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RSS FeedsRemote Sensing, Vol. 14, Pages 546: Spatio-Temporal Estimation of Rice Height Using Time Series Sentinel-1 Images (Remote Sensing)

 
 

24 january 2022 11:09:29

 
Remote Sensing, Vol. 14, Pages 546: Spatio-Temporal Estimation of Rice Height Using Time Series Sentinel-1 Images (Remote Sensing)
 


Rice height, as the fundamental biophysical attribute, is a controlling factor in crop phenology estimation and yield estimation. The aim of this study was to use time series Sentinel-1A images to estimate the spatio-temporal distribution of rice height. In this study, a particle filter (PF) was applied for the real-time estimation of rice height compared with a simplified water cloud model (SWCM) on the basis of rice mapping and transplanting date. It was found that the VH backscatter (σvho) can potentially be applied to accurately estimate rice height compared with VV backscatter (σvvo), the σvho/σvv0 ratio, and the Radar Vegetation Index (RVI, 4* σvho/(σvho+σvvo)). The results show that the rice height estimation by PF generated a better result with a root-mean-square error (RMSE) equal to 7.36 cm and a determination factor (R2) of 0.95 compared with SWCM (RMSE = 12.59 cm and R2 = 0.86). Moreover, rice height in the south and east of the study area was higher than in the north and west. The reason for this is that the south and east are near to the South China Sea, and there are higher temperatures and earlier transplanting. Altogether, our results demonstrate the potential of PF and σvho to study the spatio-temporal distribution of crop height estimation. As a result, the PF method can contribute greatly to improvements in crop monitoring.


 
75 viewsCategory: Geology, Physics
 
Remote Sensing, Vol. 14, Pages 545: Remote Sensing Scene Image Classification Based on Self-Compensating Convolution Neural Network (Remote Sensing)
Remote Sensing, Vol. 14, Pages 548: Radiative Transfer Image Simulation Using L-System Modeled Strawberry Canopies (Remote Sensing)
 
 
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