I am trying to use the Spectral Unmixing feature in SNAP on a S3 subset. I have created a tab separated csv file using python in several different ways. The csv endmember file uploads successfully and the individual endmembers can be seen in the LSU popup window. However, when I click Run, I get error saying “Matrix is Singular”. I am not sure what this means or how to address the problem.
If I create a tab separated csv file with the same data using Excel the LSU tool runs successfully. I am not sure what difference using python is creating.
I am also having problems with the Endmember file for the unmixing. I exported my endmembers from Envi in ASCII format and then converted it in a tab separated CSV file using Excel and Notepad. It looks like this:
All Endmembers are loaded into the tool
There is only a slider missing in the list of endmembers. If you further step down through the list by the cursor keys you see different spectra highlighted in the graph.
Also, it would be good if you have a different name for each of the endmember.
And you have to make sure that you have more source bands then endmembers.
hi, I’m trying to use spectral unmixing tools in SNAP, I’ve already converted the endmembers file into the csv tab-separated file using excel and notepad, and it looks like this :
thanks, @Marco_EOM , I changed all the endmembers name and It actually worked, but then there was another problem when I tried to Run the product, and it showed like this :
The reason could be that you have moved source product from one location to another.
It is a BEAM-DIMAP product, right?
You might have moved only the *.dim file, but you also must move the *.data directory.
I double-checked the folder .dim and .data. They are located in the same folder. But when I tried to Run the product again, it gave me the same error… I’m really confused now
hi, @Marco_EOM I finally know what the problem is, it is because the stacking layer process that I’ve done before is incomplete and caused an error, and now the problem is solved! thank you.