Access Pleiades image from BYOC using API process when image has more than 2500X2500 pixels


I’m trying to access images I purchased from Airbus from BYOC using sentinel-hub API process .
it seems like I can’t request some of the images due to the image size (more than 2500X2500 pixels).

My question is, what is the recommended method to access images that their shape is larger than 2500X2500 size, when dealing with BYOC ? is there any way to directly download it without API ? (it’s only 3 images that make this issue)

thanks in advanced :slight_smile:

Hi Reut,

We have actually developed an API for this purpose, when you wish to access images that are larger than 2500x2500 pixels. This is called Async Process API. It was developed for use cases when you wish to process larger images without dealing with tiled results such as in your use case. The differentiation between this and Process API is that instead of instantly returning your requested image, the image is saved to S3 storage where it can then be downloaded by yourself.

I would encourage you to read the documentation, it is very similar to Process API, except that the results are not immediate (although still very fast). You can even try it out in the Request Builder application. An important note to make is that you are required to have AWS S3 storage that is configured correctly with Sentinel Hub services (this is documented on the Async Process API page).

Whilst the API is currently in beta, but you should be able to use it no problem :slight_smile:

I hope that this meets your needs, but if you have any more questions, then let us know and we’ll be happy to help.

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Hi William,

thank you for your answer :slight_smile:
So, in case I don’t have AWS user, I can’t access it with any other API?

Hi Reut,

You are correct, if you are not an AWS user, currently, you can’t use the Async Process API.

An alternative would be to use the Large Area Utilities functionality in the Sentinel Hub Python package. This helps you by splitting your large area of interest into smaller bounding boxes.

Another alternative is to access and download the original imagery archive using the Third Party Data Import API. This is documented in our API documentation here.

If you need help with either method, then we’ll be happy to help.

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Hi @william.ray

thank you for your answer.
I have opened the tutorial for API and I’m a bit confused.
I need to access Airbus Pleiades collection,
I see there examples such as this:


* "data": [
  * {}],

* "links": {
  * "currentToken": "string",

  * "nextToken": "string",

  * "previousToken": "string",

  * "@id": "[](",

  * "next": "[](",

  * "previous": "[]("}


but I’m not sure where should it go to in my python script, and where do I define the BYOC I’m using.
I found there also this example:


* "provider": "AIRBUS",

* "bounds": {
  * "bbox": [],

  * "geometry": {},

  * "properties": {}},

* "data": [
  * {}]


But I’m also not sure where should it go and how can I specify the image I want.

Hi Reut,

If you already have a BYOC collection containing your Pleaides imagery (which I think is the case here) then you can access this via Process API.

When defining your request input parameters you can use the DataCollection.define_byoc inserting your collection_id as a string as the function’s input.

            time_interval=('2022-12-02', '2023-01-02'),          

Does this make sense to you? If not, then happy to guide you further :slight_smile:

Hi @william.ray
thank you for the answer.
I’m a bit confused, because what I need is to get the images that are larger than 2500X2500 pixels , which are already downloaded and are on my BYOC collection.
and I asked if I can access them without AWS and without large area downloading of the data, just directly download them. Not sure how what you shared can help with this ,so if you can explain it will be great :slight_smile:

Hi @reutkeller,

as William mentioned, you can download the original archive using the API function described here.

These same data are also available via BYOC collection.


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