Dear Sen4Cap,
Another interest. Since data is from both Sentinel 2 and Landsat 8 (different satellites), when sen4cap does the resample and gap filled for both data set together, is there any adjustment or process to eliminate any discrepancy when we do time series analysis or change detection on the combined data set?
Thanks and Regards,
Henry
Hello Henry,
We discussed a little bit about that during the webinar and I have to go back with what I said concerning the gap filling for the L4A crop type. So like Sophie said during the webinar, the system handles the download/access to the L8 data and the preprocessing using MAJA, to provide L8 L2A products. Then, if you trigger the L3B vegetation status processor, it will compute for each acquisition, the NDVI, LAI, FAPAR and FCOVER, separately for the S2 and L8 time series. And then, the L4B grassland mowing detection and L4C agricultural practices monitoring processors use by default all the available NDVI values for the parcels, both from S2 and L8 time series. However, for the L4A crop type processor, the L8 time series was not integrated in the processing:
Because we are working at a country scale and because of the numerous markers that are extracted from the S2 time series, it was already a challenge to optimize the gap filling and markers extraction steps (which are performed at the pixel level) and these steps are already quite long.
The availability of the S1 time series enables to limit the impact of a less dense S2 time series due to a higher cloud coverage so we preferred to put our effort to extract the most of the S1 time series than to integrate the L8 time series (knowing also the specs differences between S2 and L8).
Still, in the Sen2-Agri system, which is a pixel-based crop classification system, it combines S2 and L8 time series to create nice monthly composites, this is what I was confused with during the webinar.
Best regards,
Philippe
Hello Philippe,
Thank you for getting back to me after Webminar. Special credit to Sophie as well.
Appreciate for clarification.
Could you refer the document of time series integration between S1 and L8 if you have one?
So, we should be using Sen2Agri if we want to explore combination time series data of S2 and L8?
Thanks and Regards,
Henry
Hello Henry,
You can refer to these 2 documents that explain how the Sen2-Agri system combine the S2 and L8 time series to create cloud-free reflectance composites:
Still, as explaind above, except for the L4A crop type processor, the other Sen4CAP L4x processors combine the 2 time series (S2 and L8 time series) because they use the biophysical indicators (vegetation status) that are created from both time series.
Best regards,
Philippe
Hello Philippe,
Thanks a lot. I will go through the docs.
Regards,
Henry