Paper
19 January 2024 Research and application of semi-automatic geomorphology classification method on Caiwei Seamounts
Author Affiliations +
Proceedings Volume 12980, Fifth International Conference on Geoscience and Remote Sensing Mapping (ICGRSM 2023); 129800O (2024) https://doi.org/10.1117/12.3020910
Event: Fifth International Conference on Geoscience and Remote Sensing Mapping (ICGRSM 2023), 2023, Lianyungang, China
Abstract
The advancement of topography detection technologies over the whole ocean has led to a significant rise in the quantity of high-resolution and comprehensive data. This increase in data availability serves as a fundamental basis for the investigation of topography and geomorphology features in the deep sea. This study introduces the auxiliary classification using ruggedness and backscatter intensity data by considering the regional characteristics of the Caiwei seamounts. Through establishing a mapping relationship between the geomorphology types and geomorphology factors of the Caiwei seamounts, the semi-automatic geomorphology classification algorithm is enhanced. This algorithm enables batch calculation of geomorphology factors and succeeds in dividing the Caiwei seamounts into 10 distinct geomorphology units. Finally, a geomorphology classification map of the Caiwei seamounts is generated. The present methodology demonstrates a high level of accuracy in identifying various geomorphology types, including Summit edges and seamount ridges. This research is of great significance in studying the impact of seamount morphological alterations on the distribution features of biological organisms and the processes related to metallogenesis.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Dexiang Huang, Lei Wang, Yongfu Sun, Shengli Wang, Wei Gao, Weikun Xu, Wei Wang, Yixin Zhang, and Xiaoyang Lv "Research and application of semi-automatic geomorphology classification method on Caiwei Seamounts", Proc. SPIE 12980, Fifth International Conference on Geoscience and Remote Sensing Mapping (ICGRSM 2023), 129800O (19 January 2024); https://doi.org/10.1117/12.3020910
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