As of today, Sentinel 2 data are available in Google Earth Engine. See the dataset description page. Please let us know if anyone has comments or suggestions.
Thanks once again to the Copernicus program, and to forum members for answering our questions.
Several people from the Earth Engine team, including me, will be attending the Living Planet Symposium in Prague next week. You are welcome to stop by the Google booth if you are interested.
In addition, we will be offering two free hands-on workshops at the Google Prague office:
Introduction to Earth Engine, Wednesday, May 11, 2016, 18:00 - 20:30
This workshop is intended for new Google Earth Engine users interested in doing large-scale remote sensing analysis. Participants will be guided through the basics of getting up and running with Earth Engine and work through examples of how to easily perform complex, large-scale tasks such as multi-sensor time-series compositing and supervised classification using the Earth Engine API and interactive development environment.
Intermediate Earth Engine Topics, Thursday, May 12, 2016, 18:00 - 20:30
This workshop is intended for users that have already some experience using Earth Engine, and would like to learn more about the Earth Engine internals and advanced processing techniques.
Check out the workshop website for more information and a link to the registration form.
Hi Google Earth Engine Team,
Is there a similar workshop planned for users in the USA any time soon? I am interested in learning more about SENTINEL-2 MSI data processing in GEE.
Thanks,
Abdulwasey
Workshop announcements are usually sent to our developers mailing list (you get an invite when you sign up for EE). You can also ask questions on this list without having to wait for a workshop.
All workshops are announced on the mailing list. There will be an EE summit in California in June, but it’s too late to apply this year, unfortunately.
The use of Sentinel images with Google Earth Engine is very promising, but only 1C level is included in the datasets. I need to work with 2A level though. Is there any chance to include 2A level imagery in the datasets of GEE? Or alternatively, is there any reliable atmospheric correction I could easily apply to Sentinel-2 1C collection? Thanks in advance
ESA assessment
ESA organized an “assessment” by 6 distinguished data users
with no special knowledge of atmospheric correction and cloud screening
with 6 weeks to analyze 1 TB of data
without any comparison to in-situ data
Experts looked at some images (no arid sites), and provided no statistics result : “No method is perfect”
Based on this ESA concluded
“The multi-temporal technique of MAJA, which features state of the art results, is not delivering the quantum leap in image utilisation yet”
“SEN2COR resulted a state of the art method, and simpler to implement and run operationally than MAJA”
=> Sen2cor will be used for the next few years to produce Sentinel-2 data at ESA at global scale
We would like to see a broader consensus accepting sen2cor first. Running an SR algorithm on all of S2 and storing the results costs a non-trivial amount of money, so unfortunately, we have to set a high acceptance bar.
you have an interesting conversation here.
But there is still no answer on the original question and the last reply was November 2017.
@simonf: do you finally got your “broader consensus” after almost one year?
I’m really intrested in using Level2A data in GEE. Could you please give us an update?
Is there a possibility, at least , to apply an atmospheric correction on an image collection of S2-L1C in GEE?
Would be great to hear from you.
Sorry, still no news (also, it’s not possible to run classic processing to SR in EE). But we are well aware of the demand for SR, and continue to investigate options.
Don’t know whether I’d call that consensus, but at least ESA decided to use Sen2Cor for producing the official S2A product, and this product is now also available from the Senitnel data hubs. So probably EE doesn’t need to do any processing itself, but store & provide the L2A the way it does for L1C (unless the huge amount of data - L2A being roughly as big as L1C, ie doubling the required storage - is a problem).
@jmendrok
The problem with the L2A data in the sentinel hub is, that not all of the L1C are corrected. There is a pre-selection by ESA/Copernicus (?!). Unfortunately I didn’t get an answer how they select which image is worth to correct and which image is not. But a huge amount of L1C data are not corrected.
Hi guys
it is good to watch your conversation, it is already 2019 now, I wonder if there is an answer about the SR product in GEE, anything new? also, if we can’t use SR product lunch by GEE, is there an alternative option for us to generate our own SR product on GEE?