About exporting to ENVI format?

[Shellyin]

Hi,
L1C product was exported to ENVI format, and the spectral value become larger(above1000). But it(the reflectance) is between 0.0-1.0 in SNAP, I want to know how it is converted during the exporting process. Is there any instructions? And, what the VALUE in the second figure represent? still reflectance? a little strange

spectral value in SNAP

spectral value in ENVI

THANKS

[ABraun]

The values in the second picture are the reflectance (0-1) * 10.000

This is part of the answer:

Error in GLCM calculation

Hello Andreas. Just a remark: there is no difference between AWS S2 data and SciHub data, except the packing/grouping of files. From an “original” S2 product, the SNAP S2 reader knows how to convert DN to reflectance (of type float), whilst if you open just a jp2 file (a single band), the SNAP JP2 reader doesn’t know how to do that and you only have DN.

This means that the data is basically stored as an integer (0-5000 or something) but in SNAP it is interpreted as reflectance (float values between 0-1) using the available metadata.

If you want to export it you need the corresponding quantification value (1.000 in the past, 10.000 now). So dividing your data by 10.000 should be the solution.

DC to reflectance

Hi I think you can use a simple bandmath like “B2/1000” and save as floating point data. Please have a look at the algorithm document “https://sentinel.esa.int/web/sentinel/technical-guides/sentinel-2-msi/level-1c/algorithm”. Reflectance, often between 0 and 1, is converted into integer values, in order to preserve the dynamic range of the data by applying a fixed coefficient (1000 by default). Regards Ralf

DC to reflectance

Be aware that the quantization of reflectance values in L1C product will change in future products. Reflectances will be coded in the [0, 10000] range instead of the actual [0 1000] that you can observe in current products on scihub. A metadata value gives you this information in : Level-1C_User_Product/General_Info/Product_Image_Characteristics/QUANTIFICATION_VALUE

[Shellyin]

Great! THANKS!
“The values in the second picture are the reflectance (0-1) * 10.000”. Another question occurs to me. If I want to use its radiance or original DN values information, what should I do?

[ABraun]

Open the band maths for the corresponding layer (right click)
Enter band / 10000 (while band is your data) and save it to a new band. Then, export the band in a format which allows for decimal values (float).

[Shellyin]

Hi, THANKS!
I applied your method using 3 bands in band maths, and when I was about to export the calculated new bands but unluckily to find NO DATA STORAGE(red circle, but I can display them in SNAP ). I still tried to export data but really nothing in the exported file. And I found the format of new bands(read rectangle) was different from previous bands.
Sorry to trouble you again

[ABraun]

this is because band maths only calculates virtual rasters unless the checkbox ‘Virtual’ is unchecked. This means that you can open and view them based on their logical or mathematical expression but they are not saved on your hard drive.
To convert the bands into a permanent raster, right click on the corresponding band, select ‘convert band’ and save your product with File > Save product.

[Shellyin]

You solve my problem! THANKS!!

[Ganjug]

Dear SNAP-users,

I have same problem here. I divided the band value by 10000. But the result was almost same. The minimium value is minus and the difference between min and max value is too high.

In C2RCC atmospheric correction processor, min=31 and max=78. What I have to do? I’m using empirical algorithm (regretion with in-situ data) for detecting Chl-a concentration after Sen2Cor processing. I couldn’t find my error. Please help me.

[marpet]

It is difficult to trace what you have done and where the error could be, because multiple processing steps have been done.
Maybe you first have a look at the sen2core results and check of those values are too high too.
If they look good, then check How you calculate the NDCI.

[ABraun]

Maybe negative numbers were also introduced when resampling the data. Did you reproject the raster, for example?

[Ganjug]

@ABraun

negative numbers were also introduced when resampling the data. Did you reproject the raster, for example?

Dear Abraun,

I resampled and subset them. Should I reproject? I faced again with minus values after the C2X processing

[ABraun]

The type of resampling surely affects the nature of the values, especially the largest and smallest ones. The fraction of negative values in your data is minimal, so I wonder if it’s a problem at all.

Reprojection would lead to further resampling, thus chaning your data even more. You can check if different resampling methods lead to other results. As Marco said, if the values are negative from the beginning, then it’s not a matter of processing.