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Plastics waste identification in river ecosystems by multispectral proximal sensing: a preliminary methodology study
- Source :
- Water and Environment Journal. 35:569-579
- Publication Year :
- 2020
- Publisher :
- Wiley, 2020.
-
Abstract
- A considerable amount of the plastics produced around the world is now dispersed throughout the environment, and in particular in aquatic ecosystems. This can have damaging consequences for plants, animals and human beings. This study investigates some approaches for detection and monitoring of plastics waste in river habitats through multispectral image classification. The data are acquired using a proximity sensor in the electromagnetic spectrum range that includes the ultraviolet, visible and near infrared bands, as for the WorldView-2 satellite. The in-depth analysis of the spectral signatures obtained shows typical plastics trends and reflectance values in the near infrared bands. Different classification methods were compared to test their effectiveness for the isolation of plastics samples dispersed in a river habitat. This project represents the first step within a wider research programme, with the aim to define a new approach for future river pollution monitoring.
- Subjects :
- river ecosystem
Environmental Engineering
River ecosystem
Decision tree learning
Multispectral image
Management, Monitoring, Policy and Law
Pollution
multispectral proximity sensor
decision tree algorithm
remote sensing
plastic waste
Remote sensing (archaeology)
plastic spectral signature
Environmental science
Identification (biology)
Plastic waste
Water Science and Technology
Remote sensing
Subjects
Details
- ISSN :
- 17476593 and 17476585
- Volume :
- 35
- Database :
- OpenAIRE
- Journal :
- Water and Environment Journal
- Accession number :
- edsair.doi.dedup.....528a46daa413f4914de3c37292db7a61
- Full Text :
- https://doi.org/10.1111/wej.12652