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A Data Harmonization Methodology
Based On Simultaneous Nadir OverpassesJorge Gil - Juan Fernando Rodrigo - Alberto García - Sergio Gil - Cristina Moclán - Alfredo Romo - Fabrizio Pirondini
17th Joint Agency Commercial Imagery Evaluation (JACIE) Workshop. NOAA Center For Weather And Climate Prediction, MD, USA. September 17th -19th , 2018
• Launched in July 2009, operational since March 2010
• Sun-Synchronous ascending orbit at 650 km
• Mass: 100 Kg; Nadir-pointing platform
• Dual-bank pushbroom CCD, 3 cameras per bank
• Spatial resolution of 22m GSD at 10 bits
• Red, Green and NIR bands similar to Landsat to assure
continuity with existing tools and harmonization with
historical data
• DEIMOS-1 wide swath (625 km) combined with data
download at each orbit assures a high revisit frequency
for any given point on Earth
• No on-board calibration devices. Relies on reference
sensors
The Deimos-1 Earth Observation Satellite
2
17th Joint Agency Commercial Imagery Evaluation (JACIE) Workshop. NOAA Center For Weather And Climate Prediction, MD, USA. September 17th -19th , 2018
• A Pseudo-Invariant Calibration Site (PICS) is a place on
the Earth’s surface that has a high spatial uniformity and
a significant radiometric stability in time.
• PICS are being used for on-orbit radiometric trending,
cross calibration and absolute calibration of optical
satellite sensors.
• PICS-Based methodologies:
• Require long series of data
• Have a high latency
• Need BRDF modellization
Radiometry: PICS-Based Methodologies I
3
CEOS calibration sites
17th Joint Agency Commercial Imagery Evaluation (JACIE) Workshop. NOAA Center For Weather And Climate Prediction, MD, USA. September 17th -19th , 2018
Radiometry: PICS-Based Methodologies II
4
Libya-4 PICS Landsat-7 Trend
Band 3 (red)
Collection-1
Red
• Long series of data: To build the trend minimizing the
uncertainty mainly created by the atmosphere
• High latency: Several cloud-free observations are
needed to create a noticeable change in the trend.
• BRDF modelling: To take into account the viewing
and illumination conditions (seasonal variations)
17th Joint Agency Commercial Imagery Evaluation (JACIE) Workshop. NOAA Center For Weather And Climate Prediction, MD, USA. September 17th -19th , 2018
Simultaneous Nadir Overpasses
5
When Landsat 8 was launched in 2013 Landsat 7
had been the radiometric reference for Deimos-1
during 5 years.
Due to the different RSRs in Landsat 8 we needed
to compare Deimos-1 with it immediately. There
was no time to create a trend.
Back in 2014 our terminology was “close
approach”. We acquired a Deimos-1 image over
Libya-4 4.5 minutes before Landsat 8.
It was a “simultaneous nadir overpass” over a
PICS.
The results were presented on JACIE 2014. Libya-4 2014-02-14 “close approach” acquisition.
Deimos-1 08:51:28 UTC – Landsat 8 08:56:00 UTC,
17th Joint Agency Commercial Imagery Evaluation (JACIE) Workshop. NOAA Center For Weather And Climate Prediction, MD, USA. September 17th -19th , 2018
Two acquisitions from different platforms in a short time period over an area which is seen by both sensors nadir-looking.
Simultaneous Nadir OverpassesOur Definition I
6
Whereas we want to compare measurements, we
have:
• Minimized uncertainties created by the
atmosphere
• Negligible need of a BRDF modelling
While we have left differences in:
• Relative spectral responses
• Spatial resolution
If we succeed we can focus on the sensor’s
properties since atmospheric and ground features
could be considered the same.
17th Joint Agency Commercial Imagery Evaluation (JACIE) Workshop. NOAA Center For Weather And Climate Prediction, MD, USA. September 17th -19th , 2018
How short is a short time period?
Simultaneous Nadir OverpassesOur Definition II
7
The limitation is empirical. Our limit is set to 10 minutes for acquisition planning. After analysis most valid SNOs are less
than 90 seconds.
NOAA National Calibration Center Simultaneous Nadir Overpass (SNO) Predictions are 80 seconds.
SNO over the Bhadi
area in India with a
time gap of ~46
minutes.
Changes caused by
the atmosphere are
observable.
