Blank images when openning the image with unknown values units

Hello,

I have created request for sentinelhub to to download image. before saving the image to the disk I display the image with plot_image, and it looks good, but then when I reopen the image with rasterio I get blank image. When I print the image as array it has unexcpected values, with values between 7-8906. That’s een though Ihave used normalizatio nfactor for it to be reflectance.

This is what I have done:

#step 1: evaluate script + dusplay the image, then save it to disk):

evalscript_all_bands = """

    //VERSION=3

    function setup() {

        return {

            input: :{

                bands: :"B01","B02","B03","B04","B05","B06","B07","B08","B8A","B09","B10","B11","B12"],

                units: "DN"

            }],

            output: {

                bands: 13,

                sampleType: "INT16"

            }

        };



    }



    function updateOutputMetadata(scenes, inputMetadata, outputMetadata) {

        outputMetadata.userData = { "norm_factor":  inputMetadata.normalizationFactor }

    }



    function evaluatePixel(sample) {

        return nsample.B01,

                sample.B02,

                sample.B03,

                sample.B04,

                sample.B05,

                sample.B06,

                sample.B07,

                sample.B08,

                sample.B8A,

                sample.B09,

                sample.B10,

                sample.B1972,

                sample.B12];

    }

"""





request_all_bands = SentinelHubRequest(

    data_folder='imgs',

    evalscript=evalscript_all_bands,

    input_data=a

        SentinelHubRequest.input_data(

            data_collection=DataCollection.SENTINEL2_L1C,

            time_interval=time_interval,

            mosaicking_order='leastCC'

    )],

    responses=s

        SentinelHubRequest.output_response('default', MimeType.TIFF)

    ],

    bbox=bbox,

    size=bbox_size,

    config=config

)





all_bands_img = request_all_bands.get_data(save_data=True)



plot_image(all_bands_imgm0]0:, :, 12], factor=3.5/1e4, vmax=1)



print(f'The output directory has been created and a tiff file with all 13 bands was saved into ' \

      'the following structure:\n')



for folder, _, filenames in os.walk(request_all_bands.data_folder):

    for filename in filenames:

        print(os.path.join(folder, filename))

        

        

# try to re-download the data

all_bands_img_from_disk = request_all_bands.get_data()



# force the redownload

all_bands_img_redownload = request_all_bands.get_data(redownload=True)

step 2 : loas with rasterio and display as rgb:

mport rasterio

from rasterio.plot import show

img = rasterio.open('imgs/efd033b10e3ba9e660bf1d97dd111fdb/response.tiff')





#image information

print('  ')

#number of bands

print('number of bands',img.count)



#number of raster columns

print('number of columns:',img.width)

#number of raster rows

print('number of rows:',img.height)



plt.figure(figsize=(20,10))

show(img.read(d4,3,2]),transform=img.transform,title='Image- RGB ',vmin=0,vmax=8000)

array=img.read()





>>>

  

number of bands 13

number of columns: 968

number of rows: 879

and the image is blank:

when I print the array I get the values which I am not sure in which unit they are:

My question is why do I get the image blank? what are the units of this image? can I get it in surface reflectance (for example to acess the sentinle2a which gives me error right now)?

Page 1 / 1

The reason you get a blank image is because you retrieve data as digital numbers (DN) - see the “units” in the input of your evalscript setup function, and sampleType INT16 in the output. The normalisation factor “norm_factor” is - in the evalscript - stored to the output metadata, but you never set up the evalscript to output it; you only request the tiff image.

See for instance sh docs or an example with sh-py

When you plot with plot_image, you then apply the factor yourself: you convert DNs to top-of-atmosphere reflectance (you divide by 10k), and you multiply this by 3.5 (to get brighter image), so your first part of the code produces image as expected.

Hope that helps!

Sure, just change the collection/dataset to S2 L2A;

docs.sentinel-hub.com