1. Plastics waste identification in river ecosystems by multispectral proximal sensing: a preliminary methodology study
- Author
-
I. Cortesi, M. Maraviglia, Marco Dubbini, Grazia Tucci, E. I. Parisi, M. De Giglio, De Giglio M., Dubbini M., Cortesi I., Maraviglia M., Parisi E.I., and Tucci G.
- 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 - 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.
- Published
- 2020
- Full Text
- View/download PDF