Role of Polarimetric SAR data for discrimination/biophysical parameters of crops based on canopy architecture

11 citations as recorded by crossref.

1. A SAR-Driven Approach for Winter Catch Crop Classification in Germany S. Selvaraj et al. https://doi.org/10.1109/ACCESS.2025.3615739
2. Evaluating the spatio-temporal transferability of multi-regional models for winter catch crop classification using Sentinel-1 and Sentinel-2 time series S. Selvaraj et al. https://doi.org/10.1016/j.rsase.2026.102107
3. Analyzing Temporal Characteristics of Winter Catch Crops Using Sentinel-1 Time Series S. Selvaraj et al. https://doi.org/10.3390/rs16193737
4. An eigenvalue decomposition based full polarimetric SAR framework for leaf area index retrieval using entropy-anisotropy features A. Mukhopadhyay et al. https://doi.org/10.1080/10106049.2026.2709708
5. A Preliminary Investigation of the Potential of Sentinel-1 Radar to Estimate Pasture Biomass in a Grazed Pasture Landscape R. Crabbe et al. https://doi.org/10.3390/rs11070872
6. Biophysical parameter assessment of winter crops using polarimetric variables—entropy (H), anisotropy (A), and alpha (α) D. Haldar et al. https://doi.org/10.1007/s12517-019-4516-8
7. Estimation of mustard and wheat phenology using multi-date Shannon entropy and Radar Vegetation Index from polarimetric Sentinel- 1 D. Haldar et al. https://doi.org/10.1080/10106049.2021.1926554
8. Condition assessment of pearl millet/ bajra crop in different vigour zones using Radar Vegetation Index S. Selvaraj et al. https://doi.org/10.1007/s41324-021-00380-y
9. Radar Vegetation Index for assessing cotton crop condition using RISAT-1 data D. Haldar et al. https://doi.org/10.1080/10106049.2018.1516249
10. Discrimination of maize crop in a mixed Kharif crop scenario with synergism of multiparametric SAR and optical data S. Elango et al. https://doi.org/10.1080/10106049.2021.1920628
11. Pearl Millet Crop Biophysical Parameter Retrieval From Space Borne Polarimetric SAR Data Using Machine Learning D. Thulasiraman et al. https://doi.org/10.1029/2022EA002799