Identification of Tyre and Plastic Waste from Combined Copernicus Sentinel-1 and -2 Data
As a result of tightened waste regulation across Europe, reports of waste crime have been on the rise. Significant stockpiles of tyres and plastic materials have been identified as a threat to both human and environmental health, leading to water and livestock contamination, providing substantial fu...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-08-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/12/17/2824 |
| _version_ | 1797555015916716032 |
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| author | Robert Page Samantha Lavender Dean Thomas Katie Berry Susan Stevens Mohammed Haq Emmanuel Udugbezi Gillian Fowler Jennifer Best Iain Brockie |
| author_facet | Robert Page Samantha Lavender Dean Thomas Katie Berry Susan Stevens Mohammed Haq Emmanuel Udugbezi Gillian Fowler Jennifer Best Iain Brockie |
| author_sort | Robert Page |
| collection | DOAJ |
| description | As a result of tightened waste regulation across Europe, reports of waste crime have been on the rise. Significant stockpiles of tyres and plastic materials have been identified as a threat to both human and environmental health, leading to water and livestock contamination, providing substantial fuel for fires, and cultivating a variety of disease vectors. Traditional methods of identifying illegal stockpiles usually involve laborious field surveys, which are unsuitable for national scale management. Remotely-sensed investigations to tackle waste have been less explored due to the spectrally variable and complex nature of tyres and plastics, as well as their similarity to other land covers such as water and shadow. Therefore, the overall objective of this study was to develop an accurate classification method for both tyre and plastic waste to provide a viable platform for repeatable, cost-effective, and large-scale monitoring. An augmented land cover classification is presented that combines Copernicus Sentinel-2 optical imagery with thematic indices and Copernicus Sentinel-1 microwave data, and two random forests land cover classification algorithms were trained for the detection of tyres and plastics across Scotland. Testing of the method identified 211 confirmed tyre and plastic stockpiles, with overall classification accuracies calculated above 90%. |
| first_indexed | 2024-03-10T16:41:17Z |
| format | Article |
| id | doaj.art-e44fbce8d247410d8af34612932a0335 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T16:41:17Z |
| publishDate | 2020-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-e44fbce8d247410d8af34612932a03352023-11-20T12:02:46ZengMDPI AGRemote Sensing2072-42922020-08-011217282410.3390/rs12172824Identification of Tyre and Plastic Waste from Combined Copernicus Sentinel-1 and -2 DataRobert Page0Samantha Lavender1Dean Thomas2Katie Berry3Susan Stevens4Mohammed Haq5Emmanuel Udugbezi6Gillian Fowler7Jennifer Best8Iain Brockie9Pixalytics Ltd., 1 Davy Road, Plymouth Science Park, Derriford, Plymouth, Devon PL6 8BX, UKPixalytics Ltd., 1 Davy Road, Plymouth Science Park, Derriford, Plymouth, Devon PL6 8BX, UKPixalytics Ltd., 1 Davy Road, Plymouth Science Park, Derriford, Plymouth, Devon PL6 8BX, UKScottish Environment Protection Agency, Angus Smith Building, Eurocentral, Holytown ML1 4WQ, UKScottish Environment Protection Agency, Angus Smith Building, Eurocentral, Holytown ML1 4WQ, UKScottish Environment Protection Agency, Angus Smith Building, Eurocentral, Holytown ML1 4WQ, UKScottish Environment Protection Agency, Angus Smith Building, Eurocentral, Holytown ML1 4WQ, UKScottish Environment Protection Agency, Angus Smith Building, Eurocentral, Holytown ML1 4WQ, UKScottish Environment Protection Agency, Angus Smith Building, Eurocentral, Holytown ML1 4WQ, UKScottish Environment Protection Agency, Angus Smith Building, Eurocentral, Holytown ML1 4WQ, UKAs a result of tightened waste regulation across Europe, reports of waste crime have been on the rise. Significant stockpiles of tyres and plastic materials have been identified as a threat to both human and environmental health, leading to water and livestock contamination, providing substantial fuel for fires, and cultivating a variety of disease vectors. Traditional methods of identifying illegal stockpiles usually involve laborious field surveys, which are unsuitable for national scale management. Remotely-sensed investigations to tackle waste have been less explored due to the spectrally variable and complex nature of tyres and plastics, as well as their similarity to other land covers such as water and shadow. Therefore, the overall objective of this study was to develop an accurate classification method for both tyre and plastic waste to provide a viable platform for repeatable, cost-effective, and large-scale monitoring. An augmented land cover classification is presented that combines Copernicus Sentinel-2 optical imagery with thematic indices and Copernicus Sentinel-1 microwave data, and two random forests land cover classification algorithms were trained for the detection of tyres and plastics across Scotland. Testing of the method identified 211 confirmed tyre and plastic stockpiles, with overall classification accuracies calculated above 90%.https://www.mdpi.com/2072-4292/12/17/2824CopernicusEARSeLland use &land coverrandom forestsplastics |
| spellingShingle | Robert Page Samantha Lavender Dean Thomas Katie Berry Susan Stevens Mohammed Haq Emmanuel Udugbezi Gillian Fowler Jennifer Best Iain Brockie Identification of Tyre and Plastic Waste from Combined Copernicus Sentinel-1 and -2 Data Remote Sensing Copernicus EARSeL land use & land cover random forests plastics |
| title | Identification of Tyre and Plastic Waste from Combined Copernicus Sentinel-1 and -2 Data |
| title_full | Identification of Tyre and Plastic Waste from Combined Copernicus Sentinel-1 and -2 Data |
| title_fullStr | Identification of Tyre and Plastic Waste from Combined Copernicus Sentinel-1 and -2 Data |
| title_full_unstemmed | Identification of Tyre and Plastic Waste from Combined Copernicus Sentinel-1 and -2 Data |
| title_short | Identification of Tyre and Plastic Waste from Combined Copernicus Sentinel-1 and -2 Data |
| title_sort | identification of tyre and plastic waste from combined copernicus sentinel 1 and 2 data |
| topic | Copernicus EARSeL land use & land cover random forests plastics |
| url | https://www.mdpi.com/2072-4292/12/17/2824 |
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