Remote Sensing Monitoring of Green Tide Disaster Using MODIS and GF-1 Data: A Case Study in the Yellow Sea
Satellites with low-to-medium spatial resolution face challenges in monitoring the early and receding stages of green tides, while those with high spatial resolution tend to reduce the monitoring frequency of such phenomena. This study aimed to observe the emergence, evolution, and migratory pattern...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-11-01
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| Series: | Journal of Marine Science and Engineering |
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| Online Access: | https://www.mdpi.com/2077-1312/11/12/2212 |
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| author | Yanzhuo Men Yingying Liu Yufei Ma Ka Po Wong Jin Yeu Tsou Yuanzhi Zhang |
| author_facet | Yanzhuo Men Yingying Liu Yufei Ma Ka Po Wong Jin Yeu Tsou Yuanzhi Zhang |
| author_sort | Yanzhuo Men |
| collection | DOAJ |
| description | Satellites with low-to-medium spatial resolution face challenges in monitoring the early and receding stages of green tides, while those with high spatial resolution tend to reduce the monitoring frequency of such phenomena. This study aimed to observe the emergence, evolution, and migratory patterns of green tides. We integrated GF-1 and MODIS imagery to collaboratively monitor the green tide disaster in the Yellow Sea during 2021. Initially, a linear regression model was employed to adjust the green tide coverage area as captured using MODIS imagery. We jointly observed the distribution range, drift path, and coverage area of the green tide and analyzed the drift path in coordination with offshore wind field and flow field data. Furthermore, we investigated the influence of SST, SSS, and rainfall on the 2021 green tide outbreak. The correlations calculated between SST, SSS, and precipitation with the changes in the area of the green tide were 0.43, 0.76, and 0.48, respectively. Our findings indicate that the large-scale green tide outbreak in 2021 may be associated with several factors. An increase in SST and SSS during the initial phase of the green tide established the essential conditions, while substantial rainfall during its developmental stage provided favorable conditions. Notably, the SSS exhibited a close association with the outbreak of the green tide. |
| first_indexed | 2024-03-08T20:37:34Z |
| format | Article |
| id | doaj.art-25c0f21d8934428aba0a9587b48ca5e7 |
| institution | Directory Open Access Journal |
| issn | 2077-1312 |
| language | English |
| last_indexed | 2024-03-08T20:37:34Z |
| publishDate | 2023-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj.art-25c0f21d8934428aba0a9587b48ca5e72023-12-22T14:18:34ZengMDPI AGJournal of Marine Science and Engineering2077-13122023-11-011112221210.3390/jmse11122212Remote Sensing Monitoring of Green Tide Disaster Using MODIS and GF-1 Data: A Case Study in the Yellow SeaYanzhuo Men0Yingying Liu1Yufei Ma2Ka Po Wong3Jin Yeu Tsou4Yuanzhi Zhang5College of Marine Science, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaCollege of Marine Science, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaCollege of Marine Science, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaDepartment of Applied Social Sciences, The Hong Kong Polytechnic University, Hong Kong 999777, ChinaDepartment of Architecture and Civil Engineering, City University of Hong Kong, Hong Kong 999777, ChinaCollege of Marine Science, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaSatellites with low-to-medium spatial resolution face challenges in monitoring the early and receding stages of green tides, while those with high spatial resolution tend to reduce the monitoring frequency of such phenomena. This study aimed to observe the emergence, evolution, and migratory patterns of green tides. We integrated GF-1 and MODIS imagery to collaboratively monitor the green tide disaster in the Yellow Sea during 2021. Initially, a linear regression model was employed to adjust the green tide coverage area as captured using MODIS imagery. We jointly observed the distribution range, drift path, and coverage area of the green tide and analyzed the drift path in coordination with offshore wind field and flow field data. Furthermore, we investigated the influence of SST, SSS, and rainfall on the 2021 green tide outbreak. The correlations calculated between SST, SSS, and precipitation with the changes in the area of the green tide were 0.43, 0.76, and 0.48, respectively. Our findings indicate that the large-scale green tide outbreak in 2021 may be associated with several factors. An increase in SST and SSS during the initial phase of the green tide established the essential conditions, while substantial rainfall during its developmental stage provided favorable conditions. Notably, the SSS exhibited a close association with the outbreak of the green tide.https://www.mdpi.com/2077-1312/11/12/2212green tideGF-1MODISthe Yellow Sea |
| spellingShingle | Yanzhuo Men Yingying Liu Yufei Ma Ka Po Wong Jin Yeu Tsou Yuanzhi Zhang Remote Sensing Monitoring of Green Tide Disaster Using MODIS and GF-1 Data: A Case Study in the Yellow Sea Journal of Marine Science and Engineering green tide GF-1 MODIS the Yellow Sea |
| title | Remote Sensing Monitoring of Green Tide Disaster Using MODIS and GF-1 Data: A Case Study in the Yellow Sea |
| title_full | Remote Sensing Monitoring of Green Tide Disaster Using MODIS and GF-1 Data: A Case Study in the Yellow Sea |
| title_fullStr | Remote Sensing Monitoring of Green Tide Disaster Using MODIS and GF-1 Data: A Case Study in the Yellow Sea |
| title_full_unstemmed | Remote Sensing Monitoring of Green Tide Disaster Using MODIS and GF-1 Data: A Case Study in the Yellow Sea |
| title_short | Remote Sensing Monitoring of Green Tide Disaster Using MODIS and GF-1 Data: A Case Study in the Yellow Sea |
| title_sort | remote sensing monitoring of green tide disaster using modis and gf 1 data a case study in the yellow sea |
| topic | green tide GF-1 MODIS the Yellow Sea |
| url | https://www.mdpi.com/2077-1312/11/12/2212 |
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