Sentinel-2 Collection Is Available For Digital Twin Applications

Horizon 2020 Global Earth Monitor project and the European Space Agency’s Digital Twin activities scientists Matic Lubej and Grega Milcinski create a data collection for multipurpose use including Digital Twin applications.

Grega Milcinski says “Such collection is an essential input for any kind of EO ML process. To make it by oneself, one would have to process several PB of data. We’ve done this for you.”

The data is available via several means:

What is this good for?

“First and foremost, the envision this collection to be used in various machine learning exercises. Just about any model that was working on Sentinel-2 data should work with these data as well, hopefully even better, as the data is cloudless (wherever possible). Most of the complexity of the remote sensing has removed, therefore making the collection easy to use even for non-experts, e.g. computer vision data scientists. As a starting point, one can perform land cover or crop-type classification, perhaps bare soil or mowing detection. Sentinel Hub custom scripts work here as well, e.g. monthly snow report or snow cover change detection(make sure to check if the script is using DN or reflectance and adjust accordingly).

Having the data easily accessible at such a large scale also makes it convenient to observe various global phenomena, for research as well as for educational purposes. An example that is often shown is a variation of NDVI during the year. Now you can perform these analyses yourself, in EO Browser, Jupyter Notebook, or elsewhere.

One could also use the data as a nice background map — the resolution is twice the one of the Blue Marble and the fact that it is available in 37 intervals over the year might make it very interactive. With COGs being openly accessible it should be straightforward to integrate them using Sentinel Hub OGC services or rio-tiler-mosaic.

Last but not least, there is a ton of material for artistic expressions of our planet, either for still imagery or by creating beautiful time-lapses.”

More Information and Source: Digital Twin Sandbox Sentinel-2 collection available to everyone

Nursinem Handan ŞAHAN
Nursinem Handan ŞAHAN
Graduated from Yıldız Technical University, Department of Geomatics Engineering in 2018 as an honour student. During her undergraduate education, she studied at the Warsaw University of Technology with the Erasmus + program. Currently continuing her education at Istanbul Technical University, Department of Geographical Information Technologies.

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