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This competition focuses on land cover classification using polarimetric synthetic aperture radar (PolSAR) images from the AgriSAR 2009 campaign conducted over the Flevoland region in the Netherlands.

**Challenge**: Classify image pixels into **15 distinct land cover types** using polarimetric scattering features.

**Why This Matters**: 
- PolSAR provides all-weather, day-and-night imaging capabilities.
- Agricultural monitoring and land cover mapping are crucial for agricultural land management. 
- Machine learning techniques hold the potential to significantly enhance the accuracy of automated classification.

**Key Dataset Characteristics**:
- Source: AgriSAR 2009 Campaign (Flevoland)
- Features: 10 polarimetric scattering features extracted from quad-polarimetric SAR data
- Classes: 15 different land cover types