Journal of Forestry Research

, Volume 30, Issue 3, pp 1053–1061 | Cite as

Three-dimensional visualization of soil pore structure using computed tomography

  • Qiaoling Han
  • Xibo Zhou
  • Lei Liu
  • Yandong Zhao
  • Yue ZhaoEmail author
Original Paper


The geometric and spatial characteristics of pore structures determine the permeability and water retention of soils, which have important effects on soil functional diversity and ecological restoration. Until recently, there have not been tools and methods to visually and quantitatively describe the characteristics of soil pores. To solve this problem, this research reconstructs the geometry and spatial distribution of soil pores by the marching cubes method, texture mapping method and the ray casting method widely used in literature. The objectives were to explore an optimal method for three-dimensional visualization of soil pore structure by comparing the robustness of the three methods on soil CT images with single pore structure and porosity ranging from low (2–5%) to high (12–18%), and to evaluate the reconstruction performance of the three methods with different geometric features. The results demonstrate that there are aliases (jagged edges) and deficiency at the boundaries of the model reconstructed by the marching cubes method and pore volumes are smaller than the ground truth, whereas the results of the texture mapping method lack the details of pore structures. For all the soil images, the ray casting method is preferable since it better preserves the pore characteristics of the ground truth. Furthermore, the ray casting method produced the best soil pore model with higher rendering speed and lower memory consumption. Therefore, the ray casting method provides a more advanced method for visualization of pore structures and provides an optional technique for the study of the transport of moisture and the exchange of air in soil.


Soil Pore structure X-ray computed tomography Three-dimensional reconstruction Pore visualization 


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Copyright information

© Northeast Forestry University and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Qiaoling Han
    • 1
    • 2
  • Xibo Zhou
    • 1
  • Lei Liu
    • 1
    • 3
  • Yandong Zhao
    • 1
    • 2
  • Yue Zhao
    • 1
    • 2
    Email author
  1. 1.School of TechnologyBeijing Forestry UniversityBeijingPeople’s Republic of China
  2. 2.Beijing Laboratory of Urban and Rural Ecological EnvironmentBeijing Municipal Education CommissionBeijingPeople’s Republic of China
  3. 3.Key Lab of State Forestry Administration for Forestry Equipment and Automation, School of TechnologyBeijing Forestry UniversityBeijingPeople’s Republic of China

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