| --- |
| id: green_tide |
| type: element |
| name: Green tide / Enteromorpha |
| task_types: [semantic_segmentation, polygon_extraction] |
| preferred_heads: [validity, context, semantic_segmentation] |
| label_formats: [mask, polygon, geojson, shp] |
| positive_label: green_tide |
| negative_policy: unlabeled_is_ignore |
| typical_sensors: [PMS, MUX, MSS] |
| typical_resolutions_m: [2, 8, 10] |
| --- |
| |
| # Green Tide / Enteromorpha |
|
|
| Green tide is a floating-algae target. It can be confused with land vegetation, |
| aquaculture structures, cloud edges, turbid water, sunglint, and black/no-data |
| regions if the model is trained as a simple foreground/background classifier. |
|
|
| ## Required Context |
|
|
| - Validity handling: black borders and no-data pixels must not be interpreted as green tide. |
| - Context handling: land and water context should be learned or provided as labels/hard negatives. |
| - Do not assume a coastline vector or external land mask exists. |
|
|
| ## Recommended Output |
|
|
| - Per-pixel probability map for green tide. |
| - Binary candidate mask after validity/context filtering. |
| - Optional polygon extraction for product delivery. |
|
|
| ## Failure Modes |
|
|
| - Land vegetation is often spectrally similar to algae. |
| - Black borders can be falsely predicted when labels do not include invalid regions. |
| - Single-element binary models overpredict on unknown ecological elements. |
|
|
|
|
