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Multifractal and Levy-stable statistics of soil surface moisture distribution derived from 2D image analysis

机译:基于二维图像分析的土壤表面水分分布的多重分形和征稳统计

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摘要

Soil moisture distribution usually presents extreme variation at multiple spatial scales. A Levy stable model can assist multifractal analysis for a complete statistical characterization of such extreme variability. The objectives of the present work were (ⅰ) to characterize superficial soil moisture distribution patterns using a multifractal approach and (ⅱ) to propose a 2D/3D model for estimating the Levy stable index from the multifractal distribution. Photographs (Kodak™ EasyShare C182,12 Mpx resolutions) were taken at three different times of soil wetting process after soil irrigation (e.g., 5,10 and 20 min.). ImageJ Software was used for image processing and multifractal analysis. Levy stable index, μ, was estimated from the f(α) curve using a 2D extension of a previous model. All gray scale images were approximately bimodal. Multi-fractal analysis showed that D_0 was consistently <2, which gives evidence on the fractal structure of the support. All the investigated soil moisture distributions fitted well the multifractal log-Levy stable model with stability index within the range 1 < μ < 2 and Hurst exponent (H) 0.5 < H < 1. This implies that soil moisture pattern can be described by sub-Gaussian statistics (e.g., far from Central Limit Theorem) and it can arise as the outcome of persistence due to long memory effects. The results could be useful for improving the statistical characterization and the predictive capability of future models related to spatially variable soil processes.
机译:土壤水分分布通常在多个空间尺度上表现出极大的变化。征税稳定模型可以帮助进行多重分形分析,以便对此类极端变异性进行完整的统计表征。本工作的目的是(ⅰ)使用多重分形方法表征表层土壤水分分布模式,以及(ⅱ)提出2D / 3D模型以从多重分形分布估算Levy稳定指数。在土壤灌溉后的三个不同时间(例如5,10和20分钟)拍摄了照片(Kodak™EasyShare C182,分辨率为12 Mpx)。 ImageJ软件用于图像处理和多重分形分析。使用先前模型的2D扩展从f(α)曲线估算出征税稳定指数μ。所有灰度图像都是近似双峰的。多重分形分析表明,D_0始终<2,这为支撑物的分形结构提供了证据。所有调查的土壤水分分布均符合多元分形对数Levy稳定模型,其稳定指数在1 <μ<2范围内,赫斯特指数(H)在0.5 <H <1内。高斯统计量(例如,远离中心极限定理),由于长期记忆效应,它可以作为持久性的结果而出现。这些结果对于改善与空间可变土壤过程有关的未来模型的统计特性和预测能力可能是有用的。

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