Compact Polarimetric Response of Rape (Brassica napus L.) at C-Band: Analysis and Growth Parameters Inversion

Abstract

Growth parameters like biomass, leaf area index (LAI) and stem height play an import role for crop monitoring and yield prediction. Compact polarimetric (CP) SAR has shown great potential and similar performance to fully-polarimetric (FP) SAR in crop mapping and phenology retrieval, but its potential in growth parameters inversion has not been fully explored. In this paper, a time series of images of CP SAR was simulated from five FP SAR data gathered during the entire growth season of rape. CP response of 27 parameters, relying on Stokes parameters and their child parameters, decomposition parameters and backscattering coefficients, were extracted and investigated as a function of days after sowing (DAS) during the whole rape growth cycle to interpret their sensitivity to each growth parameter. Then, random forest (RF) was chosen as an automatic approach for the growth parameters inversion method, and its results were compared with traditional single-parameter regression models. Most of the CP parameters showed high sensitivity with growth parameters and great potential for growth parameters inversion. Among all of the regression models, the quadratic regression model showed the best performance for all of the growth parameters inversion, the best result for biomass inversion was the third component of the Stokes parameters (g 3 ) with R 2 of 0.765 and RMSE of 73.20 g/m 2 . For LAI and stem height was one of the Stokes child parameters, the circular polarization ratio (U c ), with R 2 of 0.857 and 0.923 and RMSE of 0.66 and 18.71 cm, respectively. RF showed the highest accuracy and smallest RMSE for all of three growth parameters inversion; R 2 for biomass, LAI and stem height were 0.93, 0.96 and 0.95, respectively; RMSE were 46.24 g/m 2 , 0.25 and 13.5 cm, respectively. However, there are also some CP parameters, which showed low sensitivity to growth parameters, that had high importance for RF inversion. The results confirmed the potential of CP data and the RF method in growth parameters inversion, but they also confirmed that it was difficult to give a physical interpretation for the RF inversion model.

Compatibilization of biocomposites based on sponge‐gourd natural fiber reinforced poly(lactic acid)

“…Additionally, luffa fibers contribute in decreasing the PLA stability in reason of the degrading effect originated by the residue resulting from their combustion. Analogous results were found by Zhang et al [36] while studying PLA/wood fiber composites.…”

Improving Aboveground Biomass Estimation of Pinus densata Forests in Yunnan Using Landsat 8 Imagery by Incorporating Age Dummy Variable and Method Comparison

“…However, the model structures derived from these algorithms are often difficult to interpret [9,19,32]. The RF, introduced by Leo Breiman [43], can be used for either classifying categorical variables or estimating continuous variables such as forest AGB [43,44]. It provides the average prediction from a number of regression models created by a subset of training data selected randomly with a random subset of predictors [45,46].…”

Mid-season Crop Classification Using Dual-, Compact-, and Full-Polarization in Preparation for the Radarsat Constellation Mission (RCM)

“…This is particularly true for S 3 , as it was among the top-five most important CP SAR features. This finding is potentially explained by the fact that S 3 is highly sensitive to the crop biomass, as [26] reported the best result for biomass inversion with S 3 among all other CP SAR features.…”

“…The Stokes vector parameters can be used to extract the Stokes child features (see Table 2). Degree of polarization represents the state of polarization [4] with values approaching 0 and 1 correspond to depolarized and purely polarized wave, respectively [26]. Relative phase (δ) ranges between −180 • and 180 • [12] and indicates that whether the surface (δ > 0) or double-bounce (δ < 0) scattering is dominant [27].…”