Identification of microplastics in soils using 2D geometric shape descriptors

  • 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.

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Author:Irada IsmayilovaORCiDGND, Tabea ZeyerORCiDGND, Sabine TimpfORCiDGND
Frontdoor URL
Parent Title (English):AGILE: GIScience Series
Place of publication:Göttingen
Year of first Publication:2021
Publishing Institution:Universität Augsburg
Release Date:2023/10/23
First Page:32
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Geographie
Fakultät für Angewandte Informatik / Institut für Geographie / Professur für Geoinformatik
Fakultät für Angewandte Informatik / Institut für Geographie / Professur für Wasser- und Bodenressourcenforschung
Dewey Decimal Classification:9 Geschichte und Geografie / 91 Geografie, Reisen / 910 Geografie, Reisen
Licence (German):CC-BY 4.0: Creative Commons: Namensnennung (mit Print on Demand)