Your browser doesn't support javascript.
loading
Nearshore Depth Estimation Using Fine-Resolution Remote Sensing of Ocean Surface Waves.
Liu, Mengyuan; Zhu, Shouxian; Cheng, Shanling; Zhang, Wenjing; Cao, Guangsong.
Afiliación
  • Liu M; College of Oceanography, Hohai University, Nanjing 210098, China.
  • Zhu S; College of Oceanography, Hohai University, Nanjing 210098, China.
  • Cheng S; College of Oceanography, Hohai University, Nanjing 210098, China.
  • Zhang W; College of Meteorology and Oceanography, National University of Defense Technology, Changsha 410073, China.
  • Cao G; Institute of Water Science and Technology, Hohai University, Nanjing 210098, China.
Sensors (Basel) ; 23(23)2023 Nov 21.
Article en En | MEDLINE | ID: mdl-38067689
ABSTRACT
In the field of water depth inversion using imagery, the commonly used methods are based on water reflectance and wave extraction. Among these methods, the Optical Bathymetry Method (OBM) is significantly influenced by bottom sediment and climate, while the wave method requires a specific study area. This study introduces a method combining the FFT and spatial profile measurement to invert the wavelength of the wave bathymetry method (WBM), which enhances accuracy and reduces workload. The method was applied to remote sensing images of Sanya Bay in China, obtained from the Worldview satellite. The average error of the inverted depth results after applying the wavelength inversion technique was 15.9%, demonstrating consistency with the depth measurements obtained through the OBM in clear water of the bay. The WBM has notable advantages over the OBM, as it is unaffected by water quality. In addition, the influence of wave period on the accuracy of water depth retrieval was theoretically evaluated, revealing that a larger wave period leads to a better depth measurement. The depth measurement from two images with different wave periods aligned with the theoretical analysis. These results showcase the applicability and potential of the WBM for accurately estimating water depth in various coastal environments.
Palabras clave

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2023 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2023 Tipo del documento: Article País de afiliación: China