A Hierarchical Spatiotemporal Index for Bathymetric Data in Approach Channels

Approach channels are affected by sedimentation and scour, resulting in continuous changes in underwater topography. Such processes tend to generate shallow spots and inadequate navigable dimensions, posing safety hazards that undermine both waterway resilience and navigation capacity. To address these issues, this paper proposes a multi-level grid-based spatiotemporal indexing method for bathymetric data, aiming to support resilience-oriented management by improving the effectiveness of bathymetric data management. First, a channel-segment-section partitioning strategy is designed to construct hierarchical progressive grids for the efficient organization of massive bathymetric data. Second, a multi-dimensional spatiotemporal integrated query method is developed to meet diverse analytical and retrieval requirements. Third, a digital depth model (DDM) construction method is introduced that integrates boundary-constrained terrain reconstruction with efficient mesh optimization, enabling underwater terrain representation that adapts to the elongated and irregular morphology of approach channels. The contribution of this work lies not in proposing new individual algorithms but in the tailored integration of these techniques to address the specific challenges of approach-channel bathymetric data. Experimental results demonstrate that the proposed method achieves high construction efficiency across different storage and query schemes. The method enhances the retrieval and analytical capabilities of bathymetric data in representative application scenarios, such as shallow spot identification, critical section analysis, dredging analysis, and erosion–deposition evolution. Consequently, these improvements provide technical support for resilience-oriented channel management and ensure navigational safety.