Color composite on merged satellite images


Is it possible to merge the satellite images comprised within our study area (250 000 km2) in the EO browser? And then to apply color composite/index/custom script on the merged product to finally download it?
Or do we have to download each image and merge them with a GIS software?

Thank you very much!



Hi @zakariazamzami961 ,

Could you please elaborate a bit more on what you’re trying to achieve? Your study area is huge and it does not make sense to merge all images covering your study area to one.

it is “possible”, but with big limitations and as @chung.horng said, not really sensible or usable for any further work and probably not what you need

  • to display the area in EO Browser, the zoom level would be pretty low, so the visualization in EO Browser would be low resolution (for example for Sentinel-2 L2A, far from 10m/pixel)
  • furthermore, the image, downloaded with basic image download (jpg, png formats) or advanced image download (jpg, png, tiff), would not be really useful for further work for the same reason
  • the hi-res print download does allow for specifying the width and height of downloaded image, which results in a higher resolution, but the available formats are only jpg and png, and this option is meant more for big physical prints, cover images (for publishing), not for scientific research
  • the area is larger than the width of the orbit, so data from more than 1 acquisition date would be needed and if non-cloudy data is needed, the dates can also be more spread apart

For scientific research, it would probably make sense to use python and sentinelhub-py (maybe also eo-learn), to split the area to smaller chunks and work on them (and also stitch results to a single “unit” (file / array / matrix / …), if needed).

There is sentinelhub-js, with which you can request data from Sentinel hub directly in web apps or websites.

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Hello @chung.horng ,,

Thank you for your answers!

I am trying to obtain false colour composites to visualize geological features and also index related to water and vegetation in general.

I may look into the option of using python, thanks for the links.

Where can one educate himself about how to implement such py scripts?

Hi @ssh ,

We have a collection of examples where could be a good starting point.