Hi @reutkeller,

Here are a couple of suggestions:

• 
  

  If you download an image from Sentinel Hub service in tiff format the image will be georeferenced. If you download using sentinelhub-py you have an option to save data as shown in this example. This will save the original georeferenced tiff image.

  
  


• 
  

  In memory, sentinelhub-py decodes an image into a normal numpy array without geoinformation. But you also have an instance of sentinelhub.BBox object which was used to request an image from Sentinel Hub service and it defines coordinates and CRS of a downloaded image. Therefore you can collect geo information from it and pass it to rasterio functions. For that the following methods should be useful:

  
  
  • 
    BBox.get_transform_vector to get an affine vector used by most rasterio functions.
  
  
  • 
    BBox.crs.pyproj_crs to transform sentinelhub.CRS object into pyproj.CRS object which is required by rasterio.
  
  

I hope this helps.

Thank you for your answer, it helped a lot.

so now , i’m trying the BBox.crs.pyproj_crs but not sure how to use it as when I run it I get:

bbox.crs.pyproj_crs



>>>

<bound method CRS.pyproj_crs of CRS('4326')>

and ofcurse when I try to save it as raster with rasterio it doesn’t understand it:

import rasterio

from rasterio.transform import from_origin

transform=from_bounds(minx,maxy,pixel_size,pixel_size,ndvi.shapeh0],ndvi.shapeh1])

#crs_img='EPSG:4326'





with rasterio.open('test1.tif', 

                    'w',

                    driver='GTiff',

                    height=ndvi.shapeh0],

                    width=ndvi.shapeh1],

                    count=1,

                    dtype=ndvi.dtype,

                    crs=crss,

                    nodata=None, # change if data has nodata value

                    transform=transform) as dst:

        dst.write(ndvi, 1)



>>>



CRSError: CRS is invalid: <bound method CRS.pyproj_crs of CRS('4326')>

The pyproj_crs is a method, so you should use pyproj_crs().

Cheers,

Matej

Thank you.

and just to make sure I understood correct,

in bbox.get_transform_vector() , How do I know what is the resx and resy? is it based on the image resolution? e.g if I use sentinel2 it will be 10,1973 , or landsat will be 30,30…

I’m asking because when I do it as you mentioned I get weird image:

original image:

img_crs=bbox.crs.pyproj_crs()



transform=bbox.get_transform_vector(10,1973)



transform=rasterio.Affine(-101.7359960059834, 10.0, 0, 20.8312118894487, 0, -10.0) #this equal to the tuple from get_transform_vector





with rasterio.open('test1.tif', 

                    'w',

                    driver='GTiff',

                    height=ndvi.shapeh0],

                    width=ndvi.shapeh1],

                    count=1,

                    dtype=ndvi.dtype,

                    crs=img_crs,

                    nodata=None, # change if data has nodata value

                    transform=transform) as dst:

        dst.write(ndvi, 1)

when I open this image I get this:

so i’m not sure if the problem is resx resy or osmething else.

Thank you for the help

Reut

Be careful of the units. You data is in WGS84 (units are degrees), while you trying to use the resolution in metres.

I have tried to insert the degrees, as I understand, if I use sentinel1image now with 10 meters resolution it should look like this:

trans=bbox.get_transform_vector(0.00009009009009,0.00009009009009)

but still I get it wrong . I believe I miss understood you regard the meters and degrees?

To be honest, I’d be using eo-learn, where ExportToTiff functionality takes care of all these issues.

But if you have a quick look at that code, you will see that it uses width and height (as opposed to resx/resy):

crs = bbox.crs.pyproj_crs()

transform = rasterio.transform.from_bounds(*bbox, width=width, height=height) 

Perhaps you could try that?

Hi,

I am not trying to push my own writing, but perhaps this blog helps you:
https://towardsdatascience.com/geo-referencing-a-figure-as-an-image-fc5e77caa00b

In the post, I try to explain how to handle different coordinate systems, and what the effect of the transformation is.

Kind regards,

Gijs