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Multispectral ASV measurement datasets
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Scientists tested a low-cost robotic boat equipped with a light-based sensor that can detect both harmful algae and tiny plastic particles (microplastics) floating in water. This matters because both algae blooms and microplastics can end up in the water we drink or swim in, and having an affordable tool to spot them could help communities monitor water safety more easily. This particular release shares the raw measurement data collected during the tests, not conclusions about how well the tool works, that analysis is available separately.
Field and laboratory measurements from a low-cost autonomous surface vehicle carrying a three-wavelength active optical sensor, used to compute an Algal Growth Index (AGI) and a polyethylene-responsive scattering index (MPI). Contents: night survey (15 January 2026, Coyote Point, San Mateo CA), day survey (18 January 2026, same site), 93 laboratory calibration trial files, and a NOAA NCEI Marine Microplastics extract. This archive holds data only. The analysis code is at https://github.com/dhruvyadati/multispectral_asv_pub
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Multispectral ASV measurement datasets
AI summary Read the abstract
Scientists tested a low-cost robotic boat equipped with light sensors to detect both harmful algae and tiny plastic particles (microplastics) floating in water. This matters because both algae blooms and microplastics can end up in the water we drink or the seafood we eat, and cheaper monitoring tools could help catch contamination earlier. Note that this release is just the raw data and lab test files, it doesn't yet include the actual findings on how well the technology worked.
A Portable Optical Sensor for Microplastic Detection: Development and Calibration
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Researchers built a portable, low-cost optical sensor prototype designed to detect microplastics by shining multiple wavelengths of light through water samples. The device measures how different plastic particles absorb and scatter light, producing color spectra that can help identify microplastics. The sensor offers an affordable field-deployable option for environmental monitoring, with potential future improvements using machine learning for automated identification.
Use of an uncrewed surface vehicle and near infrared hyperspectral imaging for sampling and analysis of aquatic microplastics
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Researchers combined an uncrewed surface vehicle with near-infrared hyperspectral imaging to sample and analyze aquatic microplastics larger than 300 micrometers. The approach demonstrated improved scalability and repeatability compared to traditional trawling methods, offering a more efficient way to monitor microplastic contamination in coastal waters.
Microscopy Images of Microplastics in Photovoltaic-Covered Irrigation Pond Water
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Scientists photographed tiny plastic particles found in water from an irrigation pond in Spain (one that's covered with solar panels) to build and test an AI tool that can automatically spot and measure microplastics in water samples. This matters because irrigation water can carry microplastics onto crops we eventually eat, and faster, more reliable detection methods could help researchers track this potential contamination more efficiently. Note that this dataset is about developing the measurement tool itself, not about health effects, it doesn't tell us how much microplastic exposure is happening or what harm it might cause.
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Researchers tested a combination of an autonomous surface vehicle and a near-infrared hyperspectral imager to rapidly sample and identify microplastics on the Norwegian coast. Results compared favorably with standard FTIR analysis and demonstrated a repeatable method for assessing spatially variable microplastic concentrations in the marine environment.
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When a large batch of papers lands in the Atlas, we read through it and send a short write-up of what stood out.