Hyperspectral Data

The TERRA hyperspectral data pipeline processes imagery from hyperspectral camera, and ancillary metadata. The pipeline converts the "raw" ENVI-format imagery into netCDF4/HDF5 format with (currently) lossless compression that reduces their size by ~20%. The pipeline also adds suitable ancillary metadata to make the netCDF image files truly self-describing. At the end of the pipeline, the files are typically [ready for xxx]/[uploaded to yyy]/[zzz].


Software dependencies
The pipeline currently depends on three pre-requisites: _[_netCDF Operators (NCO)]( Python netCDF4.
Pipeline source code
Once the pre-requisite libraries above have been installed, the pipeline itself may be installed by checking-out the TERRAREF computing-pipeline repository. The relevant scripts for hyperspectral imagery are:
The pipeline works with input from any location (directories, files, or stdin). Supply the raw image filename(s) (e.g., meat_raw), and the pipeline derives the ancillary filename(s) from this (e.g., meat_raw.hdr, meat_metadata.json). When specifying a directory without a specifice filename, the pipeline processes all files with the suffix "_raw".
shmkdir ~/terrarefcd ~/terrarefgit clone [email protected]:terraref/computing-pipeline.gitgit clone [email protected]:terraref/documentation.git
Run the Hyperspectral Pipeline -i ${DATA}/terraref/foo_raw -O ${DATA}/ -I /projects/arpae/terraref/raw_data/lemnatec_field -O /projects/arpae/terraref/outputs/lemnatec_field