Opto-Electronic Engineering, Volume. 49, Issue 9, 220007(2022)
Nighttime sea fog recognition based on remote sensing satellite and deep neural decision tree
Figures & Tables(9)
Fig. 3. Sea fog identification result at UTC 18:20 on June 5, 2020 in the Yellow Sea and Bohai Sea
Fig. 4. The monitoring results of sea fog in the Yellow Sea and Bohai Sea from 15:00 to 20:00 UTC on June 5, 2020
Table 1. Experimental results of different network layers
View tableView in ArticleTable 1. Experimental results of different network layers
Method Middle/high clouds Stratus Sea fog Sea surface Average POD/(%) 89.30 76.71 82.12 92.15 85.07 Three-groups FAR/(%) 11.07 20.37 21.13 7.42 15.00 CSI/(%) 80.36 64.13 67.31 85.81 74.40 POD/(%) 89.09 80.87 86.47 92.84 87.32 Four- groups FAR/(%) 7.06 18.64 19.14 7.90 13.19 CSI/(%) 83.44 68.23 71.78 85.99 77.36 POD/(%) 90.40 78.59 82.00 90.65 85.41 Five- groups FAR/(%) 11.07 19.82 19.24 7.54 14.42 CSI/(%) 81.25 65.81 68.60 84.41 75.02 POD/(%) 91.99 77.60 80.24 91.34 85.29 Six- groups FAR/(%) 11.67 20.43 17.83 7.05 14.24 CSI/(%) 82.02 64.71 68.34 85.42 75.12
Table 2. Comparison of results of different convolution networks
View tableView in ArticleTable 2. Comparison of results of different convolution networks
Method Middle/high clouds Stratus Sea fog Sea surface Average POD/(%) 87.36 76.11 81.76 88.45 83.42 CNN_1D FAR/(%) 11.60 25.07 23.79 4.84 16.33 CSI/(%) 78.38 60.66 65.14 84.64 72.20 POD/(%) 89.09 80.87 86.47 92.84 87.32 CNN_2D FAR/(%) 7.06 18.64 19.14 7.90 13.19 CSI/(%) 83.44 68.23 71.78 85.99 77.36
Table 3. Comparison of ablation results
View tableView in ArticleTable 3. Comparison of ablation results
Method Middle/high clouds Stratus Sea fog Sea surface Average POD/(%) 90.40 67.59 73.65 93.30 81.24 ATF FAR/(%) 11.55 24.72 21.55 18.30 19.03 CSI/(%) 80.85 55.31 61.25 77.17 68.65 POD/(%) 89.44 81.96 80.47 89.49 85.34 ATL FAR/(%) 8.80 20.40 21.92 7.52 14.66 CSI/(%) 82.34 67.73 65.64 83.42 74.78 POD/(%) 89.09 80.87 86.47 92.84 87.32 WOA FAR/(%) 7.06 18.64 19.14 7.90 13.19 CSI/(%) 83.44 68.23 71.78 85.99 77.36
Table 4. Confusion matrix of model
View tableView in ArticleTable 4. Confusion matrix of model
True label Middle/high clouds Stratus Sea fog Sea surface Middle/high clouds 1290 85 58 15 Stratus 56 816 98 39 Sea fog 36 64 735 15 Sea surface 6 38 18 804
Table 5. Classification accuracy of different sea fog recognition methods
View tableView in ArticleTable 5. Classification accuracy of different sea fog recognition methods
Method Middle/high clouds Stratus Sea fog Sea surface Average POD/(%) 85.28 81.71 58.78 91.78 79.39 SVM FAR/(%) 19.12 21.56 31.02 9.05 20.19 CSI/(%) 70.97 66.72 46.49 84.10 67.07 POD/(%) 81.42 64.22 62.71 82.10 72.61 DT FAR/(%) 19.41 35.01 36.85 18.18 27.36 CSI/(%) 68.07 47.72 45.91 69.43 57.78 POD/(%) 89.99 81.17 85.41 93.76 87.58 ResNet FAR/(%) 8.37 17.94 18.24 6.13 12.67 CSI/(%) 83.15 68.94 71.74 88.36 78.05 POD/(%) 89.09 80.87 86.47 92.84 87.32 Ours FAR/(%) 7.06 18.64 19.14 7.90 13.19 CSI/(%) 83.44 68.23 71.78 85.99 77.36
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Tao Li, Wei Jin, Randi Fu, Gang Li, Caoqian Yin. Nighttime sea fog recognition based on remote sensing satellite and deep neural decision tree[J]. Opto-Electronic Engineering, 2022, 49(9): 220007
Paper Information
Category: Article
Received: Mar. 1, 2022
Accepted: --
Published Online: Oct. 13, 2022
The Author Email: Jin Wei (xyjw1969@126.com)
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