Research on Bathymetric Inversion Capability of Different Multispectral Remote Sensing Images in Seaports
In recent years, remote sensing has become an indispensable supplementary method for determining water depth in the seaports. At present, many scholars use multi-spectral satellite data to invert the water depth of the seaports, but how to select the appropriate satellite data in the seaports area i...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-01-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/23/3/1178 |
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| author | Wei Shen Jiaqi Wang Muyin Chen Lihua Hao Zhongqiang Wu |
| author_facet | Wei Shen Jiaqi Wang Muyin Chen Lihua Hao Zhongqiang Wu |
| author_sort | Wei Shen |
| collection | DOAJ |
| description | In recent years, remote sensing has become an indispensable supplementary method for determining water depth in the seaports. At present, many scholars use multi-spectral satellite data to invert the water depth of the seaports, but how to select the appropriate satellite data in the seaports area is worth exploring. In this article, the differences in the retrieving ability between domestic and foreign multispectral images are compared, through building the random forest model and the band ratio model, which use different multispectral images to conduct retrieving water depth in Nanshan Port in conjunction with the WBMS multi-beam sounding system. The band ratio model and random forest model are chosen for water depth exploration, remote sensing images use GF-6, GF-2, Sentinel-2B, and Landsat 8 OLI data, which are all popular and easily accessible. The final experiment results from the constant adjustment of the model parameter show that the domestic series of GF-6 images performed the best in this experiment. The Root Mean Square Error (RMSE) and Mean Relative Error (MRE) of the random forest model are only 1.202 and 0.187, respectively. Simultaneously, it is discovered that the ‘Red Edge’ band of GF-6 is also very helpful in improving the accuracy of water depth inversion, which is rarely mentioned in previous studies. To some extent, the preceding studies demonstrate that it is possible to investigate water depth using common multispectral remote sensing images. In the case of some bathymetry inversion models or in some waters, the aforementioned study demonstrates that it is possible to examine the water depth using domestic remote sensing images that are superior to foreign multispectral images in terms of bathymetry inversion ability. |
| first_indexed | 2024-03-11T09:25:55Z |
| format | Article |
| id | doaj.art-27ea5b03d978495d990e13fec534a15c |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-11T09:25:55Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-27ea5b03d978495d990e13fec534a15c2023-11-16T17:57:19ZengMDPI AGSensors1424-82202023-01-01233117810.3390/s23031178Research on Bathymetric Inversion Capability of Different Multispectral Remote Sensing Images in SeaportsWei Shen0Jiaqi Wang1Muyin Chen2Lihua Hao3Zhongqiang Wu4School of Marine Science, Shanghai Ocean University, Shanghai 201306, ChinaSchool of Marine Science, Shanghai Ocean University, Shanghai 201306, ChinaSchool of Marine Science, Shanghai Ocean University, Shanghai 201306, ChinaSchool of Marine Science, Shanghai Ocean University, Shanghai 201306, ChinaSchool of Information Science and Technology, Hainan Normal University, Haikou 571158, ChinaIn recent years, remote sensing has become an indispensable supplementary method for determining water depth in the seaports. At present, many scholars use multi-spectral satellite data to invert the water depth of the seaports, but how to select the appropriate satellite data in the seaports area is worth exploring. In this article, the differences in the retrieving ability between domestic and foreign multispectral images are compared, through building the random forest model and the band ratio model, which use different multispectral images to conduct retrieving water depth in Nanshan Port in conjunction with the WBMS multi-beam sounding system. The band ratio model and random forest model are chosen for water depth exploration, remote sensing images use GF-6, GF-2, Sentinel-2B, and Landsat 8 OLI data, which are all popular and easily accessible. The final experiment results from the constant adjustment of the model parameter show that the domestic series of GF-6 images performed the best in this experiment. The Root Mean Square Error (RMSE) and Mean Relative Error (MRE) of the random forest model are only 1.202 and 0.187, respectively. Simultaneously, it is discovered that the ‘Red Edge’ band of GF-6 is also very helpful in improving the accuracy of water depth inversion, which is rarely mentioned in previous studies. To some extent, the preceding studies demonstrate that it is possible to investigate water depth using common multispectral remote sensing images. In the case of some bathymetry inversion models or in some waters, the aforementioned study demonstrates that it is possible to examine the water depth using domestic remote sensing images that are superior to foreign multispectral images in terms of bathymetry inversion ability.https://www.mdpi.com/1424-8220/23/3/1178random forest modeband ratio modelbathymetry inversionmultispectral imagery |
| spellingShingle | Wei Shen Jiaqi Wang Muyin Chen Lihua Hao Zhongqiang Wu Research on Bathymetric Inversion Capability of Different Multispectral Remote Sensing Images in Seaports Sensors random forest mode band ratio model bathymetry inversion multispectral imagery |
| title | Research on Bathymetric Inversion Capability of Different Multispectral Remote Sensing Images in Seaports |
| title_full | Research on Bathymetric Inversion Capability of Different Multispectral Remote Sensing Images in Seaports |
| title_fullStr | Research on Bathymetric Inversion Capability of Different Multispectral Remote Sensing Images in Seaports |
| title_full_unstemmed | Research on Bathymetric Inversion Capability of Different Multispectral Remote Sensing Images in Seaports |
| title_short | Research on Bathymetric Inversion Capability of Different Multispectral Remote Sensing Images in Seaports |
| title_sort | research on bathymetric inversion capability of different multispectral remote sensing images in seaports |
| topic | random forest mode band ratio model bathymetry inversion multispectral imagery |
| url | https://www.mdpi.com/1424-8220/23/3/1178 |
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