7 Matchup Analysis

7.1 Parametrization for sensors bands

7.1.1 Ag(440)

Characteristic OLI MSI OLCI
Beta (95% CI)1 p-value Beta (95% CI)1 p-value Beta (95% CI)1 p-value
a 24 (20 to 29) <0.001 20 (17 to 24) <0.001 20 (17 to 24) <0.001
b 1.9 (1.8 to 2.1) <0.001 1.8 (1.6 to 2.0) <0.001 1.8 (1.6 to 1.9) <0.001

1 CI = Confidence Interval

Characteristic MODISA MERIS SeaWiFS
Beta (95% CI)1 p-value Beta (95% CI)1 p-value Beta (95% CI)1 p-value
a 18 (15 to 21) <0.001 20 (17 to 23) <0.001 18 (16 to 21) <0.001
b 1.7 (1.5 to 1.9) <0.001 1.7 (1.6 to 1.9) <0.001 1.7 (1.6 to 1.9) <0.001

1 CI = Confidence Interval

Sensor MedianAE MeanAE bias
OLI 0.22 0.353 0.0648
MSI 0.209 0.341 0.0562
OLCI 0.219 0.34 0.047
MODISA 0.239 0.346 0.0664
MERIS 0.229 0.34 0.0492
SeaWiFS 0.256 0.344 0.0475

7.2 SPM

7.2.1 SPM from Rrs

EGSL
Characteristic OLI MSI OLCI
Beta (95% CI)1 p-value Beta (95% CI)1 p-value Beta (95% CI)1 p-value
a 3.5 (1.9 to 6.1) <0.001 3.7 (2.1 to 6.7) <0.001 3.7 (2.0 to 6.5) <0.001
b 0.21 (0.12 to 0.29) <0.001 0.22 (0.13 to 0.31) <0.001 0.22 (0.13 to 0.30) <0.001

1 CI = Confidence Interval

JB
Characteristic OLI MSI OLCI
Beta (95% CI)1 p-value Beta (95% CI)1 p-value Beta (95% CI)1 p-value
a 12 (8.2 to 19) <0.001 13 (8.7 to 19) <0.001 13 (8.7 to 19) <0.001
b 0.51 (0.43 to 0.60) <0.001 0.52 (0.44 to 0.60) <0.001 0.52 (0.44 to 0.60) <0.001

1 CI = Confidence Interval

EGSL
Characteristic MODISA MERIS SeaWiFS
Beta (95% CI)1 p-value Beta (95% CI)1 p-value Beta (95% CI)1 p-value
a 3.7 (2.1 to 6.6) <0.001 3.7 (2.0 to 6.5) <0.001 3.9 (2.1 to 7.0) <0.001
b 0.22 (0.13 to 0.30) <0.001 0.21 (0.13 to 0.30) <0.001 0.22 (0.13 to 0.31) <0.001

1 CI = Confidence Interval

JB
Characteristic MODISA MERIS SeaWiFS
Beta (95% CI)1 p-value Beta (95% CI)1 p-value Beta (95% CI)1 p-value
a 13 (8.8 to 19) <0.001 13 (8.7 to 19) <0.001 13 (8.9 to 20) <0.001
b 0.52 (0.44 to 0.60) <0.001 0.52 (0.44 to 0.60) <0.001 0.52 (0.44 to 0.60) <0.001

1 CI = Confidence Interval

Region Sensor MedianAE MeanAE bias
EGSL OLI 1.83 3.47 0.541
EGSL MSI 1.8 3.4 0.494
EGSL OLCI 1.79 3.41 0.51
EGSL MODISA 1.8 3.4 0.499
EGSL MERIS 1.79 3.42 0.514
EGSL SeaWiFS 1.78 3.38 0.494
JB OLI 0.841 3.68 0.323
JB MSI 0.806 3.52 0.299
JB OLCI 0.825 3.47 0.297
JB MODISA 0.824 3.46 0.296
JB MERIS 0.825 3.48 0.298
JB SeaWiFS 0.816 3.45 0.292

