Results 1 to 10 of about 353,191 (161)

A Convolutional Neural Network with Spatial Location Integration for Nearshore Water Depth Inversion [PDF]

Sensors, 2023
Nearshore water depth plays a crucial role in scientific research, navigation management, coastal zone protection, and coastal disaster mitigation. This study aims to address the challenge of insufficient feature extraction from remote sensing data in ...
Chunlong He, Qigang Jiang, Guofang Tao, Zhenchao Zhang   +3 more
doaj   +5 more sources

Accurate Depth Inversion Method for Coastal Bathymetry: Introduction of Water Wave HighOrder Dispersion Relation [PDF]

Journal of Marine Science and Engineering, 2020
This paper proposes a wave model for the depth inversion of sea bathymetry based on a new highorder dispersion relation which is more suitable for intermediate water depth. The core of this model, a highorder dispersion relation is derived in this paper.
Hongli Ge, Hao Liu, Libang Zhang
doaj   +3 more sources

Enhancing water depth inversion accuracy via SAR and variable window sliding segmentation

Frontiers in Marine Science
The utilization of synthetic aperture radar (SAR) for depth inversion is crucial for accurate underwater mapping. However, current SAR-based techniques face challenges in segmentation accuracy, which directly affects inversion precision and spatial ...
Meng Zhang, Meng Zhang, Chao Qi, Chao Qi, Fanlin Yang, Fanlin Yang, Ruifu Wang, Ruifu Wang, Saied Pirasteh, Saied Pirasteh   +9 more
doaj   +3 more sources

Effect of the One-to-Many Relationship between the Depth and Spectral Profile on Shallow Water Depth Inversion Based on Sentinel-2 Data

Remote Sensing
In shallow water, Sentinel-2 multispectral imagery has only four visible bands and limited quantization levels, which easily leads to the occurrence of the same spectral profile but different depth (SSPBDD) phenomenon, resulting in a one-to-many ...
Erhui Huang, Benqing Chen, Kai Luo, Shuhan Chen   +3 more
doaj   +3 more sources

Enhancing Water depth inversion accuracy in turbid coastal environments using random forest and coordinate attention mechanisms

Frontiers in Marine Science
This study introduces an innovative water depth estimation method for complex coastal environments, focusing on Yantian Port. By combining Random Forest algorithms with a Coordinate Attention mechanism, we address limitations of traditional bathymetric ...
Siwen Fang, Zhongqiang Wu, Zhongqiang Wu, Shulei Wu, Zhixing Chen, Wei Shen, Wei Shen, Zhihua Mao   +7 more
doaj   +3 more sources

A METHOD OF WATER DEPTH INVERSION IN COASTAL AREA CONSIDERING TEMPERATURE INFORMATION [PDF]

ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2021
The remote sensing method for water depth inversion is fast, flexible, and low in cost, which has become an important means of method for water depth detection. This paper takes the coastal area where is around Gulangyu Island as the research area. Based
Y. Liu, X. Gao, G. Wang, G. Wang, T. Zhang, J. Wang   +5 more
doaj   +3 more sources

Water Depth Inversion From a Single SPOT-5 Dataset [PDF]

IEEE Transactions on Geoscience and Remote Sensing, 2016
Knowing bathymetry at intermediate depth, over large areas, and at a reasonable cost is a key issue. Spaceborne remote sensing techniques must play an essential role in retrieving such bathymetry. In this paper, a method is proposed that aims to address this issue without any in situ measurements by exploiting the characteristics of the SPOT-5 ...
Poupardin, Adrien, Idier, Déborah, de Michele, Marcello, Raucoules, Daniel   +3 more
openaire   +4 more sources

Joint sensing of bedload flux and water depth by seismic data inversion [PDF]

Water Resources Research, 2019
AbstractRivers are the fluvial conveyor belts routing sediment across the landscape. While there are proper techniques for continuous estimates of the flux of suspended solids, constraining bedload flux is much more challenging, typically involving extensive measurement infrastructure or labor‐intensive manual measurements. Seismometers are potentially
M. Dietze, S. Lagarde, E. Halfi, J. B. Laronne, J. M. Turowski   +4 more
openaire   +6 more sources

Water Depth Inversion based on Landsat-8 Date and Random Forest Algorithm

Journal of Physics: Conference Series, 2020
Abstract In view of the fact that the traditional water depth inversion model is susceptible to water quality and environmental factors, the water depth inversion model is constructed using the random forest algorithm using the high resolution remote sensing image of the Huangyan Island area and the corresponding measured water depth ...
Jin Zhang, Shujun Li, Mo Wang
openaire   +2 more sources

Water Depth Inversion in Haikou Bay Based on TM Image [PDF]

Proceedings of the 2013 International Conference on Remote Sensing,Environment and Transportation Engineering, 2013
Remote sensing has been proved to be a useful technique in measuring water depth in coastal zone. This paper takes Haikou Bay as the study area. The spectral analysis of the correlation index between TM image and the observed water depth from chart is made.
Zeng Wenhua, Zhang Xiaodong, Zhu Shouxian, Ruan Kun   +3 more
openaire   +2 more sources