engine_echo_data_viz

Xinyuan Lin

I contributed the interactive map-based echogram visualization system in the mapapp/ folder. This includes both frontend and backend components to support real-time rendering of ocean acoustic data.

Key contributions:

• Developed a basemap viewer with selectable layers (standard, terrain, ocean)
• Enabled users to click on map trajectory points, select time ranges, and generate echograms dynamically
• Implemented trajectory highlighting based on user-selected time ranges
• Built the backend Flask API (app.py) and frontend logic (app.js) for dynamic echogram generation with custom Sv range and channel selection
• Set up benchmarking and multi-resolution resampling via downsample.py to support:
  • Low-resolution track data for lightweight map rendering
  • High-resolution echogram slices rendered on demand

The high-resolution and low-resolution datasets were processed using downsample.py, downsample_highdensity.py and integrated into the mapapp/ folder for use by the map interface and echogram renderer.

How to Run the Map App Locally

To run the echogram map application on your local machine:

1. Download the high-resolution dataset merged_60s.nc (approx. 314MB) from the following link:
   Download from Google Drive

2. Place the file in the following directory: mapapp/merged_60s.nc

3. In your terminal, navigate to the mapapp/ folder and start the Flask server:

cd mapapp
python run.py

Sasha Lai

Developed an interactive prototype for echogram-based region selection and export using Jupyter notebooks, located in the region-browser/ directory. This tool supports both manual polygon annotation and the matching of pre-existing region labels to NOAA acoustic datasets.

• region-browser/polygon_selection.ipynb: Interactive tool for drawing and editing polygons on echograms

• region-browser/match_region_labels_v1.ipynb: Matches existing region label CSVs to their corresponding MVBS .zarr files on S3 based on ping_time overlap

• region-browser/echogram_annotation_tool.ipynb: Consolidated notebook combining interactive annotation, region matching, and export functionality

Key contributions:

• Real-time polygon drawing and editing on echograms using PolyDraw and PolyEdit tools with HoloViews/Panel integration

• Interactive loading of region label files and matching with corresponding MVBS datasets on S3

• Matching algorithm to link labeled regions with their source .zarr files based on ping_time range overlap

• Export functionality for newly drawn region polygons with timestamped CSV output

• Real-time histogram visualizations and statistical summaries of Sv (volume backscattering strength) values within user-selected regions

Siyu Meng

I mainly contributed to the echshader package by fixing existing bugs, improving code robustness, and adding new features.

Key contributions:

• Resolve pandas version conflict: I update DataFrame processing to align with pandas API changes. Therefore, echoshader can support pandas versions greater than 2.0.

• Check the input dataset: Add input validation to ensure that users provide the correct type of dataset.

• Generate 3D curtain by plotly: Upgrade the curtain plot method in the echoshader package. This was previously drawn using pyvista, which was relatively crude and could only be used for simple observation. I upgraded it using plotly, and the image is more intuitive and you can see the specific coordinate information. In addition, the rendering time was reduced by around 50%.

Ethan Takahashi

I contributed to the frontend code and the option to display multiple sources of data simultaneously in the `multi-track folder. ** Key Contributions**

• Utilized maplibre-gl to display geospatial context for ship data.
• Modified display to allow multiple data sources to be displayed simultaneously.
• Add toggleable and individually controllable buttons for each specific data source.