Abstract

ABSTRACTThe utility of time series polarimetric C-band data for vegetation state monitoring was explored to understand the mechanism of growth and phenology for important winter crops in India. Parameters investigated were HH–VV phase difference (co-polarization phase difference, PPD), amplitude ratio, and polarization indices. Data were acquired during the entire growth phase categorized as early, mid/peak vegetative, and post-vegetative /flowering phase. The trend emerging in this study showed a shift in the phase difference distribution for agricultural areas relating to the growth rate for various crops. The time series data set revealed that the PPD is a function of frequency and was directly affected by crop type (planophile or erectophile), vigour, structure, and crop biophysical parameters, particularly biomass. The behaviour of crop biomass with PPD responded differentially across crop architectures and vigour classes. Co-polarization index was found to be a good measure for discrimination in early growth stages while cross-polarization index suited in advanced vegetative stages where geometrical orientation was uniform. The PPD captured the change in frequency distribution resulting in a peaked distribution at sowing changing to smooth, well-spread frequency distribution as the peak vegetation stage approaches. This histogram nature is observed to be gradual for high-biomass crops and peaked in case of the low-biomass crops. It is indicative of the rate of growth; a low peaked normal curve indicates faster growth rate and resulting in high biomass. The amplitude ratio in the later phase of growth as on the third date is similarly altered as in the VV returns from the crop. Intuition of the rate of growth and plant vigour is obtained from the temporal PPD pattern. The current study shows that while phase differences and amplitude ratio carry little information content on a single resolution cell basis, their spatial distribution over a wider time span can be used to derive quantitative relationships between SAR response and crop condition. The synergy of information involving the above parameters were used to derive useful information on the vegetation.

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