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首页> 外文会议>IEEE International Geoscience and Remote Sensing Symposium >LAI Retrieval of Winter Wheat using Simulated Compact SAR Data through GA-PLS Modeling
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LAI Retrieval of Winter Wheat using Simulated Compact SAR Data through GA-PLS Modeling

机译：GA-PLS建模的紧凑型SAR数据反演冬小麦的LAI

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摘要

This study evaluated the potential of a compact polarimetric (CP) mode SAR concept for the retrieval of winter wheat LAI values. First, the CP SAR data used in this study were simulated from full polarimetric SAR data. A total of 19 CP parameters were extracted from CP matrices and from CP decomposition results. Second, a hybrid inversion model based on nonlinear genetic partial least square (GA-PLS) algorithm was built to determine the relationships between CP SAR parameters and LAI values. Finally, the mapping and estimation of winter wheat LAI using the CP SAR parameters by GA-PLS algorithm were implemented. Our study indicates that by using a CP SAR dataset, LAI retrieval can yield an accuracy of R2=0.70 and RMSE = 0.40 m2/m2. Our study has significant implications for field crop condition monitoring and growth stage estimation, providing relevant data for agronomic practices and precision agriculture.
机译：这项研究评估了紧凑极化（CP）模式SAR概念在检索冬小麦LAI值方面的潜力。首先，从全极化SAR数据模拟了本研究中使用的CP SAR数据。从CP矩阵和CP分解结果中总共提取了19个CP参数。其次，建立了基于非线性遗传最小二乘算法的混合反演模型，确定了CP SAR参数与LAI值之间的关系。最后，利用GA-PLS算法利用CP SAR参数进行了冬小麦LAI的定位和估计。我们的研究表明，通过使用CP SAR数据集，LAI检索可以产生R的精度 2 = 0.70和RMSE = 0.40 m 2 /米 2 。我们的研究对田间作物状况监测和生育期估算具有重要意义，可为农艺实践和精准农业提供相关数据。

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