Leg laying zone selection technology for deep sea exploration platform based on gradient and variance of digital elevation model

Zhenming Zheng; Xuyang Zhang; Lunyi Cui; Jinzhu Liang; Shuai Yang; Xinghua Chen; Peng Wu

doi:10.1117/12.3032224

3 June 2024 Leg laying zone selection technology for deep sea exploration platform based on gradient and variance of digital elevation model

Zhenming Zheng, Xuyang Zhang, Lunyi Cui, Jinzhu Liang, Shuai Yang, Xinghua Chen, Peng Wu

Author Affiliations +

Proceedings Volume 13170, International Conference on Remote Sensing, Surveying, and Mapping (RSSM 2024); 131701D (2024) https://doi.org/10.1117/12.3032224
Event: Third International Conference on Remote Sensing, Surveying, and Mapping (RSSM 2024), 2024, Wuhan, China

Abstract

In order to research the selection of leg laying zone under the offshore operation of deep-sea exploration platform, considering the need for real-time collection of information such as terrain elevation and small scale terrain roughness, the submarine terrain feature extraction technology based on gradient and variance of Digital Elevation Model (DEM) is used to fuzzy process and reconstruct the seabed terrain, and generate the point cloud map of the seabed terrain. The results show that the point cloud map information can reflect the roughness of the terrain in this zone, and also reflect the slope information in this zone to a certain extent. This method can provide a rough assessment of the topographic characteristics of the leg laying zone and determine the candidate leg laying zone for the deep-sea exploration platform.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Zhenming Zheng, Xuyang Zhang, Lunyi Cui, Jinzhu Liang, Shuai Yang, Xinghua Chen, and Peng Wu "Leg laying zone selection technology for deep sea exploration platform based on gradient and variance of digital elevation model", Proc. SPIE 13170, International Conference on Remote Sensing, Surveying, and Mapping (RSSM 2024), 131701D (3 June 2024); https://doi.org/10.1117/12.3032224

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KEYWORDS

Feature extraction

Windows

Reflection

Engineering

Image processing

Navigation systems

Point clouds

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