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Search Results (3)

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Keywords = sun glitter remote sensing

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17 pages, 5469 KiB  
Article
An Experiment on Multi-Angle Sun Glitter Remote Sensing of Water Surface Using Multi-UAV
by Chen Wang, Huaguo Zhang, Guanghong Liao, Wenting Cao, Juan Wang, Dongling Li and Xiulin Lou
Drones 2025, 9(6), 400; https://doi.org/10.3390/drones9060400 - 28 May 2025
Viewed by 527
Abstract
Unmanned aerial vehicle (UAV) remote sensing has become an important tool for modern remote sensing technology with its low cost and high flexibility. Sun glitter (SG) remote sensing based on satellite platforms shows great potential in the fields of marine dynamic environment and [...] Read more.
Unmanned aerial vehicle (UAV) remote sensing has become an important tool for modern remote sensing technology with its low cost and high flexibility. Sun glitter (SG) remote sensing based on satellite platforms shows great potential in the fields of marine dynamic environment and marine oil spill, but the analysis and application of SG images based on UAV need to be further studied. In this study, we conduct a multi-angle water surface SG remote sensing experiment using multi-UAV and collect images under different observation parameters. Then, we analyze and discuss the SG signal in the multi-angle images, especially the distribution and intensity of SG. In addition, a model for extracting SG signals from images based on region-based dark pixel retrieval is proposed in this study. Since the current Cox-Munk model is only applicable to statistical SG, the extracted SG images are reduced in resolution by mean filtering. Based on the multi-angle SG remote sensing model, the water surface roughness and equivalent refractive index are estimated. The estimated results are compared with measured and literature data. Additionally, the influence of different observation angle combinations on the inversion results is also discussed. The results of the study show that multi-angle SG remote sensing of water surface based on UAVs provides a new idea for the analysis and application of image signals, which has an important role to play. Full article
(This article belongs to the Special Issue The Application of Image Processing and Signal Processing Techniques in Unmanned Aerial Vehicles)
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19 pages, 12313 KiB  
Article
LSTM-Based Remote Sensing Inversion of Largescale Sand Wave Topography of the Taiwan Banks
by Yujin Zhao, Liaoying Zhao, Huaguo Zhang and Bin Fu
Remote Sens. 2021, 13(16), 3313; https://doi.org/10.3390/rs13163313 - 21 Aug 2021
Cited by 1 | Viewed by 3154
Abstract
Shallow underwater topography has important practical applications in fisheries, navigation, and pipeline laying. Traditional multibeam bathymetry is limited by the high cost of largescale topographic surveys in large, shallow sand wave areas. Remote sensing inversion methods to detect shallow sand wave topography in [...] Read more.
Shallow underwater topography has important practical applications in fisheries, navigation, and pipeline laying. Traditional multibeam bathymetry is limited by the high cost of largescale topographic surveys in large, shallow sand wave areas. Remote sensing inversion methods to detect shallow sand wave topography in Taiwan rely heavily on measured water depth data. To address these problems, this study proposes a largescale remote sensing inversion model of sand wave topography based on long short-term memory network machine learning. Using multi-angle sun glitter remote sensing to obtain sea surface roughness (SSR) information and by learning and training SSR and its corresponding water depth information, the sand wave topography of a largescale shallow sea sand wave region is extracted. The accuracy of the model is validated through its application to a 774 km2 area in the sand wave topography of the Taiwan Banks. The model obtains a root mean square error of 3.31–3.67 m, indicating that the method has good generalization capability and can achieve a largescale topographic understanding of shallow sand waves with some training on measured bathymetry data. Sand wave topography is widely present in tidal environments; our method has low requirements for ground data, with high application value. Full article
(This article belongs to the Special Issue GIS and RS in Ocean, Island and Coastal Zone)
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21 pages, 17484 KiB  
Article
On Optimal Imaging Angles in Multi-Angle Ocean Sun Glitter Remote-Sensing Platforms to Observe Sea Surface Roughness
by Dazhuang Wang, Liaoying Zhao, Huaguo Zhang, Juan Wang, Xiulin Lou, Peng Chen, Kaiguo Fan, Aiqin Shi and Dongling Li
Sensors 2019, 19(10), 2268; https://doi.org/10.3390/s19102268 - 16 May 2019
Cited by 2 | Viewed by 3936
Abstract
Sea surface roughness (SSR) is a key physical parameter in studies of air–sea interactions and the ocean dynamics process. The SSR quantitative inversion model based on multi-angle sun glitter (SG) images has been proposed recently, which will significantly promote SSR observations through multi-angle [...] Read more.
Sea surface roughness (SSR) is a key physical parameter in studies of air–sea interactions and the ocean dynamics process. The SSR quantitative inversion model based on multi-angle sun glitter (SG) images has been proposed recently, which will significantly promote SSR observations through multi-angle remote-sensing platforms. However, due to the sensitivity of the sensor view angle (SVA) to SG, it is necessary to determine the optimal imaging angle and their combinations. In this study, considering the design optimization of imaging geometry for multi-angle remote-sensing platforms, we have developed an error transfer simulation model based on the multi-angle SG remote-sensing radiation transmission and SSR estimation models. We simulate SSR estimation errors at different imaging geometry combinations to evaluate the optimal observation geometry combination. The results show that increased SSR inversion accuracy can be obtained with SVA combinations of 0° and 20° for nadir- and backward-looking SVA compared with current combinations of 0° and 27.6°. We found that SSR inversion prediction error using the proposed model and actual SSR inversion error from field buoy data are correlated. These results can provide support for the design optimization of imaging geometry for multi-angle ocean remote-sensing platforms. Full article
(This article belongs to the Special Issue Remote Sensors for Applications at Multi-Acquisition Levels and Resolutions)
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