Nan output of sharpen in sen-et processing

Dear SNAP devoloper,

I have been following the sen-et tutorial to obtain evotranspiration at 20m resolutions ( All the steps are well achaived, however, in the SHARPEN LTS step the output of the Data mining sharpener is nan.
Any idea what might be going wrong?

I really appreciate your help

Thanks in advances,

Hi Caleb,

Thanks for your question. I’m not sure if the developers of the plugin are around here and can answer your question. And I here the first time of this plugin. But it is great to see 3rd party plugins.
Unfortunately, on the page is no option is provided to contact the team.
@mengdahl Do you know who should be contacted?

Dear Marco

Thank you for your prompt response, I look forward to hearing from you if anyone else knows.


in WRAP to TEMPLATE, what is the source image and template image?

Hi Calebdb,
Are you sure that there is spatial overlap between the high and low resolution images? Also, please provide more details, e.g. what settings do you use, what messages are printed out, etc.

I’m also having the same issue of NaN values of LST_SHARPENING output.
No error message is there.
Followings are my input and parameters.
Why the sharpened image is Nan?

Could you also double check that all the input layers overlap and display properly in SNAP. Also what machine are you running this on? The sharpening module can be quite resource intensive when run for a large area (e.g. S2 tile). See section 3.1 of the Sen-ET user manual for recommended system requirements.

This happened with me recently, and the cause was that the lai from the sentinel 3 preprocessing was empty, check results from previous steps to be sure the input is all right.

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Dear @radosuav

Thanks for your advice. Unfortunately, I have not been able to fix the problem. There is overlap between both areas. I turn up the sharpening processing input I used to drive, maybe it could help. There is also the output message in a txt file.

I really appreciate your help in this field.



Hi Calebdb, it looks like you are messing up the inputs to the sharpening algorithm. For example, you are using the same file for LST and LST quality mask. Have a look at figure 2.2 and section of the user manual.