Abstract Dune crestlines encode sediment transport dynamics and atmospheric forcing, yet their large‐scale quantification has been constrained by labor‐intensive mapping or limited resolution. Here we develop an attention‐augmented U‐Net model to automatically extract crestlines from ∼1 m resolution satellite imagery. Trained on 17,798 manually annotated crestlines, the model maps over 4 million crest features across the Badain Jaran and Tengger Deserts, yielding an unprecedented high‐resolution data set of dune‐field organization. Integrating ERA5‐Land wind reanalysis and Copernicus digital elevation model‐derived equivalent sand thickness, we quantify spatial variations in crest orientation, spacing, sinuosity, and hierarchy with respect to boundary conditions. Crest orientations largely agree with predictions from the bed‐instability mode under sand‐covered conditions, while deviations near upwind margins and transport corridors indicate elongation‐mode preference under sand‐starved bed. A downwind reduction in orientation dispersion and sinuosity reveals system‐scale reorganization driven by directional filtering through a narrow transport corridor, highlighting coupled wind‐sediment controls on self‐organized dune fields.