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Construction of a Suspended Sediment Concentration Inversion Model in The Yellow River Estuary Surrounding Waters Based on GOCI-I Images
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Lu MAO1, Na JIANG2, Juan WANG3, Shanwei LIU1, Jianyong CUI1, Mingming XU1
Journal of Telemetry, Tracking and Command | 2024, 45(6) : 121 - 130
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Journal of Telemetry, Tracking and Command | 2024, 45(6): 121-130
Radar and Countermeasures
Construction of a Suspended Sediment Concentration Inversion Model in The Yellow River Estuary Surrounding Waters Based on GOCI-I Images
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Lu MAO1, Na JIANG2, Juan WANG3, Shanwei LIU1, Jianyong CUI1, Mingming XU1
Affiliations
  • 1.Dept. Surveying and Mapping, China University of Petroleum (East China), Qingdao 266580, China
  • 2.Land Surveying and Mapping Institute of Shandong Province, Jinan 250102, China
  • 3.North China Sea Environmental Monitoring Center, State Oceanic Administration, Qingdao 266033, China
doi: 10.12347/j.ycyk.20240225001
Outline
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In order to achieve high-precision remote sensing inversion of suspended particulate matter concentration in the seas surrounding the Yellow River Estuary, this paper constructs seasonal models for spring, summer, and autumn, as well as a cross-seasonal model, utilizing GOCI-I image data and based on the WOA-BP algorithm. These models are compared with multiple algo-rithms such as Catboost, RF, KNN, BP and so on. The results reveal that within each seasonal model, the WOA-BP algorithm exhib-its superior performance on both the training and testing sets, with the average relative errors for the respective seasonal testing sets being 24.18%, 25.97%, and 29.42%. When the cross-seasonal testing set is employed to evaluate the three models, and their accura-cy is found to be significantly lacking, which indicates that seasonal models are not applicable across different seasons. In the cross-seasonal model, the WOA-BP algorithm again demonstrates the highest accuracy, with an overall average relative error of 26.96%. The average relative errors when testing with the three seasonal testing sets are 25.80%, 21.90%, and 37.17%, respectively. While the accuracy for summer is improved, the accuracy for the other two seasons falls below that of the corresponding seasonal models,with autumn experiencing the greatest decline in precision. Therefore, it is suggested that the cross-seasonal model be employed for spring and summer, whereas the appropriate seasonal models are recommended for autumn.

Suspended sediment concentration inversion  /  GOCI-I satellite data  /  Seasonal analysis  /  WOA-BP model
Lu MAO, Na JIANG, Juan WANG, Shanwei LIU, Jianyong CUI, Mingming XU. Construction of a Suspended Sediment Concentration Inversion Model in The Yellow River Estuary Surrounding Waters Based on GOCI-I Images[J]. Journal of Telemetry, Tracking and Command, 2024 , 45 (6) : 121 -130 . DOI: 10.12347/j.ycyk.20240225001
Year 2024 volume 45 Issue 6
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Article Info
doi: 10.12347/j.ycyk.20240225001
  • Receive Date:2024-02-25
  • Online Date:2026-03-19
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History
  • Received:2024-02-25
  • Revised:2024-10-08
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Affiliations
    1.Dept. Surveying and Mapping, China University of Petroleum (East China), Qingdao 266580, China
    2.Land Surveying and Mapping Institute of Shandong Province, Jinan 250102, China
    3.North China Sea Environmental Monitoring Center, State Oceanic Administration, Qingdao 266033, China
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表12种不同金属材料的力学参数

Family
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Number of
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Number of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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