Summary of the SGLI products
Validation results(Ver. 3.00)
Earth Observation Research Center
Japan Aerospace Exploration Agency
25 Nov. 2021

1History
23 Dec. 2017
01 Jan. 2018
28 Mar. 201820 Dec. 2018

GCOM-C (SHIKISAI) launched from Tanegashima Space Center
Release of the SGLI First-light images
Initial function verification completed
Public release of first version Level- 1 and Level- 2 SGLI products

Aug. 2019
Jun. 2020

GCOM-C Science team decided version-up products
Public release of second version Level- 1 and Level- 2 SGLI products

30 Aug. 2021

Online mini-workshop

07 Sep. 2021
29 Nov. 2021

SGLI user committee meeting
Public release of third version Level- 2 SGLI products

Late 2022

Final review for the full/extra success of GCOM-C mission

2Validation summary of the SGLI L1/L2 products
GCOM-C Success criteria (data production aspect only)
Success
Level

Minimum Success[L + 1 yr]

Full Success[L + 5 yr]

Extra Success[L + 5 yr]

StandardProducts

Complete the Cal. & Val. phaseand start data distribution ofmore than 20 products
achieving the release accuracy
thresholds

Achieve standard accuracy
thresholds of all standardproducts

Achieve target
accuracy thresholds of
one or more standard
products

Results of the version-upgrade validation[The number of products]

L1[1]

Land
[9]

Atmosphere
[8]

Ocean
[7]

Cryosphere
[4]

Total
[29]

Release accuracy

1

98

7

429

Standard accuracy

1

Target accuracy*

0

Level/Area

9 (+5) 8 (+3) 7 (+2) 4 (+2) 29 (+12)
02

1 (0)03 (0)*the number of products achieved standard and target accuracy threshold
The numbers in parentheses are the differences of achieved product number from Ver.1.
Confirmation of achievement of standards and target accuracy will take place five years after launch.

Twelve products achieved newly standard accuracy through version-upgrade validation.

3

Standard products version up summary

L1-

Product

Algorithm

Validation
JAXA

Level-1-

Product

Algorithm

Validation
JAXA

Precise geometric correction
Atmospheric correctedreflectance (incl. clouddetection)

JAXA

Land PIs

Land

fAPAR
Leaf area Index
Land surface temperature-ProductCloud flag/Classification

Brush up the estimation coefficient and validation
method and added solar altitude data

Land PI
Land PIs

Land PIs
Land PIJAXA, Land PI

Land PIs

Land PI
Algorithm
Atmosphere PIs

Update LUTs based on GEDI’s observed data
NAValidation
JAXA,Atmosphere PIs

Classified cloud fraction

Atmosphere

Revise of BRDF estimation and update QA
NA

Shadow Index

Vegetation roughness index

Ver.3 Major changes
NAVegetation Index

Above-ground biomass

Ver.3 Major changes
Correction for sensor sensitivity aging
Reduction of linear noise (VNR) and horizontal stripes (TIR)

Update of forest structure map using SGLI
Revise of cloud screening using CLFG

Ver.3 Major changes
Add the cloud and heavy aerosol screening
using machine learning method focused on
the snow region and night-time

Cloud top temp/height
Water cloud optical
thickness/effective radiusAtmosphere PIs

Atmosphere PIs

JAXA,
Atmosphere PIs

Atmosphere PIs

NA

Ice cloud optical thickness
Aerosol over the oceanLand aerosol by near ultra-violet
Aerosol by polarization

Integrated of aerosol retrieval algorithms using
polarization channels and non-polarization channels

4Standard products version up summary-Product
Normalized water leaving radiance(incl. cloud detection)
Atmospheric correction parametersOceanPhotosynthetically available radiation
Chlorophyll-a concentration

Algorithm

CryosphereVer.3 Major changes
Algorithm and QA improvements, including
modification of aerosol model and additionof underwater model.

