激光与光电子学进展, 2019, 56 (5): 051101, 网络出版: 2019-07-31   

基于CWT的人类不同程度干扰下干旱区土壤有机质含量估算研究 下载: 1051次

CWT-Based Estimation of Soil Organic Matter Content in Arid Area Under Different Human Disturbance Degrees
作者单位
1 新疆大学资源与环境科学学院/教育部绿洲生态重点实验室, 新疆 乌鲁木齐 830046
2 北京联合大学应用文理学院城市系, 北京 100083
摘要
为了研究人类干扰活动对土壤有机质含量的影响以及提高干旱区土壤有机质估算精度,以新疆北部阜康市的土壤为研究对象,对90个采样点的高光谱曲线分别进行连续小波变换(CWT),并与两种常用光谱变换R′、lg(1/R)进行对比。结果表明,随着人类干扰程度的增加,土壤有机质的空间变异性随之增强;常用光谱变换中,Ⅰ、Ⅱ、Ⅲ区R′与土壤有机质所建立的偏最小二乘决定系数模型R2均高于R、lg(1/R);经过CWT变换后所建模型精度更高,验证模型精度R2分别为0.717、0.689、0.630,与R所建模型的R2相比最大分别提高了0.382、0.4、0.389,且相对分析误差分别达到2.150、2.090、2.013,均能很好地预测土壤有机质含量,说明利用CWT不会因人类干扰程度的提高而使模型精度大幅度降低,更加适用于干旱区有机质含量的预测。
Abstract
In order to explore the influence of human disturbance activities on soil organic matter content and improve the estimation accuracy of soil organic matter in arid area. The soil in Fukang City, northern Xinjiang, is studied. The hyperspectral curves of 90 sampling points are successively transformed by continuous wavelet transform (CWT) and compared with R′and lg(1/R), two common spectral transformation methods. The results show that the spatial variability of soil organic matter is enhanced with the increase of human disturbance degree. Moreover, in the common spectral transformation methods, R2 of partial least squares models established by the soil organic matter institute and R′ in zone I, zone II and zone III are both higher than those by R and lg(1/R). The precision of the model established after CWT is very high. Compared with R2 of the model established by R, R2 of the measured value and the predicted value are 0.717, 0.689, 0.630, increased by 0.382, 0.4, 0.389, respectively. In addition, the relative percent deviation correspondingly reach 2.150, 2.090, 2.013, indicating that CWT can well predict the soil organic matter contents. The usage of CWT does not greatly reduce the model accuracy with the increase of human disturbance degree and is more suitable for the prediction of organic matter content in arid regions.

叶红云, 熊黑钢, 张芳, 王宁, 马利芳. 基于CWT的人类不同程度干扰下干旱区土壤有机质含量估算研究[J]. 激光与光电子学进展, 2019, 56(5): 051101. Hongyun Ye, Heigang Xiong, Fang Zhang, Ning Wang, Lifang Ma. CWT-Based Estimation of Soil Organic Matter Content in Arid Area Under Different Human Disturbance Degrees[J]. Laser & Optoelectronics Progress, 2019, 56(5): 051101.

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