Subsurface CDOM Vertical Distribution Inversion in Ocean Based on Multi-Source Remote Sensing Data

Beibei Xie; Wang Gao; Yingjie Wang; Kaijie Ma; Xiuzhi Kong

doi:10.3788/AOS241370

Acta Optica Sinica, Volume. 45, Issue 12, 1201001(2025)

Subsurface CDOM Vertical Distribution Inversion in Ocean Based on Multi-Source Remote Sensing Data

Beibei Xie^1,2、*, Wang Gao¹, Yingjie Wang¹, Kaijie Ma¹, and Xiuzhi Kong³

Author Affiliations

¹School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, Hebei , China

²Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province, Qinhuangdao 066004, Hebei , China

³Guoneng Zhishen Control Technology Co., Ltd., Beijing 102211, China

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Figures & Tables(18)

Fig. 1. Multi-source data processing flow

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Fig. 2. Inversion model structure for vertical distribution of CDOM in the ocean subsurface

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Fig. 3. Effect of BGC-Argo data before and after filtering. (a) Vertical distribution of CDOM mass concentration at subsurface before filtering; (b) vertical distribution of CDOM mass concentration at subsurface after filtering

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Fig. 4. Initial Rrs443 remote sensing data for the target area on the 1st of each month in 2020

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Fig. 5. Rrs443 remote sensing data on the 1st of each month in 2020 after target area reconstruction

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Fig. 6. Loss during training

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Fig. 7. Independent testing area

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Fig. 8. Vertical distribution of subsurface CDOM mass concentration in independent testing area A. (a) Actual measured result; (b) predicted result

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Fig. 9. Vertical distribution of subsurface CDOM mass concentration in independent testing area B. (a) Actual measured result; (b) predicted result

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Fig. 10. Residual scatter plots of true and predicted values. (a) Residual plot of the test set; (b) residual plot of independent testing area A; (c) residual plot of independent testing area B

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Fig. 11. CDOM-SST scatter plots of independent testing area. (a) CDOM-SST scatter plot in area A; (b) CDOM-SST scatter plot in region B

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Table 1. BGC-Argo buoy information statistics

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Table 1. BGC-Argo buoy information statistics

BGC-Argo buoy number	Data collection time	Select CDOM profile depth /m	Number of collected files
2902750	2018-09-11‒2019-05-31	0‒200	226
2902754	2018-08-30‒2023-11-23		339
2902755	2018-09-03‒2021-02-10		289
2902857	2022-07-05‒2023-03-10		235
2903329	2018-01-28‒2018-04-20		82
2903330	2018-01-28‒2018-04-20		82
2903393	2020-08-22‒2022-09-26		150
2903394	2019-05-26‒2022-04-07		218
2903395	2019-06-03‒2021-06-24		167
2903396	2019-08-26‒2020-05-27		62
2903672	2021-03-05‒2022-10-29		51
2902887	2023-06-06‒2023-11-30		42
Total	-	-	1943

Table 2. Remote sensing data information

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Table 2. Remote sensing data information

Remote sensing parameter	Data collection time	Temporal resolution	Spatial resolution	Number
B1 （Rrs412）	2018-01-01‒2023-12-31	1 d	0.04°	2190
B2 （Rrs443）				2190
B3 （Rrs490）				2190
B4 （Rrs510）				2190
B5 （Rrs560）				2190
B6 （Rrs665）				2190
SST			0.25°	2190
Total	-	-	-	15330

Table 3. Results of K-fold cross-validation

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Table 3. Results of K-fold cross-validation

Data collection time	MAPE /%
January 1, 2020	25.77
February 1, 2020	18.51
March 1, 2020	18.13
April 1, 2020	19.49
May 1, 2020	21.52
June 1, 2020	22.57
July 1, 2020	20.35
August 1, 2020	16.53
September 1, 2020	17.11
October 1, 2020	29.04
November 1, 2020	17.27
December 1, 2020	22.88

Table 4. Dataset partition information
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Table 4. Dataset partition information
Data type Number of samples
Total 1895
Training set 1400
Test set 350
Independent testing area A 72
Independent testing area B 73

Table 5. Model input and output parameters

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Table 5. Model input and output parameters

Number	Input variable	Input parameter	Number	Output variable	Output parameter
1	B1 (Rrs412)	Target area: 1°×1° grid with 25×25 data points	8	CDOM	CDOM profile at center point (0‒200 m, 20 levels)
2	B2 (Rrs443)
3	B3 (Rrs490)
4	B4 (Rrs510)
5	B5 (Rrs560)
6	B6 (Rrs665)
7	SST

Table 6. Parameters of sensitivity analysis model
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Table 6. Parameters of sensitivity analysis model
Model Input parameter
Model 1 SST, Rrs （B1‒B6）
Model 2 Rrs （B1‒B6）
Model 3 SST

Table 7. Model evaluation results
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Table 7. Model evaluation results
Test data RMSE /（μg/L） r R²
Test set 0.14 0.73 0.74
Independent testing area A 0.13 0.81 0.79
Independent testing area B 0.18 0.74 0.69

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Beibei Xie, Wang Gao, Yingjie Wang, Kaijie Ma, Xiuzhi Kong. Subsurface CDOM Vertical Distribution Inversion in Ocean Based on Multi-Source Remote Sensing Data[J]. Acta Optica Sinica, 2025, 45(12): 1201001

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