Advanced search in data hub (contains - intersects)

Hi there,

does someone know if there is a possibility to search for data which contain the region of interest?? not just intersecting…
Thank you in advance for your help!

Michi

You can use the OData or OpenSearch queries to do programmatic selections via command line tools. Check out

https://scihub.copernicus.eu/userguide/5APIsAndBatchScripting

You can even drill down to individual granules, check their cloud mask (GML), and decide whether you want to download a single granules, or even a single band [or even a subset…].

GL

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thanks a lot for your answer glemoine!!!

Regarding your question about the possibility of querying only products containing the region of interest, the answer is yes, it is actually supported by the SciHub. It’s just undocumented. Since the SciHub seems to follow the OpenSearch Geo extension specification you can also use contains and disjoint in addition to the default intersects spatial relation parameters described there.
That is, you can do
https://scihub.copernicus.eu/dhus/search?q=polarisationmode:VV AND footprint:"Contains(POLYGON((-4.53 29.85, 26.75 29.85, 26.75 46.80,-4.53 46.80,-4.53 29.85)))"
instead of the default
https://scihub.copernicus.eu/dhus/search?q=polarisationmode:VV AND footprint:"Intersects(POLYGON((-4.53 29.85, 26.75 29.85, 26.75 46.80,-4.53 46.80,-4.53 29.85)))", for example.

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Hi glemoine, reading your answer I stumbled upon your last sentence: “[or even a subset…].” Did you mean that it is possible to download just a subset (a crop) of a Sentinel product, without having to download the whole file ?

I know that this can be achieved for Sentinel-2 images on AWS, thanks to gdal vsicurl driver. But I didn’t manage to get it work on scihub, hence I cannot use it for Sentinel-1. It’s sad because Sentinel-1 products are very large.

You can also download single bands (for S2). Download the XML metadata, parse the URLs for individual files. You could, in principle, also get subsets inside an image, if you open an image file directly from URL (e.g. using python/gdal). In general, this is relatively easy in python. For S1, it would be possible to extract individual polarization bands from the ZIP archive, but I am not sure whether that is very useful.