Seamounts Lists: Machine Learning Predictions and Updated Catalogs

41.1 MB of data contains multiple lists of predicted and cataloged seamounts. Zhenyu Wang published these files on figshare, last updated in May 2026. The dataset includes raw machine learning predictions, post-processed results, and updated versions of two existing seamount catalogs.

Use Cases

• Validate machine learning predictions for seamount detection based on the described post-processing procedure.
• Compare updated seamount catalogs (Hillier & Watts 2007, Gevorgian et al. 2023) with new predictions.
• Analyze the distribution of seamounts by height, volume, and area based on the labeled features.
• Study the characteristics of small or near-continent seamounts filtered out during post-processing.

Strengths

• Dataset size is 41.1 MB, indicating substantial content.
• Includes multiple curated lists (raw predictions, post-processed results, updated catalogs) for comparison.
• Provides explicit filter parameters (e.g., width of 400 km) for the prediction models.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The description does not specify the spatial coverage or source data for the predictions.

Provenance

Source

Zhenyu Wang via figshare.

Collection Method

Likely generated using machine learning models on bathymetric data, followed by morphological post-processing.

Freshness

Last updated 2026-05-18 21:33:58; freshness should be verified.