Marine plastic pollution is hard to measure at scale: surveys are expensive and sparse, while remote sensing offers repeatable coverage—if we can make detection reliable across conditions, sensors, and geographies (Rußwurm et al., 2023)

Snap Snap Track (Open Mind proposal concept, 2025)

Research direction: multi-scale monitoring

We work on end-to-end pipelines that connect: 1) in-situ / camera observations (for ground truth and process understanding),
2) controlled field experiments (to learn detectability limits and calibration), and
3) large-scale satellite monitoring (to map and track litter hotspots over time).

Selected papers and works

Large-scale Detection of Marine Debris in Coastal Areas with Sentinel-2 (iScience, 2023)

Main contributions:

  • Introduces a pixel-wise marine debris detector (deep segmentation) for medium-resolution Sentinel-2 imagery.
  • Shows that performance gains come largely from data-centric design (many hard negatives + label refinement), not just architecture tweaks.
  • Releases model weights and training code to support reproducible large-scale monitoring.

Exploring plastic detectability on riverbanks using remote sensing (SSRN)

Main contributions:

  • Runs a controlled riverbank target experiment with multiple sensors (field spectrometer, close-range multispectral, Sentinel-2, PlanetScope, EnMAP).
  • Proposes a detectability workflow (incl. a new index and a simple classifier) and shows polyester sheets can be detected at larger sizes, while PET bottle targets were not detected in this setup.
  • Derives practical limits: detectability is constrained by spatial resolution and plastic concentration.

Exploring Transferability of Plastic-Water Hyacinth Interaction and Detection in Rivers (SSRN, 2025, under review)

Main contributions:

  • Studies how floating plastics become entangled in water hyacinths, enabling monitoring via a natural “proxy” that concentrates plastics.
  • Evaluates transferability of object detection models across rivers (including performance gaps between entangled vs. free-floating plastics).
  • Combines imagery-based detection with physical sampling, highlighting differences between what is visible from imagery and what is present in-situ.

    MSc thesis: double acquisition across sensors (2025)

  • MSc thesis exploring double-image / multi-sensor acquisition strategies for monitoring drifting marine litter.

What’s next

Current focus areas:

  • Cross-scale validation: connecting camera/field observations to satellite detections.
  • Robust generalization: reducing false positives via better negatives, site diversity, and uncertainty-aware outputs.
  • Operational monitoring: turning detectors into repeatable coastal and river monitoring products (with transparent evaluation and open baselines).