Awesome

TRAIN

The Toolbox for Reducing Atmospheric InSAR Noise – TRAIN – is developed in an effort to include current state of the art tropospheric correction methods into the default InSAR processing chain. Initial development was performed at the University of Leeds. The toolbox consists of a combination of command line scripts, shell scripts, and matlab scripts. More information on software is provided in Chapter 3. TRAIN is independent of the used InSAR processor, as long as the data convention is followed. The toolbox is compatible with the StaMPS software. Further initial efforts have been put to include TRAIN into the default -rate processing chain.

 We welcome community contributions and request users to contribute back to the repo. 

CITATION

We request TRAIN users to reference our publication of TRAIN:

• Bekaert, D.P.S., Walters, R.J., Wright, T.J., Hooper, A.J., and Parker, D.J. (2015c), Statistical comparison of InSAR tropospheric correction techniques, Remote Sensing of Environment, doi: 10.1016/j.rse.2015.08.035

In addition, also cite the original methods where needed. E.g. for our power-law method this is:

• Bekaert, D.P.S., Hooper, A.J., and Wright, T.J. (2015a), A spatially-variable power-law tropospheric correction technique for InSAR data, JGR, doi:10.1029/2014JB011558

LICENSE

TRAIN is distributed under a GNU GPL licence.

Acknowledgement

Thanks to Richard J. Walters, Hannes Bathke, Simran Sangha, Tim J. Wright, Andy J. Hooper, Doug J. Parker, Zhenhong Li, the Leeds InSAR group, COMET members, and community for their feebback and contributions.