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Monitoring total nitrogen content in soil of cultivated land based on hyperspectral technology

机译:基于高光谱技术的耕地土壤总氮含量监测

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Monitoring total nitrogen content (TNC) in soil of cultivated land quantitively is significant for fertility adjustment, yield improvement and sustainable development of agriculture. Analyzing the hyperspectrum response on soil TNC is the basis of remote sensing monitoring in a wide range. The study aimed to develop a universal method to monitor total nitrogen content in soil of cultivated land by hyperspectrum data. The correlations between soil TNC and the hyperspectrum reflectivity and its mathematical transformations were analyzed. Then the feature bands and its transformations were screened to develop the optimizing model of monitoring soil TNC based on the method of multiple linear regression. Results showed that the bands with good correlation of soil TNC were concentrated in visible bands and near infrared bands. Differential transformation was helpful for reducing the noise interference to the diagnosis ability of the target spectrum. The determination coefficient of the first order differential of logarithmic reciprocal transformation was biggest (0.56), which was confirmed as the optimal inversion model for soil TNC. The determination coefficient (R~2) of testing samples was 0.45, while the RMSE was 0.097 mg/kg. It indicated that the inversion model of soil TNC in the cultivated land with the one differentiation of logarithmic reciprocal transformation of hyperspectral data could reach high accuracy with good stability.
机译:定量监测耕地土壤中的总氮含量(TNC)对于肥力调整,产量提高和农业可持续发展具有重要意义。分析土壤TNC的高光谱响应是广泛遥感监测的基础。该研究旨在开发一种通过高光谱数据监测耕地土壤中总氮含量的通用方法。分析了土壤TNC与高光谱反射率之间的相关性及其数学转换。然后通过多元线性回归的方法筛选特征带及其变换,建立土壤TNC监测的优化模型。结果表明,与土壤TNC具有良好相关性的波段集中在可见波段和近红外波段。微分变换有助于减少噪声对目标光谱诊断能力的干扰。对数倒数转换的一阶微分的确定系数最大(0.56),被确认为土壤TNC的最佳反演模型。测试样品的测定系数(R〜2)为0.45,而RMSE为0.097 mg / kg。结果表明,耕地土壤TNC的反演模型具有高光谱数据对数倒数转换的一种区别,可以达到较高的精度和稳定性。

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