metadata
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.