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7.3 Matchups analysis

Matchup analysis is performed for OLI and MSI images of Sept-Îles bay. Coefficient derived specifically for sensors are used. Four Atmospheric correction algorithm are compared in order to find the most appropriate, based on errors metrics: 1. ACOLITE 2. SSP 3. iCOR 4. C2RCC

7.3.1 Matchup summary statistics

Global summary
Characteristic Overall, N = 1181 2015-06-09, N = 1 2015-10-24, N = 1 2016-08-23, N = 9 2017-05-22, N = 5 2017-06-06, N = 6 2017-06-07, N = 5 2017-06-23, N = 2 2017-09-14, N = 9 2018-08-06, N = 2 2018-08-13, N = 5 2018-08-18, N = 4 2019-06-01, N = 2 2019-06-04, N = 5 2019-07-07, N = 7 2019-07-09, N = 7 2019-07-14, N = 8 2019-07-17, N = 1 2019-07-24, N = 6 2019-07-27, N = 7 2019-07-29, N = 5 2019-08-08, N = 3 2019-08-18, N = 10 2019-08-21, N = 8
ID, Range 1 - 504 227 - 227 243 - 243 1 - 9 59 - 64 73 - 83 87 - 93 113 - 115 151 - 159 358 - 359 380 - 385 402 - 405 177 - 178 196 - 200 433 - 439 440 - 446 448 - 456 470 - 470 481 - 486 490 - 496 497 - 501 502 - 504 252 - 278 313 - 320

1 Range

Global summary
Characteristic ACOLITE, N = 44 C2RCC, N = 44 C2X, N = 44 iCOR, N = 44 SeaDAS, N = 44 SSP, N = 33
Sensor, n (%)
MSI 27 (61) 27 (61) 27 (61) 27 (61) 27 (61) 27 (82)
OLI 17 (39) 17 (39) 17 (39) 17 (39) 17 (39) 6 (18)
Date, n (%)
2016-08-23 13 (30) 13 (30) 13 (30) 13 (30) 13 (30) 13 (39)
2017-05-22 5 (11) 5 (11) 5 (11) 5 (11) 5 (11) 0 (0)
2017-06-06 3 (6.8) 3 (6.8) 3 (6.8) 3 (6.8) 3 (6.8) 3 (9.1)
2017-06-07 4 (9.1) 4 (9.1) 4 (9.1) 4 (9.1) 4 (9.1) 0 (0)
2017-09-14 8 (18) 8 (18) 8 (18) 8 (18) 8 (18) 8 (24)
2019-06-04 3 (6.8) 3 (6.8) 3 (6.8) 3 (6.8) 3 (6.8) 3 (9.1)
2019-07-07 3 (6.8) 3 (6.8) 3 (6.8) 3 (6.8) 3 (6.8) 3 (9.1)
2019-07-14 5 (11) 5 (11) 5 (11) 5 (11) 5 (11) 3 (9.1)
Project, n (%)
CHONe 36 (82) 36 (82) 36 (82) 36 (82) 36 (82) 27 (82)
CoastJB 8 (18) 8 (18) 8 (18) 8 (18) 8 (18) 6 (18)
atmcor Nobs MeanAE MedAE bias wins
ACOLITE 44 4.0 3.1 3.10 5.3
C2RCC 44 2.5 1.9 0.81 40.0
C2X 44 2.4 1.9 1.20 31.0
iCOR 44 4.1 2.9 2.90 11.0
SeaDAS 44 4.2 2.9 2.90 11.0
SSP 33 5.4 4.5 4.50 1.8
atmcor r2 slope
ACOLITE 0.082 1.30
SSP 0.130 2.70
SeaDAS 0.120 3.30
iCOR 0.230 2.10
C2RCC 0.370 0.41
C2X 0.510 0.43
atmcor Nobs MeanAE MedAE bias wins
ACOLITE 44 0.525 0.324 -0.0188 23.30
C2RCC 44 0.774 0.697 -0.1880 20.00
C2X 44 0.892 0.790 -0.3300 6.67
iCOR 44 0.564 0.392 0.1480 16.70
SeaDAS 44 0.540 0.355 0.0329 20.00
SSP 33 0.595 0.459 0.1780 13.30
atmcor r2