repoGitHubTrust 82 · PrimaryPublished 1mo agoLive · 25d ago
Climate-Vision/ClimateVision
Open-source ML platform for detecting deforestation, ice melt, and flooding from Sentinel-2 / Landsat imagery.
Lineage graph
Paper → model → repo connections mined from source citations (Tier-1 exact match).
Why these links exist
Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- PossiblePossibly related (embedding) · 60%High-Resolution Flood Mapping With Sentinel-1 and Sentinel-2 via Misalignment-Robust Cross-Sensor Learning and Generative Despeckling →
- PossiblePossibly related (embedding) · 57%AI Can Help Track the World’s Shrinking Glaciers →
- PossiblePossibly related (embedding) · 48%FLORA: A deep learning approach to predict forest attributes from heterogeneous LiDAR data →
- PossiblePossibly related (embedding) · 46%TreeAgent: A Generalizable Multi-Agent Framework for Automated Bias Labeling in Forestry via Compiled Expert Rules and Vision-Language Models →
- PossiblePossibly related (embedding) · 45%MonoIR-RS: Infrared Remote Sensing Vision-Language Learning with CLIP and VLM Adaptation →
- PossiblePossibly related (embedding) · 58%Weakly Supervised Spatio-Temporal Candidate Discovery of Dairy Farm Sites from Seasonal Satellite Imagery →
- PossiblePossibly related (embedding) · 54%Regional drought prediction from Sentinel-2 time series using Random Forest, DNN, and 1D-CNN: a case study in Marchfeld, Austria - EurekAlert! →
Implements
paperHigh-Resolution Flood Mapping With Sentinel-1 and Sentinel-2 via Misalignment-Robust Cross-Sensor Learning and Generative DespecklingpaperFLORA: A deep learning approach to predict forest attributes from heterogeneous LiDAR datapaperTreeAgent: A Generalizable Multi-Agent Framework for Automated Bias Labeling in Forestry via Compiled Expert Rules and Vision-Language Models
Covers
Implements (incoming)
Covers (incoming)
Related across the graph
paperHigh-Resolution Flood Mapping With Sentinel-1 and Sentinel-2 via Misalignment-Robust Cross-Sensor Learning and Generative DespecklingpaperFLORA: A deep learning approach to predict forest attributes from heterogeneous LiDAR datapaperWeakly Supervised Spatio-Temporal Candidate Discovery of Dairy Farm Sites from Seasonal Satellite ImagerypaperMonoIR-RS: Infrared Remote Sensing Vision-Language Learning with CLIP and VLM AdaptationnewsAI Can Help Track the World’s Shrinking GlacierspaperTreeAgent: A Generalizable Multi-Agent Framework for Automated Bias Labeling in Forestry via Compiled Expert Rules and Vision-Language ModelsnewsRegional drought prediction from Sentinel-2 time series using Random Forest, DNN, and 1D-CNN: a case study in Marchfeld, Austria - EurekAlert!