Dear Sushil Khatri,

QGIS could be helpful.

To get started, try this: https://www.youtube.com/watch?v=XAClP8ERmsA

Dear Sushil,

In my opinion, you can use python its one of the quick and easy tool for conversion. Here I have attached one of the research article from which you may benefit:

Article Evaluation of Variable-Infiltration Capacity Model and MODIS...

I hope it helps.

Cheers,

Ankur

Dear Sushil,

Surprised no one mentioned this, but pyModis is a pretty popular Python library to work with MODIS imagery which allows bulk downloading, reprojecting, format conversion, etc. even though development is not as active as it used to be.

http://www.pymodis.org/

Otherwise,, when working in Python you really can't go wrong with GDAL and h5py:

https://gdal.org/api/python.html

https://www.h5py.org/

Dear Sushil,

If you are interested to get started in R, which has a powerful libraries to work with netCDF and HDF type of datasets, the below course might help you a lot. It really worked for me before.

https://pjbartlein.github.io/REarthSysSci/index.html

https://developers.google.com/s/results/earth-engine/datasets?hl=en&q=MODIS%20Terra%20AOD%20data

Several programming languages now have geo packages that can help you explore, through Hierarchical Data Format Files (HDF). In the case of the R program you can explore the data via ncdf4: This package works for both HDF4 and HDF5. rgdal. For the python platform, pyhdf package will help you out. Similarly, MATLAB also has its hdf read packages.

However, If you wish to work on bulk data sets from satellites for say >10 years, the processing in way fatser using shell scripting and FORTRAN.

You can also process hdf file format using ENVI software ...

Using the MCTK plugin under ENVI and IDL might be a useful tool.

Sushil Khatri, Very good question and thank you to all contributors.