CHARACTERIZATION OF LAND COVER SEASONALITY IN SENTINEL-1 TIME SERIES DATA

15 citations as recorded by crossref.

1. An Unsupervised Clustering Technique for Dual-Pol Sentinel-1 SLC and GRD SAR Data A. Verma et al. https://doi.org/10.1109/TGRS.2025.3589724
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3. Accounting for Deciduous Forest Structure and Viewing Geometry Effects Improves Sentinel-1 Time Series Image Consistency M. Zehner et al. https://doi.org/10.1109/TGRS.2023.3310113
4. Characterizing Spatial Variability of Soil Organic Carbon Through Improved Machine-Learning Modeling With In Situ Data Resampling: A Case Study in Alaska W. Peng et al. https://doi.org/10.1109/TGRS.2025.3572344
5. Potential of Sentinel-1 SAR to Assess Damage in Drought-Affected Temperate Deciduous Broadleaf Forests K. Schellenberg et al. https://doi.org/10.3390/rs15041004
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9. Sentinel-1 Backscatter Time Series for Characterization of Evapotranspiration Dynamics over Temperate Coniferous Forests M. Mueller et al. https://doi.org/10.3390/rs14246384
10. Sensitivity of Sentinel-1 Backscatter to Management-Related Disturbances in Temperate Forests S. van der Woude et al. https://doi.org/10.3390/rs16091553
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13. Exploring the Relationship Between Time Series of Sentinel-1 Interferometric Coherence Data and Wild Edible Mushroom Yields in Mediterranean Forests R. Martínez-Rodrigo et al. https://doi.org/10.1007/s41651-024-00199-9
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15. Seasonality and directionality effects on radar backscatter are key to identify mountain forest types with Sentinel-1 data I. Borlaf-Mena et al. https://doi.org/10.1016/j.rse.2023.113728