Author Affiliations
1School of Marine Sciences, Nanjing University of Information Science and Technology, Nangjing, Jiangsu 210044, China2Jiangsu Key Laboratory of Ocean Dynamics Remote Sensing and Acoustics, Nangjing, Jiangsu 210044, China3Jiangsu Research Center for Ocean Survey Technology, Nangjing, Jiangsu 210044, Chinashow less
Fig. 1. Distribution of Ulva prolifera in Yellow Sea area. (a) Location of Yellow Sea, where RGB image shows pseudo-color composite image of GOCI acquired on 26 May, 2017; (b) true-color composite image of GOCI along coast of Qingdao acquired on 26 May, 2017; (c) aerial photo of Qingdao coast attacked by Ulva prolifera taken on 10 July, 2016
Fig. 2. Mean value (solid line) and standard deviation (shadow) of Rayleigh-corrected reflectance spectra of macroalgae, seawater, terrestrial vegetation, and cloud pixels
Fig. 3. Characteristic curves of K-T transformation components of floating macroalgae and seawater at three different periods (error lines represent standard deviation of mean values). (a) 19 May, 2017; (b) 16 June, 2017; (c) 13 July, 2017; (d) three different periods
Fig. 4. Probability and cumulative probability distributions of TCT-GTI values for different target object pixels. (a) Seawater pixels (N=12634); (b) Ulva prolifera pixels (N=7570); (c) mean values and standard deviation of TCT-GTI values for all Ulva prolifera and seawater pixels
Fig. 5. Probability and cumulative probability distributions of brightness values for different target object pixels. (a) Ulva prolifera (N=15078); (b) seawater (N=12633); (c) thick cloud (N=181624); (d) mean values and standard deviation of brightness values for all Ulva prolifera, seawater, and thick cloud pixels
Fig. 6. Confusion matrix and all indexes of accuracy evaluation
Fig. 7. Comparison of results of green-tide extraction using three different algorithms. (a) (e) (i) Pseudo-color images for different regions; (b)-(d) results of green-tide extraction using TCT-GTI algorithm; (f)-(h) results of green-tide extraction using AFAI algorithm; (j)-(l) results of green-tide extraction using IGAG algorithm
Fig. 8. Accuracy evaluation values of TCT-GTI, AFAI, and IGAG algorithms
Fig. 9. Coverage area of Ulva prolifera as a function of time
Fig. 10. Monitoring results of green tide of GOCI images at different time and its drifting trajectory. (a) Distribution of Ulva prolifera on 13 May, 2017; (b) distribution of Ulva prolifera on 21 May, 2017; (c) distribution of Ulva prolifera on 4 June, 2017; (d) distribution of Ulva prolifera on 7 June, 2017; (e) distribution of Ulva prolifera on 26 June, 2017; (f) distribution of Ulva prolifera on 27 June, 2017; (g) distribution of Ulva prolifera on 1 Ju
Fig. 11. Average wind-field distributions for corresponding dates of green-tide remote sensing monitoring. (a) May 13-21,2017; (b) May 21-June 4,2017; (c) June 4-7, 2017; (d) June 6-26, 2017; (e) June 26-27, 2017; (f) June 27-July 1, 2017
Band | Band center /nm | Bandwidth /nm | SNR(signal to noise ratio) | Type | Primary use |
---|
1 | 412 | 20 | 1000 | Visible | Yellow substance turbidity | 2 | 443 | 20 | 1190 | Visible | Chlorophyll absorption maximum | 3 | 490 | 20 | 1170 | Visible | Chlorophyll and other pigments | 4 | 555 | 20 | 1070 | Visible | Turbidity, suspended sediment | 5 | 660 | 20 | 1010 | Visible | Baseline of fluorescence signal,chlorophyll, suspended sediment | 6 | 680 | 10 | 870 | Visible | Atmospheric correctionand fluorescence signal | 7 | 745 | 20 | 860 | NIR | Atmospheric correction andbaseline of fluorescence | 8 | 865 | 40 | 750 | NIR | Aerosol optical thickness, vegetation,water vapor reference over the ocean |
|
Table 1. Band characteristics of GOCI sensor and its main applications
Region | TCT-GTI | AFAI | IGAG | | |
---|
Pixel No. | Aa /km2 | | | Pixel No. | Aa /km2 | Pixel No. | Aa / km2 |
---|
Total area | 22627 | 5656.75 | 22912 | 5728.00 | 23 | 5652.00 | Region 1 | 911 | 227.75 | 877 | 219.25 | 962 | 240.50 | Region 2 | 125 | 31.25 | 102 | 25.50 | 96 | 24.00 |
|
Table 2. Comparison of macroalgae coverage areas for three algorithms