Deimos-1 2018-05-15 04:49:11 Sentinel-2A 2018-05-15 05:35:53 Enhanced TOA reflectance change
17th Joint Agency Commercial Imagery Evaluation (JACIE) Workshop. NOAA Center For Weather And Climate Prediction, MD, USA. September 17th -19th , 2018
What is a SNO area?
Simultaneous Nadir OverpassesOur Definition III
8
A circular surface whose center is the ground track crossing. The radius ranges from 15km to 50km depending on the
resolutions being compared, solar elevation, relief, surface features and cloudiness.
Deimos-1 & Sentinel-2B SNO.
Australia. Gap 37s
Deimos-1 & Landsat 8 SNO. Gap 55s Deimos-1 & Sentinel-2A SNO. Gap 83s
17th Joint Agency Commercial Imagery Evaluation (JACIE) Workshop. NOAA Center For Weather And Climate Prediction, MD, USA. September 17th -19th , 2018
The reference sensors we compare
Deimos-1 with are:
• Landsat 7 (bands 2, 3 & 4)
• Landsat 8 (bands 3, 4 & 5)
• Sentinel-2A (bands 3, 4, 8 & 8A)
• Sentinel-2B (bands 3, 4, 8 & 8A)
Blue, green and NIR (narrow and wide)
All polar sun-synchronous with very similar
orbital periods.
Landsats and Sentinels are descending.
Deimos-1 is ascending => Plenty of SNO
opportunities.
Simultaneous Nadir OverpassesOpportunities
9
17th Joint Agency Commercial Imagery Evaluation (JACIE) Workshop. NOAA Center For Weather And Climate Prediction, MD, USA. September 17th -19th , 2018
Simultaneous Nadir OverpassesOpportunities
10
Maximum gap set to
10 minutes.
SNO gaps:
• Australia 7’ 25’’
• Africa 4’ 6’’
• Brazil 2’ 53’’
• Peru 2’ 8’’
An example of Landsat 8 and Deimos-1 automatic SNO prediction over landmasses on the Deimos’ PlanEO planning tool on
2018-07-27.
17th Joint Agency Commercial Imagery Evaluation (JACIE) Workshop. NOAA Center For Weather And Climate Prediction, MD, USA. September 17th -19th , 2018
A double SNO on the same
Deimos-1 orbit highlights the
number of available
opportunities for SNO
acquisitions with Landsat 8 and
Sentinel 2A/B of an ascending
satellite
Deimos-1 (ascending) SNOs
with Landsat-7 and Sentinel-2B
(descending) on Jun the 27th
2018.
Simultaneous Nadir OverpassesOpportunities
11
17th Joint Agency Commercial Imagery Evaluation (JACIE) Workshop. NOAA Center For Weather And Climate Prediction, MD, USA. September 17th -19th , 2018
The video shows a SNO
acquisition between Deimos-
1 and Landsat 7 in real time
to illustrate how short the
time gap can be and to
emphasize how ground,
atmospheric and illumination
differences between
samples can be neglected.
Simultaneous Nadir OverpassesAcquisition
12
17th Joint Agency Commercial Imagery Evaluation (JACIE) Workshop. NOAA Center For Weather And Climate Prediction, MD, USA. September 17th -19th , 2018
Simultaneous Nadir OverpassesMethodology
13
1. SNO identification and acquisition
17th Joint Agency Commercial Imagery Evaluation (JACIE) Workshop. NOAA Center For Weather And Climate Prediction, MD, USA. September 17th -19th , 2018
Simultaneous Nadir OverpassesMethodology
14
1. SNO identification and acquisition
2. Gather reference data
17th Joint Agency Commercial Imagery Evaluation (JACIE) Workshop. NOAA Center For Weather And Climate Prediction, MD, USA. September 17th -19th , 2018
Simultaneous Nadir OverpassesMethodology
15
1. SNO identification and acquisition
2. Gather reference data
3. Orthorectify Deimos-1 using reference
17th Joint Agency Commercial Imagery Evaluation (JACIE) Workshop. NOAA Center For Weather And Climate Prediction, MD, USA. September 17th -19th , 2018
Simultaneous Nadir OverpassesMethodology
16
1. SNO identification and acquisition
2. Gather reference data
3. Orthorectify Deimos-1 using reference
17th Joint Agency Commercial Imagery Evaluation (JACIE) Workshop. NOAA Center For Weather And Climate Prediction, MD, USA. September 17th -19th , 2018
Simultaneous Nadir OverpassesMethodology
17
1. SNO identification and acquisition
2. Gather reference data
3. Orthorectify Deimos-1 using reference
4. Locate an accurate nadir position and
extract data over the AoI
17th Joint Agency Commercial Imagery Evaluation (JACIE) Workshop. NOAA Center For Weather And Climate Prediction, MD, USA. September 17th -19th , 2018
