首页> 外文期刊>Catena: An Interdisciplinary Journal of Soil Science Hydrology-Geomorphology Focusing on Geoecology and Landscape Evolution >Study on a fast EC measurement method of soda saline-alkali soil based on wavelet decomposition texture feature
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Study on a fast EC measurement method of soda saline-alkali soil based on wavelet decomposition texture feature

机译:基于小波分解纹理特征的苏打盐碱土快速EC测量方法研究

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摘要

Wavelet texture features can well describe the cracking of salt-affected clayey soils on different decomposition scales since the desiccation cracking is considered as a common phenomenon and mainly determined by the salt content. To establish the relationship between wavelet texture features and the salinity of soda saline-alkali soils, 200 soil samples were selected in Songnen Plain of China and the crack images of the samples were processed uniformly. The 4-levels orthogonal wavelet decompositions were performed based on coiflet-1 wavelet basis function using the grayscale images. After that, correlation analysis was carried out between electrical conductivity (EC) and wavelet texture features (energy and L1 norm) under different decomposition levels. The results indicate that the poor relationship between low-frequency texture features and EC is hardly affected by the decomposition levels, but the correlation coefficients between high-frequency wavelet texture features and EC of soil samples increases significantly with decomposition levels. Besides, 100 calibration samples were used to establish the regression models and the results show that both energy and L1 norm are exponentially correlated with EC of soil samples especially for those from 90 degrees high-frequency decomposition results with R-2 of the exponential models of 0.90 and 0.84. A fast EC measurement method for predicting soil EC was then proposed and verified by the other 100 soil samples. The fitting results show very high prediction accuracy when EC was calculated by the energy from 90 degrees with R-2 of 0.91 and ratio of performance to deviation (RPD) of 4.73 and L1 norm from 90 degrees with R-2 of 0.85 and RPD of 3.53. Moreover, the fitting results based on the mean texture features calculated from 0 degrees, 90 degrees and 135 degrees high-frequency decomposition results are also relatively good (R-2 of 0.88 and RPD of 4.13 for energy, R-2 of 0.81 and RPD of 3.36 for L1 norm).
机译:由于干化开裂是一种常见现象,主要由含盐量决定,因此小波纹理特征可以很好地描述不同分解尺度下盐渍粘性土的开裂。为了建立小波纹理特征与苏打盐碱土盐分之间的关系,在松嫩平原选取了200个土壤样品,对样品的裂缝图像进行了均匀处理。基于coiflet-1小波基函数,对灰度图像进行四级正交小波分解。然后,在不同分解水平下,对电导率(EC)和小波纹理特征(能量和L1范数)进行相关分析。结果表明,分解水平对低频纹理特征与EC的相关性影响不大,但高频小波纹理特征与土壤样本EC的相关系数随分解水平的增加而显著增加。此外,使用100个校准样本建立回归模型,结果表明,能量和L1范数均与土壤样本的EC呈指数相关,尤其是90度高频分解结果,指数模型的R-2分别为0.90和0.84。提出了一种预测土壤EC的快速EC测量方法,并用其他100个土壤样本进行了验证。拟合结果表明,当使用90度的能量(R-2为0.91)、性能偏差比(RPD)为4.73以及90度的L1范数(R-2为0.85、RPD为3.53)计算EC时,预测精度非常高。此外,基于0度、90度和135度高频分解结果计算的平均纹理特征的拟合结果也相对较好(能量的R-2为0.88,RPD为4.13,L1范数的R-2为0.81,RPD为3.36)。

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