I'm a beginner in SeaDAS looking to batch process atmospheric correction using l2gen on Landsat images. I see a related post (below), but I'm not up to speed on how to use shell or Python with SeaDAS.
Is there a way to use the "ilist" input in the .par file to point to a list of input folders, each containing bands for an image?
https://oceancolor.gsfc.nasa.gov/forum/oceancolor/topic_show.pl?pid=27992;hl=batch%20process
batch processing in l2gen
batch processing in l2gen
Are you familiar with the multilevel processor (mlp)? I believe it might be useful for you.
You can run it within the SeaDAS GUI from the OCSSW menu, once you've installed the OCSSW processors. However, it can also be run from the command line, which would allow you to set up scripts to run it and automate into batch processing. To run it, you enter a command something like:
The program expects a parameter (par) file with a format similar to other OCSSW programs, but with some differences. Each par file must have a [main] section and a section for the final program you want to run. Special processing for intermediate programs needs to be specified also; otherwise, the mlp will use the intermediate program's defaults.
Below is a simple example par file - using MODIS data, but hopefully it helps you get started - which shows using input data files in different subdirectories of the directory from which the program is run:
From the command line, you can get more information about the mlp with:
If you need more help, please let us know!
Matt
You can run it within the SeaDAS GUI from the OCSSW menu, once you've installed the OCSSW processors. However, it can also be run from the command line, which would allow you to set up scripts to run it and automate into batch processing. To run it, you enter a command something like:
> multilevel_processor.py NAME_OF_MLP_PAR_FILEThe program expects a parameter (par) file with a format similar to other OCSSW programs, but with some differences. Each par file must have a [main] section and a section for the final program you want to run. Special processing for intermediate programs needs to be specified also; otherwise, the mlp will use the intermediate program's defaults.
Below is a simple example par file - using MODIS data, but hopefully it helps you get started - which shows using input data files in different subdirectories of the directory from which the program is run:
[main]
ifile=data1/A2012114175000.L1B_LAC,data2/A2012114172500.L1B_LAC
[l2gen]
l2prod=chlor_a
From the command line, you can get more information about the mlp with:
multilevel_processor.py --helpIf you need more help, please let us know!
Matt