VID_WBT: A Video Imagery Dataset for Nearshore Wave Breaking Type Classification

Wave breaking type is a fundamental indicator of nearshore hydrodynamic processes, directly reflecting wave energy dissipation mechanisms. With the advancement of shore-based video monitoring, remote sensing has emerged as an efficient tool for identifying wave breaking types. However, existing studies predominantly rely on static single-frame imagery, limiting the ability to capture the dynamic evolution of breaking events. In this study, we present the first publicly available video imagery dataset dedicated to wave breaking type classification. The dataset comprises 9,000 labeled wave breaking clips collected from 15 cameras across six morphologically diverse coastal sites, encompassing three primary breaking types: Spilling, Plunging, and Surging. A rigorous data curation workflow is implemented to ensure quality and consistency. This dataset offers a valuable resource for video-based wave breaking monitoring and provides technical support for advancing the understanding of nearshore wave dynamics.