Reprojecting Modis data using python

[arnabp893]

Hello everyone,
I want to reproject/georeference multiple Modis L2 (single variable, such as chl_a) data in a folder using python. any code or guidance will be helpful.

[gnwiii]

ESA SNAP snappy uses the jpy java-python bridge and can map MODIS level-2 files, but the mapped data will be a Java object so there is consierable overhead if you want the mapped data in Python.

For native Python with MODIS data: https://python-geotiepoints.readthedocs.io/en/latest/#example-aqua-terra-modis-data

[arnabp893]

Thank you for the reply.

I am probably gonna do them manually in seadas. In that case, which format will be useful to save the reprojected data?
There are multiple options such as netcdf-cf, netcdf BEAM etc. which one will be easily readable by python?

[gnwiii]

NetCDF4-CF has good metadata support and supports internal compression. BEAM DIMAP is useful as an intermediate format when subsequent processing will be done using SNAP or SeaDAS 8, but is not as well supported by 3rd party software and does not support internal compression. Modern CPU's do internal compression with very low impact on most workflows, and significant space savings which is often useful (in large organizations, using compression saves time filling out requests for increased disk space and then waiting for the next tranch of funds).

[OB.DAAC - SeanBailey]

If you are not rigid on requiring python to do the reprojection (and assuming you are interested in the L2 data from the OB.DAAC), the processing code available with SeaDAS includes several programs that can be tied together to generate mapped outputs. The workflow is to bin the L2 data to L3, then map the L3 to your favorite projection. ...and there is a wrapper script (written in python - cleverly called mapgen) that puts it all together.

Sean

[sym_knull]

Thank You very much!!