LandSegmenter creates a task-specific foundation model for LULC mapping using weak labels from existing products, an RS adapter, text encoder, and confidence-guided fusion to achieve competitive zero-shot performance across modalities and taxonomies.
publisher: Nature Publishing Group
2 Pith papers cite this work. Polarity classification is still indexing.
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AEF embeddings perform competitively with RS models for local agricultural tasks but show limited spatial transferability, time sensitivity, and interpretability.
citing papers explorer
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LandSegmenter: Towards a Flexible Foundation Model for Land Use and Land Cover Mapping
LandSegmenter creates a task-specific foundation model for LULC mapping using weak labels from existing products, an RS adapter, text encoder, and confidence-guided fusion to achieve competitive zero-shot performance across modalities and taxonomies.
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Harvesting AlphaEarth: Benchmarking the Geospatial Foundation Model for Agricultural Downstream Tasks
AEF embeddings perform competitively with RS models for local agricultural tasks but show limited spatial transferability, time sensitivity, and interpretability.