Plasticulture detection at the country scale by combining multispectral and SAR satellite data
Abstract The use of plastic films has been growing in agriculture, benefiting consumers and producers. However, concerns have been raised about the environmental impact of plastic film use, with mulching films posing a greater threat than greenhouse films. This calls for large-scale monitoring of di...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-04-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-93658-2 |
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| author | Alessandro Fabrizi Peter Fiener Thomas Jagdhuber Kristof Van Oost Florian Wilken |
| author_facet | Alessandro Fabrizi Peter Fiener Thomas Jagdhuber Kristof Van Oost Florian Wilken |
| author_sort | Alessandro Fabrizi |
| collection | DOAJ |
| description | Abstract The use of plastic films has been growing in agriculture, benefiting consumers and producers. However, concerns have been raised about the environmental impact of plastic film use, with mulching films posing a greater threat than greenhouse films. This calls for large-scale monitoring of different plastic film uses. We used cloud computing, freely available optical and radar satellite images, and machine learning to map plastic-mulched farmland (PMF) and plastic cover above vegetation (PCV) (e.g., greenhouse, tunnel) across Germany. The algorithm detected 103 103 ha of PMF and 37 103 ha of PCV in 2020, while a combination of agricultural statistics and surveys estimated a smaller plasticulture cover of around 100 103 ha in 2019. Based on ground observations, the overall accuracy of the classification is 85.3%. Optical and radar features had similar importance scores, and a distinct backscatter of PCV was related to metal frames underneath the plastic films. Overall, the algorithm achieved great results in the distinction between PCV and PMF. This study maps different plastic film uses at a country scale for the first time and sheds light on the high potential of freely available satellite data for continental monitoring. |
| format | Article |
| id | doaj-art-dfd563ba661b43d6a59cb0509d07c8d1 |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-dfd563ba661b43d6a59cb0509d07c8d12025-08-20T03:04:50ZengNature PortfolioScientific Reports2045-23222025-04-0115111910.1038/s41598-025-93658-2Plasticulture detection at the country scale by combining multispectral and SAR satellite dataAlessandro Fabrizi0Peter Fiener1Thomas Jagdhuber2Kristof Van Oost3Florian Wilken4Institute of Geography, University of AugsburgInstitute of Geography, University of AugsburgInstitute of Geography, University of AugsburgEarth and Life Institute, Université Catholique de LouvainInstitute of Geography, University of AugsburgAbstract The use of plastic films has been growing in agriculture, benefiting consumers and producers. However, concerns have been raised about the environmental impact of plastic film use, with mulching films posing a greater threat than greenhouse films. This calls for large-scale monitoring of different plastic film uses. We used cloud computing, freely available optical and radar satellite images, and machine learning to map plastic-mulched farmland (PMF) and plastic cover above vegetation (PCV) (e.g., greenhouse, tunnel) across Germany. The algorithm detected 103 103 ha of PMF and 37 103 ha of PCV in 2020, while a combination of agricultural statistics and surveys estimated a smaller plasticulture cover of around 100 103 ha in 2019. Based on ground observations, the overall accuracy of the classification is 85.3%. Optical and radar features had similar importance scores, and a distinct backscatter of PCV was related to metal frames underneath the plastic films. Overall, the algorithm achieved great results in the distinction between PCV and PMF. This study maps different plastic film uses at a country scale for the first time and sheds light on the high potential of freely available satellite data for continental monitoring.https://doi.org/10.1038/s41598-025-93658-2PlasticAgricultureSynthetic aperture radarOptical remote sensingSentinelGoogle earth engine |
| spellingShingle | Alessandro Fabrizi Peter Fiener Thomas Jagdhuber Kristof Van Oost Florian Wilken Plasticulture detection at the country scale by combining multispectral and SAR satellite data Scientific Reports Plastic Agriculture Synthetic aperture radar Optical remote sensing Sentinel Google earth engine |
| title | Plasticulture detection at the country scale by combining multispectral and SAR satellite data |
| title_full | Plasticulture detection at the country scale by combining multispectral and SAR satellite data |
| title_fullStr | Plasticulture detection at the country scale by combining multispectral and SAR satellite data |
| title_full_unstemmed | Plasticulture detection at the country scale by combining multispectral and SAR satellite data |
| title_short | Plasticulture detection at the country scale by combining multispectral and SAR satellite data |
| title_sort | plasticulture detection at the country scale by combining multispectral and sar satellite data |
| topic | Plastic Agriculture Synthetic aperture radar Optical remote sensing Sentinel Google earth engine |
| url | https://doi.org/10.1038/s41598-025-93658-2 |
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