Identification of Microplastics in Soils Using 2D Geometric Shape Descriptors
- 1Geoinformatics Group, Institute of Geography, University of Augsburg, Augsburg, Germany
- 2Water and Soil Resources Research, Institute of Geography, University of Augsburg, Augsburg, Germany
Keywords: microplastic, shape descriptors, machine learning
Abstract. Microplastics (MP), until now mostly studied in aquatic ecosystems, are also largely polluting terrestrial ecosystems, especially soil systems. Overall, there is a lack of robust and fast methods to identify, separate and eliminate MPs from soils. This paper is a first attempt to use 2D shape descriptors and Random Forest Machine Learning method in order to discriminate soil and MP particles. The results of this study demonstrate promising potential of the Machine Learning approach and shape descriptors in this relatively new scientific field of determining MPs in soils.