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Using other cloud storage instead of Amazon S3 Bucket (Batch processing API)

  • April 26, 2024
  • 5 replies
  • 305 views

I already start to use your new example of the Batch process API to prepare the Sentinel 1 images for larger areas. I have a question which would appreciate it if you could guide in this regard:

Is it possible to use other cloud storage instead of Amazon S3 Bucket or not? if so, could please let me know how is the configuration?

Kind regards

5 replies

Hi,

Cool to hear that you are looking into Batch Processing. I find it makes life so much easier for processing large areas. Currently the process only supports Amazon object storage. There are future plans for adding other cloud storage options, but I don’t have a date for this.


Hi,

is there any update about this? is it still not possible to use other sources ? (beside S3, for example, GCS)


In Batch processing, you would use the same Evalscript as a normal API request.

There are some very basic Sentinel-1 evalscript examples in the API documentation, as well as more complex ones in the custom scripts repository for diverse applications.


Hi,

Thank you for the info - Yes, I found out that for the large area eo-learn uses more processing units and I think Batch processing could help me to save some.

I am gonna use it for Sentinel-1 and honestly, I could not find suitable documentation regarding the evalscript. I thought you maybe can help me in this regard. I am gonna calculate different aggregation mode (mean, max etc.) but I cannot find anything about it.

Thank you in advance for your help 🙂

 


Not yet, but still on our time-line.
That said, it should be pretty simple to write a lambda function, in combination with SNS, that would copy the files from AWS to GCP and then delete the file…