张永鑫, 张王菲, 徐昆鹏, 李建刚. 利用典型Stokes参数的油菜物候期识别[J]. 武汉大学学报 ( 信息科学版), 2023, 48(8): 1322-1330. DOI: 10.13203/j.whugis20210394
引用本文: 张永鑫, 张王菲, 徐昆鹏, 李建刚. 利用典型Stokes参数的油菜物候期识别[J]. 武汉大学学报 ( 信息科学版), 2023, 48(8): 1322-1330. DOI: 10.13203/j.whugis20210394
ZHANG Yongxin, ZHANG Wangfei, XU Kunpeng, LI Jiangang. Phenological Phase Identification of Oilseed Rape (Brassica napus L.) Using Typical Stokes Parameters[J]. Geomatics and Information Science of Wuhan University, 2023, 48(8): 1322-1330. DOI: 10.13203/j.whugis20210394
Citation: ZHANG Yongxin, ZHANG Wangfei, XU Kunpeng, LI Jiangang. Phenological Phase Identification of Oilseed Rape (Brassica napus L.) Using Typical Stokes Parameters[J]. Geomatics and Information Science of Wuhan University, 2023, 48(8): 1322-1330. DOI: 10.13203/j.whugis20210394

利用典型Stokes参数的油菜物候期识别

Phenological Phase Identification of Oilseed Rape (Brassica napus L.) Using Typical Stokes Parameters

  • 摘要: 油菜关键物候期信息的获取对于油菜的田间管理、观赏时间预测及产量估测等具有重要意义,是精准农业实施的重要组成部分。极化合成孔径雷达技术不仅可以实现对作物全天时监测,而且对作物的结构信息敏感,在物候期提取中极具潜力。首先,以覆盖油菜整个生长期的5景时间序列全极化Radarsat-2数据为基础,基于Stokes矢量提取了平均强度 g_0 、归一化平均强度 g_0m 、平均极化度 \rho _m 、零度方向路线球面度 P_\mathrmd\mathrmo\mathrmr 、零度孔径路线倾斜度 I_\mathrmd\mathrma\mathrmp 和零度孔径路线弧对称度 A_\mathrma\mathrmd\mathrma\mathrmp 6个典型Stokes参数;然后,对比分析了这6个参数对油菜整个生长期动态变化的响应特征, 并以此为基础采用决策树(decision tree,DT)算法对油菜的物候期进行了识别。研究结果表明, 6个Stokes参数中,除 \rho _m 和 A_\mathrma\mathrmd\mathrma\mathrmp 外,其他4个参数均对油菜物候期变化敏感,在油菜物候期识别中具有极大的潜力。DT算法能有效识别油菜的各关键物候期,其分类结果与样地实测数据具有良好的一致性,总体分类精度为87.4%;在单个物候期的识别中,识别精度最高达到了94.3%。

     

    Abstract:
      Objectives  The key phenological information of oilseed rapeseed (Brassica napus L.) plays an important role in field management, viewing time prediction and yield estimation of the oilseed rape. It is also an important part of precision agriculture. Polarimetric synthetic aperture radar technology shows great potential in phenological phase identification with its all-weather monitoring capability and its sensitivity to the crop structural information.
      Methods  First, we identified the 5 phenological phases of the oilseed rape on the test area with 5 time series full-polarization Radarsat-2 data, which covers the whole growth period of the oilseed rape. 6 typical Stokes parameters are extracted and applied in the identification of oilseed rape phenological phases, the extracted Stokes parameters includ averaged intensity( g_0 ), normalized average intensity( g_0m ), averaged degree of polarization( \rho _m ), perimeter degree of zero orientation route( P_\mathrmd\mathrmo\mathrmr ), inclination degree of zero aperture route( I_\mathrmd\mathrma\mathrmp ), and arc asymmetry degree of zero aperture route( A_\mathrma\mathrmd\mathrma\mathrmp ). Then, The phenological phases of oilseed rape is identified by the decision tree (DT) algorithm based on the comparative analysis of the dynamic response of the 6 special Stokes parameters to rape growth stages.
      Results and Conclusions  Among the extracted Stokes parameters applied in this study, except \rho _m and A_\mathrma\mathrmd\mathrma\mathrmp , other parameters show great sensitivity to the change of the oilseed rape phenological phases. The DT algorithm also perform well in the classification of the oilseed rape phenological phases. The classification results agree well with the field measured samples, and the overall classification accuracy is 87.4%, while the highest classification accuracy of each phenological phase is 94.3%.

     

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