Publication | Open Access
Estimation of mustard and wheat phenology using multi-date Shannon entropy and Radar Vegetation Index from polarimetric Sentinel- 1
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Citations
32
References
2021
Year
Precision AgricultureEnvironmental MonitoringEngineeringBotanyForestryAgricultural EconomicsWheat PhenologyPhenologyRandom Forest RegressionEarth ScienceRadar Vegetation IndexMulti-date Shannon EntropyShannon EntropySynthetic Aperture RadarCrop EcologyGeographyCrop Growth ModelingEarth Observation DataRadarDual-pol Shannon EntropyRemote SensingOptical Remote SensingVegetation SciencePlant Physiology
Dual-pol Shannon Entropy captures the dynamic crop growth parameters. It was used to evaluate biophysical parameters of important crops using Sentinel-1 data. Improved phenology information is vital input to crop-growth models. Mustard experienced increase as it advanced in phenology but for wheat, decreased due to absorption. A significant relationship at initial crop stages (height < 150 cm and biomass < 5 kg m−2) R2 =0.65 between Shannon Entropy (SE) and crop parameters, though less strong (R2=0.33) for entire mustard cycle and wheat (plant height < 80 cm and biomass < 6 kg m−2) was observed. The SE appeared sensitive to low-medium biomass and useful in monitoring crop phenology in low biomass and initial phenophases. The dynamic crop profile is manifested conjunctively as Radar Vegetation Index (RVI). Random Forest Regression (RFR) and Support Vector Regression (SVR) were evaluated to predict the phenophases. Phenology responses till peak/beyond were found to perform close to ground observations.
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