An Image Analysis Algorithm for Soil Structure Identification

Pore space study has been utilized as a general method for defining soil structures. This is because the characteristics particular to pore space impact the majority of physical and physicochemical soil parameters relevant due to plant growth. This paper presents an image segmentation approach for detecting the soil pore structures that have been studied by way of soil tomography sections. In so-doing, a research study was conducted using a density-based clustering method, and in turn, the nonparametric kernel estimation methodology. This overcomes the rigidity of arbitrary assumptions concerning the number or shape of clusters among data, and lets the researcher detect inherent data structures. After a short description of the method, the practical aspects and applications illustrated with a number of soil aggregates are presented.