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Multifractal analysis on CT soil images: Fluctuation analysis versus mass distribution

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  • Sun, Xiaoqin
  • She, Dongli
  • Sanz, Ernesto
  • Martín-Sotoca, Juan J.
  • Tarquis, Ana M.
  • Gao, Lei

Abstract

The combined action of physical, chemical and biological processes at different scales creates a highly complex soil architecture. At the same time, this soil pores' complexity is crucial in maintaining soil biogeochemical and biophysical processes. The development of digital image processing and a multiscaling analysis allow a better study to quantify pore complexity and evaluate pore spatial variability. This study took saline soils from coastal reclamation areas as an example and aimed to compare the multifractality of porosity series using different methods on sample cubes of 512 pixels in length extracted at different soil depths. Two measures were selected to represent the porosity series: the average grey values (AVG) of each slice and the CT-porosity (CTP) of binarized slices. The mass distribution (MD), detrended fluctuation analysis (DFA), and the moments function (K) were the methods applied in the multiscaling study. Shuffled and surrogated series were used to analyze the two possible multifractality sources, the probability distribution density function (PDF) and long-range correlations, respectively.

Suggested Citation

  • Sun, Xiaoqin & She, Dongli & Sanz, Ernesto & Martín-Sotoca, Juan J. & Tarquis, Ana M. & Gao, Lei, 2023. "Multifractal analysis on CT soil images: Fluctuation analysis versus mass distribution," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    • Handle: RePEc:eee:chsofr:v:176:y:2023:i:c:s0960077923009815
    DOI: 10.1016/j.chaos.2023.114080
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    References listed on IDEAS

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    1. Sarker, Alivia & Mali, Provash, 2021. "Detrended multifractal characterization of Indian rainfall records," Chaos, Solitons & Fractals, Elsevier, vol. 151(C).
    2. Kantelhardt, Jan W. & Zschiegner, Stephan A. & Koscielny-Bunde, Eva & Havlin, Shlomo & Bunde, Armin & Stanley, H.Eugene, 2002. "Multifractal detrended fluctuation analysis of nonstationary time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 316(1), pages 87-114.
    3. Shang, Pengjian & Lu, Yongbo & Kamae, Santi, 2008. "Detecting long-range correlations of traffic time series with multifractal detrended fluctuation analysis," Chaos, Solitons & Fractals, Elsevier, vol. 36(1), pages 82-90.
    4. Telli, Şahin & Chen, Hongzhuan & Zhao, Xufeng, 2022. "Detecting multifractality and exposing distributions of local fluctuations: Detrended fluctuation analysis with descriptive statistics pooling," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
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