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In the present study, the differences in the kharif crop reflectance at varied wavelength regions and temporal SAR backscatter (at VV and VH polarizations) during different crop stages were analyzed to classify crop types in parts of Ranchi district, East India using random forest classifier. The spectral signature of crops was generated during various growth stages using temporal Sentinel-2 MSI (optical) satellite images. The temporal backscatter profile that depends on the geometric and di-electric properties of crops were studied using Sentinel-1 SAR data. The spectral profile exhibited distinctive reflectance at the NIR (0.842 lm) and SWIR (1.610 lm) wavelength regions for paddy (Oryza sativa; *0.25 at NIR, *0.27 at SWIR), maize (Zea mays; *0.24 at NIR, *0.29 at SWIR) and finger millet (Eleusine coracana, *0.26 NIR, *0.31 at SWIR) during pre-sowing season (mid-June). Similar variations in crop's reflectance at their different growth stages (vegetative to harvesting) were observed at various wavelength ranges. Further, the variations in the backscatter coefficient of different crops were observed at various growth stages depending upon the differences in sowing-harvesting periods, field conditions, geometry, and water presence in the crop field, etc. The Sentinel-1 SAR based study indicated difference in the backscatter of crops (i.e., *À18.5 dB (VH) and *À10 dB (VV) for paddy, *À14 dB (VH) and *À7.5 dB (VV) for maize, *À14.5 dB and *À8 dB (VV) for finger millet) during late-July (transplantation for paddy; early vegetative for maize and finger millet). These variations in the reflectance and backscatter values during various stages were used to deduce the best combination of the optical and SAR layers in order to classify each crop precisely. The GLCM texture analysis was performed on SAR for better classification of crop fields with higher accuracies. The SAR-MSI based kharif crop assessment (2017) indicated that the total cropped area under paddy, maize and finger millet was 24,544.55, 1468.28 and 632.48 ha, respectively. The result was validated with ground observations, which indicated an overall accuracy of 83.87% and kappa coefficient of 0.78. The high temporal, spatial spectral agility of Sentinel satellite are highly suitable for kharif crop monitoring. The study signifies the role of combined SAR-MSI technology for accurate mapping and monitoring of kharif crops.

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The sensitivity of dual-polarized Sentinel-1 backscatter towards biophysical parameters (height and biomass) of wheat and mustard crops was investigated. The plant height and biomass observations categorized into three groups were useful in understanding the sensitivity across a particular biomass and height range whose significance was determined using a statistical measure (student's ttest). The crop parameters were retrieved only for the C-band sensitive biomass (< 5 kg m −2) and height (< 160 cm for mustard and < 80 cm for wheat) range considering the saturation of signals at advanced crop stages and based on the detailed investigation. The sensitivity towards the mustard plant height becomes very weak as the crop proceeds to a height > 190 cm. A low RMSE (11.50 cm) was observed when the retrieval was done for height < 160 cm. The cross-polarized responses were more sensitive to crop biomass than co-polarized responses mainly due to the dominant depolarization of the transmitted power. An early saturation was found at co-polarized V V (4 kg m −2) as compared to cross-polarized V H (6 kg m −2) particularly for planophiles like mustard and little later in the case of erectophile such as wheat. The backscatter response was found to be sensitive at early crop stages for both the crop geometry, and hence retrieval of biophysical parameters at these stages can yield better accuracy than the overall retrieval. The retrieval of wheat height resulted in a low RMSE of 9.25 cm when the retrieval was carried out for crop height < 80 cm. Retrieval was attempted using the simplistic logarithmic model which can find ways in the operational application using wide swath dual-polarized datasets.