Ocean PIs,JAXA
JAXA, Ocean PI
JAXA

Ocean Pis

NA

Suspended solid concentration

Ocean PI

NA

Colored dissolved organic matter

Ocean PINA

Sea surface temperature (incl. clouddetection)-Validation

ProductJAXA
Algorithm

Revised cloud detection
Validation

Snow and ice covered area (incl. clouddetection)

Ver.3 Major changes
Revised training data setOkhotsk sea-ice distribution
Snow and ice surface temperature
Snow grain size of shallow layer

Cryosphere PI

Cryosphere PI

Updated emissivity table
Revised training data set
Add the Snow Albedo as a researchproduct5

Evaluation Status(1/2)
Products

Ver.1/Ver.2 already achieved

Ver.3 Accuracy

Release AccuracyStandard Accuracy

Target Accuracy

Precise geometric correction

VNR:0.15-0.21,IRS:0.15-0.29<1pixel<0.5pixel<0.25pixel

Atmospheric correctedreflectance (incl. clouddetection)

0.022 (<=443nm)
0.035 (>443nm)

0.3 (<=443nm),
0.2 (>443nm)

0.1 (<=443nm),
0.05 (>443nm)

0.05 (<=443nm),
0.025 (>443nm)

Vegetation Index* NDVI Grass:8.4%, Forest:11.8%
Grass: 25%, Forest: 20%
EVI Grass:16.0%, Forest:14.7%

Land14.0%

Shadow Index
Above-ground biomass
Vegetation roughness index

30%

20%

10%

Grass：30%, Forest：50%

Grass：10%, Forest：20%

40%

20%

10%

Grass: 50%, Forest: 50%

Grass: 30%, Forest: 20%

Grass: 20%, Forest: 10%

Grass:18.2%, Forest:31.9% Grass： 50%, Forest： 100%

18.5%

Grass: 20%, Forest: 15% Grass: 10%, Forest: 10%fAPAR

Grass:26.1%, Forest:8.5%

Leaf area Index

Grass:28.5%, Forest:28.8% Grass: 50%, Forest: 50%

Grass: 30%, Forest: 30% Grass: 20%, Forest: 20%Atmosphere

Land surface temperature

1.996 K

3.0 K

2.5 K

Cloud flag/Classification

10.2％

10% (with whole-sky camera)

Incl. below cloud amount Incl. below cloud amountClassified cloud fraction

10.2％

20% (on solar irradiance)

15% (on solar irradiance) 10% (on solar irradiance)

Cloud top temp/height-1K

3K/2km1.5K/1km

Water cloud optical
thickness/effective radius

82%

10%/30% (CloutOT/raduis)

100% (as cloud liquidwater)

50%/20%Ice cloud optical thickness

56%

30%

70%

20%

Aerosol over the ocean

670nm:0.072
865nm:0.051

0.1 (monthly ta_670,865)

0.1 (Scene ta_670,865)

0.05 (Scene ta_670,865)

Land aerosol by near UV

0.137

0.15 (monthly ta_380)

0.15 (scene ta_380)

0.1 (scene ta_380)

Aerosol by polarization

0.137

0.15
(monthly ta_670,865)

0.15 (scene ta_670,865) 0.1 (scene ta_670,865)

V3 updated algorithms

1.5 K

Ver.3 newly achieved

In principle, the numerical values of accuracy targets are defined in terms of root mean square error (RMSE), which has the same units as physical quantities. Note that theaccuracy value described in the unit of ratio (%) is evaluated by the ratio between RMSE and the average value of field data. For the flag type product (cloud flag / type), theerror rate (%) of the flag is statistically evaluated using the in-situ.

