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Optimization of dual-polarized bistatic specular scatterometer for studying microwave scattering response and vegetation growth parameters retrieval of paddy crop using a machine learning algorithm

机译:用机器学习算法研究微波散射响应和植被生长参数检索微波散射响应和植被生长参数的优化

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摘要

Bistatic specular (Bi-spec) scatterometer measurement system was indigenously designed at X- and C-bands in the incidence angular range from 20 degrees to 60 degrees at the interval of 10 degrees to study the scattering mechanism of vegetation growth parameters of paddy crop and their retrieval at HH and VV polarizations using machine learning algorithms. The contributions of coherent and incoherent scattering to the total reflected or scattered power was measured by the bi-spec scatterometer system to derive bi-spec scattering coefficient(sigma(0)). The effect of vegetation growth parameters such as leaf area index (LAI), plant height (PH), vegetation water content (VWC) and fresh biomass (FBm) on the sigma(0)was investigated. The values of sigma(0)(HH) at C-band were observed to be higher at HH-polarization as compared to 4-Hat X-band for all specular incidence angles due to higher penetrating ability than the X-band. An approach was made to find out the optimum parameters of the bi-spec scatterometer system by correlation analysis between the computed sigma(0)and vegetation growth parameters of paddy crop and their retrieval by the SVR model using linear, polynomial and radial kernels. The optimum parameters of the bi-spec scatterometer system for the retrieval of LAI, FBm and VWC of paddy crop were found to be HH polarization, 40 degrees angle of incidence at C-band. While, for PH retrieval, the optimum parameters were found to be VV polarization, 40 degrees angle of incidence at X band. The potential of the developed SVR model was evaluated by computing centered root mean square error (CRMSE), standard deviation (SD) and correlation coefficient (R) between estimated and observed vegetation growth parameters. The retrieval of the vegetation growth parameters of paddy crop by the developed SVR model using radial kernel provided better results in comparison to linear and polynomial kernels for LAI, FBm and VWC at C-band and PH at X-band using bi-spec scatterometer data.
机译:双面镜面(Bi-Spec)散射仪测量系统在入射角的X-和C波段处,在10度的间隔下在20度到60度的X和C波段下设计,以研究稻田植被生长参数的散射机制和使用机器学习算法在HH和VV偏振中检索。通过双规范散射仪系统测量相干和非相干散射到总反射或散射功率的贡献,以导出双规范散射系数(Sigma(0))。研究了叶片区域指数(LAI),植物高度(pH),植被水含量(VWC)和新鲜生物量(FBM)的植被生长参数等植被生长参数进行了σ(0)。与4帽X波段相比,在HH偏振中观察到在HH偏振的σ(0)(HH)的值,与X波段更高的渗透能力,与所有镜面入射角相比。通过使用线性,多项式和径向核的SVR模型来通过相关性分析来了解双规范散射仪系统的最佳参数。使用线性,多项式和径向核。发现荔枝,FBM和VWC检索的双规范散射仪系统的最佳参数是HH偏振,C波段的40度入射角。虽然对于pH检索,发现最佳参数是VV偏振,X波段的40度入射角。通过计算以估计和观察到的植被生长参数之间的中心均方误差(CRMSE),标准偏差(SD)和相关系数(R)计算所开发的SVR模型的电位。通过径向核的开发SVR模型检索稻田作物的植被生长参数提供更好的结果与使用Bi-Spec散射计数据的C频带和PH的C波段,FBM和VWC的线性和多项式内核相比。

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