Simultaneous Nadir OverpassesMethodology
18
1. SNO identification and acquisition
2. Gather reference data
3. Orthorectify Deimos-1 using reference
4. Locate an accurate nadir position and
extract data over the AoI
5. Find spatially homogeneous areas for
each band
• NIR
17th Joint Agency Commercial Imagery Evaluation (JACIE) Workshop. NOAA Center For Weather And Climate Prediction, MD, USA. September 17th -19th , 2018
Simultaneous Nadir OverpassesMethodology
19
1. SNO identification and acquisition
2. Gather reference data
3. Orthorectify Deimos-1 using reference
4. Locate an accurate nadir position and
extract data over the AoI
5. Find spatially homogeneous areas for
each band
• NIR
• Red
17th Joint Agency Commercial Imagery Evaluation (JACIE) Workshop. NOAA Center For Weather And Climate Prediction, MD, USA. September 17th -19th , 2018
Simultaneous Nadir OverpassesMethodology
20
1. SNO identification and acquisition
2. Gather reference data
3. Orthorectify Deimos-1 using reference
4. Locate an accurate nadir position and
extract data over the AoI
5. Find spatially homogeneous areas for
each band
• NIR
• Red
• Green
17th Joint Agency Commercial Imagery Evaluation (JACIE) Workshop. NOAA Center For Weather And Climate Prediction, MD, USA. September 17th -19th , 2018
Simultaneous Nadir OverpassesMethodology
21
1. SNO identification and acquisition
2. Gather reference data
3. Orthorectify Deimos-1 using reference
4. Locate an accurate nadir position and
extract data over the AoI
5. Find spatially homogeneous areas for
each band
• NIR
• Red
• Green
6. Calculate an accurate acquisition time at
the scene center for each satellite
17th Joint Agency Commercial Imagery Evaluation (JACIE) Workshop. NOAA Center For Weather And Climate Prediction, MD, USA. September 17th -19th , 2018
Simultaneous Nadir OverpassesMethodology
22
1. SNO identification and acquisition
2. Gather reference data
3. Orthorectify Deimos-1 using
reference
4. Locate an accurate nadir position
and extract data over the AoI
5. Find spatially homogeneous areas
for each band
• NIR
• Red
• Green
6. Calculate an accurate acquisition
time at the scene center for each
satellite
7. Extract statistics for each polygon in
both samples
17th Joint Agency Commercial Imagery Evaluation (JACIE) Workshop. NOAA Center For Weather And Climate Prediction, MD, USA. September 17th -19th , 2018
Data Harmonization Based on SNOsA note about homogeneous areas
23
• The purpose of the comparison based on
homogeneous areas is to reduce the influence of the
different resolutions and small geometric errors of
the samples being compared
• They are calculated using the highest resolution
sample under the assumption that it will be also
homogeneous in the lowest resolution sample
• They have a minimum size in pixels of the lowest
resolution image
17th Joint Agency Commercial Imagery Evaluation (JACIE) Workshop. NOAA Center For Weather And Climate Prediction, MD, USA. September 17th -19th , 2018
Data Harmonization Based on SNOsA note about robustness
24
• The variation of the radius between
15km and 50km don’t change the
results significatively if the scene is
clear and the sun elevation is above
30º
• If random areas are chosen instead
of the homogeneous we obtain
similar results, but with reduced
correlation. No outliers were
removed.
• There is not a noticeable
dependence on the ground type
(rainforest, desert, agricultural) when
random areas are used
• There is a noticeable sensitivity to off-
nadir viewing
Random areas (red) and
homogeneous areas (green) in
a Landsat-7 NIR image (band
4) over a SNO AoI.
17th Joint Agency Commercial Imagery Evaluation (JACIE) Workshop. NOAA Center For Weather And Climate Prediction, MD, USA. September 17th -19th , 2018
Data Harmonization Based on SNOsDifferent Sensors. Same Bands
25
• Three representative cases: Australia is semi-arid, Brazil is
rainforest and Congo contains a mixture of vegetation and
bare soil with burned areas
• There can be seen differences between samples, however
the correlation remains high.
