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This repository contains data from Sentinel-2 imagery on floating marine debris, with annotations for six debris classes, including plastic, driftwood, seaweed, pumice, sea snot, and sea foam.

License: Creative Commons Attribution 4.0 International

Python 100.00%
classification debris detection earth-observation machine-learning multispectral-images ocean plastic pollution pumice remote-sensing satellite satellite-data satellite-imagery sea-snot seaweed sentinel-2 synthetic-data

floating-marine-debris-data's Introduction

Hi there, I am Miguel ๐Ÿ‘‹

I'm a Machine Learning Engineer at Visionspace, specializing in space-related projects ๐Ÿ“ก

As part of my activities, I also contribute to the OPS-SAT mission with the European Space Agency (ESA) ๐Ÿš€

I hold a degree in Electrical and Computer Engineering and have a keen interest in applying machine learning techniques to tackle environmental challenges. I'm excited to collaborate on meaningful projects that make a positive impact on our planet ๐ŸŒ

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floating-marine-debris-data's Issues

Which ACOLITE's atmospheric correction is applied?

Hello,

Could you please specify which ACOLITE's atmospheric correction you applied to the Sentinel-2 L1C products before extracting the spectral information for each class? rayleigh reflectance or surface reflectance?

Thank you for your work.

Andrea

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