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#gaofen β€” Public Fediverse posts

Live and recent posts from across the Fediverse tagged #gaofen, aggregated by home.social.

  1. Glacial Lake Mapping Using Remote Sensing Geo-Foundation Model
    --
    doi.org/10.1016/j.jag.2025.104 <-- shared paper
    --
    HIGHLIGHTS:
    β€’ Proposed U-ViT model based on Prithvi GFM for multi-sensor glacial lake mapping.
    β€’ Achieved an F1 score of 0.894 on Sentinel-1&2, surpassing CNNs scoring below 0.8.
    β€’ Maintains strong performance with 50% less training data, proving efficiency.
    β€’ Excels in detecting small lakes (<0.01kmΒ²) and handling clouds and complex terrains..."
    #GIS #spatial #mapping #glaciallake #GeospatialFoundationModel #satellite #Sentinel #GaoFen #remotesensing #earthobservation #model #modeling #climatechange #glacial #glacier #melt #melting #UViT #deepleanring #AI #framework #performance #metrics #opensource

  2. Glacial Lake Mapping Using Remote Sensing Geo-Foundation Model
    --
    doi.org/10.1016/j.jag.2025.104 <-- shared paper
    --
    HIGHLIGHTS:
    β€’ Proposed U-ViT model based on Prithvi GFM for multi-sensor glacial lake mapping.
    β€’ Achieved an F1 score of 0.894 on Sentinel-1&2, surpassing CNNs scoring below 0.8.
    β€’ Maintains strong performance with 50% less training data, proving efficiency.
    β€’ Excels in detecting small lakes (<0.01kmΒ²) and handling clouds and complex terrains..."
    #GIS #spatial #mapping #glaciallake #GeospatialFoundationModel #satellite #Sentinel #GaoFen #remotesensing #earthobservation #model #modeling #climatechange #glacial #glacier #melt #melting #UViT #deepleanring #AI #framework #performance #metrics #opensource

  3. Glacial Lake Mapping Using Remote Sensing Geo-Foundation Model
    --
    doi.org/10.1016/j.jag.2025.104 <-- shared paper
    --
    HIGHLIGHTS:
    β€’ Proposed U-ViT model based on Prithvi GFM for multi-sensor glacial lake mapping.
    β€’ Achieved an F1 score of 0.894 on Sentinel-1&2, surpassing CNNs scoring below 0.8.
    β€’ Maintains strong performance with 50% less training data, proving efficiency.
    β€’ Excels in detecting small lakes (<0.01kmΒ²) and handling clouds and complex terrains..."
    #GIS #spatial #mapping #glaciallake #GeospatialFoundationModel #satellite #Sentinel #GaoFen #remotesensing #earthobservation #model #modeling #climatechange #glacial #glacier #melt #melting #UViT #deepleanring #AI #framework #performance #metrics #opensource

  4. Glacial Lake Mapping Using Remote Sensing Geo-Foundation Model
    --
    doi.org/10.1016/j.jag.2025.104 <-- shared paper
    --
    HIGHLIGHTS:
    β€’ Proposed U-ViT model based on Prithvi GFM for multi-sensor glacial lake mapping.
    β€’ Achieved an F1 score of 0.894 on Sentinel-1&2, surpassing CNNs scoring below 0.8.
    β€’ Maintains strong performance with 50% less training data, proving efficiency.
    β€’ Excels in detecting small lakes (<0.01kmΒ²) and handling clouds and complex terrains..."
    #GIS #spatial #mapping #glaciallake #GeospatialFoundationModel #satellite #Sentinel #GaoFen #remotesensing #earthobservation #model #modeling #climatechange #glacial #glacier #melt #melting #UViT #deepleanring #AI #framework #performance #metrics #opensource

  5. Glacial Lake Mapping Using Remote Sensing Geo-Foundation Model
    --
    doi.org/10.1016/j.jag.2025.104 <-- shared paper
    --
    HIGHLIGHTS:
    β€’ Proposed U-ViT model based on Prithvi GFM for multi-sensor glacial lake mapping.
    β€’ Achieved an F1 score of 0.894 on Sentinel-1&2, surpassing CNNs scoring below 0.8.
    β€’ Maintains strong performance with 50% less training data, proving efficiency.
    β€’ Excels in detecting small lakes (<0.01kmΒ²) and handling clouds and complex terrains..."