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 |
|---|---|
| URN: | urn:nbn:de:bvb:384-opus4-1086105 |
| Frontdoor URL | https://opus.bibliothek.uni-augsburg.de/opus4/108610 |
| ISSN: | 2700-8150OPAC |
| Parent Title (English): | AGILE: GIScience Series |
| Publisher: | Copernicus |
| Place of publication: | Göttingen |
| Type: | Article |
| Language: | English |
| Year of first Publication: | 2021 |
| Publishing Institution: | Universität Augsburg |
| Release Date: | 2023/10/23 |
| Volume: | 2 |
| First Page: | 32 |
| DOI: | https://doi.org/10.5194/agile-giss-2-32-2021 |
| 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) |
