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首页> 美国卫生研究院文献>Sensors (Basel Switzerland) >Selection of the Optimal Spectral Resolution for the Cadmium-Lead Cross Contamination Diagnosing Based on the Hyperspectral Reflectance of Rice Canopy
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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率的镉铅交叉污染诊断的最佳光谱分辨率选择

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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：本文基于水稻冠层的高光谱反射率，提出了一种用于诊断不同污染水平的镉-铅（Cd-Pb）交叉污染的最佳光谱分辨率。预处理后，通过二维方差分析（ANOVA2）和随机森林从高维高光谱数据中依次选择特征带。然后应用支持向量机（SVM），使用不同特征带和不同光谱分辨率，对污染水平进行诊断，并进行交叉验证以评估区别精度。最后，可以通过比较每个光谱分辨率中最佳特征带组合的诊断准确性来确定最佳光谱分辨率。在实验中，捕获了具有十种不同光谱分辨率的水稻冠层的高光谱反射数据，涵盖了对Cd和Pb污染的16种预处理。实验结果表明，用于诊断Cd-Pb交叉污染的类别和水平的最佳光谱分辨率为9 nm，最高平均准确度为0.71，相对标准偏差为0.07。有益的探索为选择最佳光谱分辨率以降低重金属污染诊断成本提供了证据。

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