Evaluation of remote sensing monitoring as a Prognostic Tool in microplastic pollution

Lars Hansen; M. Johansson; S. Nilsson

doi:10.5281/zenodo.22812691

Authors

Lars Hansen Division of Environmental Science, Oder Center for Environmental Science Author https://orcid.org/5089-5783-6641-1555
M. Johansson Department of Clinical Environmental Science, Amur Center for Environmental Technology Author https://orcid.org/4379-8781-3849-6013
S. Nilsson Department of Clinical Environmental Science, Snake Academy of Environmental Science Author https://orcid.org/1496-5513-2149-0781

DOI:

https://doi.org/10.5281/zenodo.22812691

Keywords:

remote sensing, microplastic pollution, satellite monitoring, hyperspectral imaging, prognostic modeling

Abstract

Graphical abstract

Background: Microplastic pollution is now documented across every ocean basin, but in-situ sampling by net trawl or beach transect is too sparse and slow to resolve basin-scale patchiness or to establish reliable pollution trends.

Objective: This review evaluates whether remote sensing platforms, from airborne and drone-mounted hyperspectral sensors to multispectral and hyperspectral satellites, can serve as a genuinely prognostic tool for anticipating microplastic accumulation rather than simply mapping existing debris.

Methods: We synthesized peer-reviewed studies on the spectral basis for optical plastic detection, sensor platform performance, and the coupling of remotely sensed observations to ocean transport and fragmentation models with forecasting relevance.

Findings: Shortwave infrared absorption features reliably distinguish plastic from water and biogenic material at airborne and drone scale, while spaceborne multispectral and hyperspectral sensors detect macroplastic aggregations with useful but imperfect accuracy; direct sub-pixel detection of dispersed microplastic itself remains unvalidated, and prognostic use so far depends on coupling debris and convergence-zone detections to circulation models rather than on satellite retrieval of microplastic concentration directly.

Conclusions: Remote sensing already functions as a meaningful, if indirect, prognostic instrument by tracking the macroplastic-dominated slicks and convergence zones from which microplastic fragments and disperses, and its forecasting value will grow with sustained multi-platform observation series and closer validation against microplastic-scale detection limits.

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