Congo Brazil Australia
17th Joint Agency Commercial Imagery Evaluation (JACIE) Workshop. NOAA Center For Weather And Climate Prediction, MD, USA. September 17th -19th , 2018
Data Harmonization Based on SNOsProof of Concept With Different Bands
26
• Sentinel-2A and B MSIs have two different
NIR bands
• The wide band 8 is similar to Deimos-1 band
1
• The band 8A is significatively narrower
• Both bands are acquired simultaneously
• What would happen if we compared the
correlation between Deimos-1 band 1 with
Sentinel-2 band 8A for a SNO and Sentinel-2
band 8 with 8A using the described
methodology?
17th Joint Agency Commercial Imagery Evaluation (JACIE) Workshop. NOAA Center For Weather And Climate Prediction, MD, USA. September 17th -19th , 2018
Data Harmonization Based on SNOsProof of Concept With Different Bands
27
The ground types in Australia are
desert, mid-latitude forest and
farmland (winter) while in Brazil it
is rainforest.
For the sake of clarity Deimos-1
data is not represented in the
figure.
Slopes Correlation coefficients
SNO Sentinel-2 Deimos-1 Sentinel-2 Deimos-1
2018-06-14-Australia-S2A 0.96426 0.96529 0.98884 0.99168
2018-06-20-Australia-S2B 0.92577 0.91368 0.99703 0.99753
2018-06-25-Australia-S2B 0.91182 0.89418 0.99453 0.96860
2018-06-27-Brazil-S2B 0.81850 0.80149 0.98860 0.96980
Each SNO has a different ground type and atmosphere. As a
consequence the slopes of the linear regression are different
as well.
Nevertheless the slopes of the Sentinel-2 wide NIR and the
Deimos-1 (wide) NIR vs. Sentinel-2 narrow NIR are similar.
17th Joint Agency Commercial Imagery Evaluation (JACIE) Workshop. NOAA Center For Weather And Climate Prediction, MD, USA. September 17th -19th , 2018
Data Harmonization Based on SNOsResults with S2A & S2B
28
The figures show the results obtained
from 18 SNOs of Deimos-1 with Sentinel-
2 (9 for each one) over a diversity of
scenes.
Despite the diversity, the correlation
coefficients remain high, which make the
linear adjustments shown suitable for
general use with the proper caution.
Note that the lowest correlation appears
on the DE1 (wide) NIR vs. S2 narrow NIR.
17th Joint Agency Commercial Imagery Evaluation (JACIE) Workshop. NOAA Center For Weather And Climate Prediction, MD, USA. September 17th -19th , 2018
Data Harmonization Based on SNOsResults with Landsat 8
29
The figures show the results obtained
from 9 SNOs of Deimos-1 Landsat 8 over
a diversity of scenes.
As it happens with the Sentinel-2 case,
the correlation coefficients remain high,
which make the linear adjustments shown
suitable for general use if special care is
taken when using the NIR band
adjustment.
The Deimos-1 satellite is now routinely
being tasked to acquire under SNO
conditions with Landsat 7/8 and Sentinel-
2A/B.
17th Joint Agency Commercial Imagery Evaluation (JACIE) Workshop. NOAA Center For Weather And Climate Prediction, MD, USA. September 17th -19th , 2018
Data Harmonization Based on SNOsConclusions
30
• Being the orbits of Landsat 7, Landsat 8, Sentinel-2A and Sentinel-2B descending, the frequency of the
acquisition opportunities with the ascending Deimos-1 under SNO conditions is high
• When the relative spectral responses of two different sensors are similar, a SNO measurement is virtually the
same in terms of ground, atmospheric features and viewing, illumination geometries; allowing this way the cross-
calibration, harmonization and trend monitoring of the radiometry with reduced latency
• Dissimilar relative spectral responses yield results that are scene-dependent. Grouping a significative number of
different scenes allows us to harmonize the TOA reflectance of different sensors, with limitations
• The harmonization accuracy is limited by the fact that the ground and atmospheric spectral features of a specific
acquisition are neglected. This limitation could be mitigated if the ground type is identified to the maximum
possible granularity and the proper parameters applied, maybe using machine learning techniques
17th Joint Agency Commercial Imagery Evaluation (JACIE) Workshop. NOAA Center For Weather And Climate Prediction, MD, USA. September 17th -19th , 2018
Thank you.Fancy Animations
31
Clouds displacement and a smoke plume
moving in a SNO with Deimos-1 and
Landsat-7.
The time gap was 15s
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