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The PlastOPol system for marine litter monitoring by citizen scientists.
- Source :
-
Environmental Modelling & Software . Nov2023, Vol. 169, pN.PAG-N.PAG. 1p. - Publication Year :
- 2023
-
Abstract
- Marine plastic pollution has in recent decades become ubiquitous, posing threats to flora, fauna, and potentially human health. Proper monitoring and registration of litter occurrences are, therefore, of paramount importance to support better-informed decision-making. In this paper, we introduce the PlastOPol marine litter monitoring system. PlastOPol integrates external data sources on beached litter with data collected through citizen science initiatives based on the use of a mobile application (App). The App relies on state-of-the-art machine-learning approaches for litter detection and registration. The system also supports a human-in-the-loop strategy based on which improved versions of litter detection models are created over time thanks to annotations by citizen scientists. Finally, the system includes a geographic visualization tool to support the analysis of litter distribution data by decision-makers. This system has the potential to create a direct path between citizens, researchers, and decision-makers on the issue of marine litter. Finally, the paper presents compelling usage scenarios of the proposed monitoring system and discusses the evaluation of the App through a user study. The user study suggests that the PlastOPol system is an effective and valuable tool to monitor and communicate marine litter. [Display omitted] • This paper introduces PlastOPol, a new system for marine litter monitoring based on citizen science. • This paper introduces a data model for litter occurrence registration and data sharing. • The model evolves based on the annotation of citizen scientists made through a mobile application. • This paper introduces a map-based visualization that supports the analysis of litter distribution. • This paper presents and discusses a user study to assess the potential of PlastOPol to support citizen science tasks. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 13648152
- Volume :
- 169
- Database :
- Academic Search Index
- Journal :
- Environmental Modelling & Software
- Publication Type :
- Academic Journal
- Accession number :
- 172848050
- Full Text :
- https://doi.org/10.1016/j.envsoft.2023.105784