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Selection of the Optimal Spectral Resolution for the Cadmium-Lead Cross Contamination Diagnosing Based on the Hyperspectral Reflectance of Rice Canopy

机译：基于水稻冠层高光谱反射的镉引出交叉污染诊断的最佳光谱分辨率的选择

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摘要

This paper proposed an optimal spectral resolution for diagnosing cadmium-lead (Cd-Pb) cross contamination with different pollution levels based on the hyperspectral reflectance of rice canopy. Feature bands were sequentially selected by two-way analysis of variance (ANOVA2) and random forests from the high-dimensional hyperspectral data after preprocessing. Then Support Vector Machine (SVM) was applied to diagnose the pollution levels using different feature bands combination with different spectral resolutions and cross validation was conducted to evaluate the distinguishing accuracies. Finally, the optimal spectral resolution could be determined by comparing the diagnosing accuracies of the optimal feature bands combination in each spectral resolution. In the experiments, the hyperspectral reflectance data of rice canopy with ten different spectral resolutions was captured, covering 16 pretreatments of Cd and Pb pollution. The experimental results showed the optimal spectral resolution was 9 nm with the highest average accuracy of 0.71 and relatively standard deviation of 0.07 for diagnosing the categories and levels of Cd-Pb cross contamination. The useful exploration provided an evidence for optimal spectral resolution selection to reduce the cost of heavy metal pollution diagnose.
机译：本文提出了一种最佳的光谱分辨率，用于基于水稻冠层的高光谱反射率与不同污染水平的镉引线（CD-PB）交叉污染。通过在预处理之后通过从高维超光谱数据的双向分析（ANOVA2）和随机林的双向分析顺序选择特征频带。然后，使用支持向量机（SVM）来使用不同的特征频带与不同光谱分辨率的组合诊断污染水平，并进行交叉验证以评估区别的精度。最后，可以通过比较每个光谱分辨率在每个光谱分辨率中的最佳特征频带组合的诊断精度来确定最佳光谱分辨率。在实验中，捕获了大米冠层的高光谱反射数据，具有十种不同的光谱分辨率，涵盖了16个CD和PB污染的预处理。实验结果表明，最佳光谱分辨率为9nm，平均精度为0.71，相对标准偏差为0.07，用于诊断CD-PB交叉污染的类别和水平。有用的探索提供了最佳光谱分辨率选择的证据，以降低重金属污染诊断的成本。

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