Advances in machine vision technologies for the measurement of soil texture, structure and topography

Publication date: 20/02/2023
Extent: 62 pages

Contributions by: Jean-Marc Gilliot, AgroParisTech Paris Saclay University, France; and Ophélie Sauzet, University of Applied Sciences of Western Switzerland, The Geneva Institute of Technology, Architecture and Landscape (HEPIA), Soils and Substrates Group, Institute Land-Nature- Environment (inTNE Institute), Switzerland

Chapter synopsis:

This chapter examines advances in machine vision technologies for the measurement of soil texture, structure and topography. It starts by providing an overview of the basic principles of machine vision technologies, focusing on areas such as 3D surface modelling and various methods of soil thin section microscopy. Two case studies are also provided in the chapter to support the main text discussion.

DOI: 10.19103/AS.2022.0107.15