections to a digitalized map considered the truth. The cost function minimizes the distance between the collectionof detections and the mapCoastline geolocation
Downhill simplex minimization approach
Fit an ensemble of detections to a digitalized map considered the truth. The cost function minimizes the distance between the collectionof detections and the mapCoastline geolocation
Downhill simplex minimization approach
Fit an ensemble of detections to a digitalized map considered the truth. The cost function minimizes the distance between the collectionof detections and the mapCoastline geolocation
Downhill simplex minimization approach
Fit an ensemble of detections to a digitalized map considered the truth. The cost function minimizes the distance between the collectionof detections and the mapCoastline geolocation
Downhill simplex minimization approach
Fit an ensemble of detections to a digitalized map considered the truth. The cost function minimizes the distance between the collectionof detections and the map

Identification of areas of interest
Significant elevation gradients
Areas with significant elevation gradients, such as mountains and valleys, identified by convoluting the global DEM with the EarthCARE CPR
footprint and selecting the regions that exhibit a higher number of σ points surpassing the threshold of 100m

GreeceAlaskaCanadaAlps

Baja
California
Peru
Chile
Chile

Compare the instrument’s surface detection heightto the reference DEM

Himalayas

Yemen
Oman
Saudi Arabia
Sudan

Namibia
AngolaSouth Africa

SouthAustralia
New Zealand

Clear coastlines
Areas with with significant elevation gradients

Significant elevation gradients geolocation
Significant elevation gradientsComparing the CPR and ATLID surface detection
height to the reference DEM convoluted with theinstrument’s footprint

CloudSatOver the Himalayas

Mount Everest

Artificial pointing errors are deliberately introduced inthe along- and cross-track directions and the final
geolocation error is found by minimizing the RMS error

Eclipse (S-W)
86 orbits
Cross-track offset: -0.003o ~ -41m
Along-track offset: -0.008o ~ -102m

Antenna Pointing Characterization
Exploiting the CPR Doppler capability
EarthCARE CPR Doppler velocity
with antenna mispointing

EarthCARE CPR Doppler velocity
after mispointing correction

Co-registration
The individual geolocation analyses for each instrument will be combined to assess potential
mis-registration. The analysis will be extended to the passive instruments
CPR
ATLID

1) Combine the individual geolocation statistics of each instrument
MSI2) Minimize the distance between detections from each instruments
3) Compare the surface height detection of the active instruments
EarthCARE CPR and ATLID surface height detection

Co-registration
DEM
ATLID
CPR