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SpatialVec: A Unified Representation Learning Framework for Geospatial Objects with Boundary-Aware Sampling
Spatial representation learning is essential for Geospatial Artificial Intelligence (GeoAI) applications, enabling machine learning models to capture the geometry, location, and spatial relationships of geographic entities such as points, polylines, and polygons. Existing spatial encoding methods of
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