Quantitative Image Analysis in Soil Science
Abstract:
While qualitative image analysis of thin sections has been used in soil science for over a century, sophisticated quantitative image analysis techniques have emerged only relatively recently and are constantly evolving, especially in light of recent developments in the field of artificial intelligence. These techniques represent a powerful tool that enables researchers to gain deeper insights into the structure, composition, and functioning of soils.
This talk will provide a comprehensive overview of the various imaging techniques utilized by our group in the study of soil systems at different scales. We will explore methodologies ranging from classical image segmentation and pattern recognition to advanced machine learning approaches.
Case studies will illustrate the application of these techniques in understanding the geometric properties of the pore system, the effects of pore properties on the habitat function of a soil, and root-soil interactions. Additionally, we will discuss the challenges and opportunities associated with integrating quantitative image analysis into soil research, highlighting future directions and technological advancements that promise to enhance our understanding of 2D, 3D and 4D soil processes.
Attendees will gain a foundational understanding of how quantitative image analysis can be applied to address critical questions in soil science, driving innovation and improving sustainability in land management practices.
Gli interessati possono scrivermi una mail a giovanni.mastrolonardo@unifi.it