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• W2076335508 abstract "Information of crop phenology is essential for evaluating crop productivity. In a previous work, we determined phenological stages with remote sensing data using a dynamic system framework and an extended Kalman filter (EKF) approach. In this paper, we demonstrate that the particle filter is a more reliable method to infer any phenological stage compared to the EKF. The improvements achieved with this approach are discussed. In addition, this methodology enables the estimation of key cultivation dates, thus providing a practical product for many applications. The dates of some important stages, as the sowing date and the day when the crop reaches the panicle initiation stage, have been chosen to show the potential of this technique." @default.
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• W2076335508 date "2015-03-01" @default.
• W2076335508 modified "2023-09-23" @default.
• W2076335508 title "Estimation of Key Dates and Stages in Rice Crops Using Dual-Polarization SAR Time Series and a Particle Filtering Approach" @default.
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• W2076335508 doi "https://doi.org/10.1109/jstars.2014.2372898" @default.
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