Multiphasic Quantification of Soil Morphology using High-Resolution X-ray Computed Tomography

使用高分辨率 X 射线计算机断层扫描对土壤形态进行多相量化

• 批准号: RGPIN-2014-06151
• 负责人: Heck, Richard
• 金额: $ 2.19万
• 依托单位: University of Guelph
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=612059
• 关键词: Multiphasic; Quantification; Soil; Morphology; using

X-ray computed tomography (CT) has become an important tool for understanding the three-dimensional (3D) configuration of soil components. This technology has provided unique insight into the physical nature of soil, especially its hydrodynamic behaviour and the impact of management practices on structural quality. One of the principle limitations of typical CT imagery of soil is its monochromatic nature, limiting our ability to distinguish among the various solid and organic solids. The issue of partial volumes, whereby the value expressed by a given unit of the imagery (voxel) may result from more than one material (referred to as the partial volume effect) further introduces complexity to segmentation and classification. Moreover, our capacity to process 3D imagery lags behind that for 2D imagery (which has been driven primarily by remote sensing applications); in part, this is also due to greater computational requirements for 3D imagery. As such, effective standardization of methodologies for the application of X-ray CT to soil has yet to be achieved. The current research program will focus on contributing our ability to discriminate the major mineral and organic solid phases that commonly occur naturally in soils, or may be present as contaminants. Specific attention will be given to refining the composition of the X-ray beam, through appropriate combinations of scanning energy and metal pre-filtering, to maximize the discrimination among phases during the scanning stage. This will be complemented by the adaptation of advanced object-based image segregation techniques to 3D X-ray CT imagery. Specific attention will be given to optimizing the quantification of hydromorphic pedofeatures, specifically Fe and Mn segregations. Finally, methods for morphometric analysis of classified imagery and advanced spatial analysis, including multi-fractal and entropy techniques, of the original grey-scale imagery will continue to be refined to take advantage of improved scanning and segmentation techniques. This research will be conducted primarily in the Soil Imaging Laboratory of the University of Guelph, but will also engage an international network of expertise on X-ray CT imaging and image processing, and provide both post-graduate and undergraduate level training opportunities.

X射线计算机断层扫描（CT）已成为了解土壤成分三维（3D）结构的重要工具。这项技术为土壤的物理性质提供了独特的见解，特别是其水动力行为和管理实践对结构质量的影响。典型的土壤CT图像的主要局限性之一是其单色性，限制了我们区分各种固体和有机固体的能力。部分体积的问题，其中由图像的给定单元（体素）表示的值可能由多于一种材料产生（称为部分体积效应），进一步引入了分割和分类的复杂性。此外，我们处理3D图像的能力落后于2D图像（主要由遥感应用驱动）;部分原因是3D图像的计算要求更高。因此，X射线CT应用于土壤的方法的有效标准化尚未实现。 目前的研究计划将集中在贡献我们的能力，以区分主要的矿物和有机固体相，通常在土壤中自然发生，或可能存在的污染物。将特别注意通过扫描能量和金属预过滤的适当组合来细化X射线束的组成，以最大限度地提高扫描阶段期间相之间的区分。这将通过将先进的基于对象的图像分离技术应用于3D X射线CT图像来补充。将特别注意优化水成土壤特征的量化，特别是铁和锰偏析。最后，将继续改进分类图像的形态计量分析方法和原始灰度图像的高级空间分析方法，包括多重分形和熵技术，以利用改进的扫描和分割技术。这项研究将主要在圭尔夫大学的土壤成像实验室进行，但也将涉及X射线CT成像和图像处理的专业知识的国际网络，并提供研究生和本科生水平的培训机会。