Unmanned Aerial Vehicle Depth Inversion to Monitor River-Mouth Bar Dynamics
Monitoring the morphological evolution of a river-mouth bar is of both practical and scientific importance. A large amount of sediment is transported from a river to surrounding littoral cells via a deltaic bar after an extreme weather event. However, it is often not feasible to capture drastic morp...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-01-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/3/412 |
| _version_ | 1797407417620758528 |
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| author | Kana Hashimoto Takenori Shimozono Yoshinao Matsuba Takumi Okabe |
| author_facet | Kana Hashimoto Takenori Shimozono Yoshinao Matsuba Takumi Okabe |
| author_sort | Kana Hashimoto |
| collection | DOAJ |
| description | Monitoring the morphological evolution of a river-mouth bar is of both practical and scientific importance. A large amount of sediment is transported from a river to surrounding littoral cells via a deltaic bar after an extreme weather event. However, it is often not feasible to capture drastic morphological changes in the short term with conventional bathymetric surveys. This paper presents a depth-inversion method based on unmanned aerial vehicle technology to estimate two-dimensional bathymetry from video-sensed swell propagation. The estimation algorithm is tested over four cases with varying wave and bathymetric conditions and is validated with transect survey data. The test results suggest that the method can estimate deltaic-bar topography in front of a river mouth with a root-mean-square error of <0.5 m. The applicable range is limited by wave breaking in the inner bar and up to a depth of ~8 m, where swell intensity signals become ambiguous. A comparison of the different cases shows that the method works better under calm weather conditions with dominant swells propagating from non-local sources. Significant morphological changes of a river-mouth bar due to a powerful typhoon are successfully detected by observations right before and after the event. |
| first_indexed | 2024-03-09T03:42:10Z |
| format | Article |
| id | doaj.art-1b11d3cbe3c243b081a17e0b734a3e9e |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T03:42:10Z |
| publishDate | 2021-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-1b11d3cbe3c243b081a17e0b734a3e9e2023-12-03T14:39:08ZengMDPI AGRemote Sensing2072-42922021-01-0113341210.3390/rs13030412Unmanned Aerial Vehicle Depth Inversion to Monitor River-Mouth Bar DynamicsKana Hashimoto0Takenori Shimozono1Yoshinao Matsuba2Takumi Okabe3Department of Civil Engineering, The University of Tokyo, Tokyo 1138656, JapanDepartment of Civil Engineering, The University of Tokyo, Tokyo 1138656, JapanDepartment of Civil Engineering, The University of Tokyo, Tokyo 1138656, JapanRegional Satellite Campus Network, Mie University, Mie 5148507, JapanMonitoring the morphological evolution of a river-mouth bar is of both practical and scientific importance. A large amount of sediment is transported from a river to surrounding littoral cells via a deltaic bar after an extreme weather event. However, it is often not feasible to capture drastic morphological changes in the short term with conventional bathymetric surveys. This paper presents a depth-inversion method based on unmanned aerial vehicle technology to estimate two-dimensional bathymetry from video-sensed swell propagation. The estimation algorithm is tested over four cases with varying wave and bathymetric conditions and is validated with transect survey data. The test results suggest that the method can estimate deltaic-bar topography in front of a river mouth with a root-mean-square error of <0.5 m. The applicable range is limited by wave breaking in the inner bar and up to a depth of ~8 m, where swell intensity signals become ambiguous. A comparison of the different cases shows that the method works better under calm weather conditions with dominant swells propagating from non-local sources. Significant morphological changes of a river-mouth bar due to a powerful typhoon are successfully detected by observations right before and after the event.https://www.mdpi.com/2072-4292/13/3/412Unmanned Aerial Vehiclebathymetryriver mouthdelta |
| spellingShingle | Kana Hashimoto Takenori Shimozono Yoshinao Matsuba Takumi Okabe Unmanned Aerial Vehicle Depth Inversion to Monitor River-Mouth Bar Dynamics Remote Sensing Unmanned Aerial Vehicle bathymetry river mouth delta |
| title | Unmanned Aerial Vehicle Depth Inversion to Monitor River-Mouth Bar Dynamics |
| title_full | Unmanned Aerial Vehicle Depth Inversion to Monitor River-Mouth Bar Dynamics |
| title_fullStr | Unmanned Aerial Vehicle Depth Inversion to Monitor River-Mouth Bar Dynamics |
| title_full_unstemmed | Unmanned Aerial Vehicle Depth Inversion to Monitor River-Mouth Bar Dynamics |
| title_short | Unmanned Aerial Vehicle Depth Inversion to Monitor River-Mouth Bar Dynamics |
| title_sort | unmanned aerial vehicle depth inversion to monitor river mouth bar dynamics |
| topic | Unmanned Aerial Vehicle bathymetry river mouth delta |
| url | https://www.mdpi.com/2072-4292/13/3/412 |
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