6A

Evaluation Status(1/2)
Ver.1/Ver.2 already achieved
ProductsNormalized water leaving
radiance (incl. clouddetection)

Ver.3 Accuracy

Release Accuracy

23~45%(<600nm)
0.50W/m2/sr/um( 60% (443～565nm)>600nm)Standard Accuracy

Target Accuracy

50% (<600nm)

30% (<600nm)

0.5W/m2/str/um(>600nm)

0.25W/m2/str/um(>600nm)

Ocean

Atmospheric correction
parameters

46%

80% (ta_865nm)

50% (ta_865nm)

30% (ta_865nm)

Photosynthetically available
radiation

8.9%

20% (10km/month)

15% (10km/month)

10%(10km/month)

Cryosphere

Chlorophyll-a concentration-55〜+121%-60～+150% (offshore)-60〜+150%-35～+50% (offshore)-50～+100% (coast)

Suspended solid
concentration-59-+141%-60～+150% (offshore)-60〜+150%-50～+100%

Colored dissolved organic
matter-54〜+119%60% (443～565nm)-60〜+150%-50～+100%

Sea surface temperature (incl.
cloud detection)

Day:0.4 K,Night:0.4 K

0.8K (daytime)

0.8K (day/night)

0.6K (day/night)

Snow and Ice covered area (incl.
cloud detection)

6.5%

10% (vicarious val. with other sat. data)

7%

5%

Okhotsk sea-ice distribution

5.0%

10% (vicarious val. with other sat. data)

5%

3%

Snow and ice surface
Temperature

1.6 K

5K (vicarious val. with other sat. data andclimatology data)

2K

1K

Snow grain size of shallow layer

50%

100% (vicarious val. with climatology
between temp-size)

50%

30%

V3 updated algorithms

Ver.3 newly achieved

In principle, the numerical values of accuracy targets are defined in terms of root mean square error (RMSE), which has the same units as physical quantities. Note that theaccuracy value described in the unit of ratio (%) is evaluated by the ratio between RMSE and the average value of field data. For the flag type product (cloud flag / type), theerror rate (%) of the flag is statistically evaluated using the in-situ.

7A

Schedule for the GCOM-C mission

201620172018

FY2017H29

FY2016
H282019

FY2018
H30

2020

2021

FY2020H32

FY2019H312022

FY2021
H332023

FY2022
H34

10-11-12 1 - 2 - 3 4 - 5 - 6 7 - 8 - 9 10-11-12 1 - 2 - 3 4 - 5 - 6 7 - 8 - 9 10-11-12 1 - 2 - 3 4 - 5 - 6 7 - 8 - 9 10-11-12 1 - 2 - 3 4 - 5 - 6 7 - 8 - 9 10-11-12 1 - 2 - 3 4 - 5 - 6 7 - 8 - 9 10-11-12 1 - 2 - 3 4 - 5 - 6 7 - 8 - 9 10-11-12 1 - 2 - 3Pre-launch algorithm
development

GCOM-C launch

Sensor Operation
Cal.

InitialCheck-out

Sensor performance
Evaluation

Val.

Review for the Ver. 1
data release and minimum success

Review for the Ver. 2
data release

Ver.1

Ver.2

Initial Cal.

Ver.3

Post-normal

Operation

Vi- cal.
obs. data

Cal. for the Ver.2

Algo. Improvement for Ver.1

Cal for the Ver.3

Cal. coef.
Determination

Ver.2 processing

Ver.1 processing
Proc.test

Accuracy
Evaluation

Review for the Ver. 3
data release
Final review for the
full/extra success

Normal Operation

Cal. for the Ver.1

Ground System

Algorithm
Development &Improvement

Algorithm improvement and validation

Initial Cal./Val.

Review for thedevelopment Completion First Light

Postnormal
operation

Coef.
fixingVer.3 processing
Proc.test

Proc.test
Past data
re-processing

Algo. Improvement for Ver.2

Past data
re-processing

Past data
re-processing

Algo. Improvement for Ver.3

Coef.
TuringVal. for the Ver.1

Val. for the Ver.2

Val. for the Ver.3

Val. for the Final review

Ground truth dataIn-situ
Observation

Field campaigns for theVer.1 data release

Field campaigns for the Ver.2/Ver.3 data release

Field campaigns for theFinal Review

Ver.3 Release - 2021.11.29
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