Fractional Cover is a remote sensing algorithm which measures the photosynthetic, non-photosynthetic and bare earth components of a Landsat image.

This repository implements Fractional Cover as used by Digital Earth Australia for the production of the Fractional Cover Data Product. The implementation is Python, with the core algorithm in Fortran.

Data production is either by a command line application that runs on the NCI, or a Virtual Product class run by Datacube Alchemist on AWS.

The easiest way to install Fractional Cover is:

pip install --extra-index-url=https://packages.dea.ga.gov.au/ fc

This package includes the compiled Fortran extensions to run about 15 times faster than the Python+scipy version you get by default without a Fortran compiler.

The first time you try to use gadi PBS commands from VDI, you will need to run:

$ remote-hpc-cmd init

See http://vdi.nci.org.au/help#heading=h.u1kl1j7vdt16 for more details.

You will also need to setup datacube to work from VDI and gadi.

$ ssh gadi "cat .pgpass" >> ~/.pgpass
$ chmod 0600 ~/.pgpass

See http://geoscienceaustralia.github.io/digitalearthau/connect/nci_basics.html for full details.

The Fractional Cover application works in 2 parts:

1. Creating the task list
2. Check for unexpected existing files - these were most likely created during an run that did not successfully finish.
3. Submit the job to gadi.

To run fractional cover:

$ module use /g/data/v10/public/modules/modulefiles/
$ module load dea

This will list the available app configs:

$ datacube-fc list
ls5_fc_albers.yaml
ls7_fc_albers.yaml
ls8_fc_albers.yaml

To submit the job to gadi, the datacube-fc app has a the datacube-fc submit command: This command kick off two stage PBS job

Stage 1 (Generate task file):

The task-app machinery loads a config file, from a path specified on the command line, into a dict.

If dry is enabled, a dummy DatasetType is created for tasks generation without indexing the product in the database. If dry run is disabled, generate tasks into file and queue PBS job to process them.

Stage 2 (Run):

During normal run, following are performed:

1. Tasks (loadables (nbart,ps,dsm) + output targets) shall be yielded for dispatch to workers.
2. Load data
3. Run FC algorithm
4. Attach metadata
5. Write output files and
6. Finally index the newly created FC output files

If dry run is enabled, application only prepares a list of output files to be created and does not record anything in the database.

$ qstat -u $USER

$ qcat 7517348.gadi-pbs | head

$ qcat 7517348.gadi-pbs | tail

$ qps 7517348.gadi-pbs

The config file (eg. ls5_fc_albers.yaml) specifies the app settings, and is found in the module.

You will need to check the folder of the latest dea module:

ls /g/data/v10/public/modules/dea/<YYYYMMDD>/lib/python3.6/site-packages/fc/config

The config file lists the output location and file_path_template``, as shown in this snippet:

source_type: ls5_nbar_albers
output_type: ls5_fc_albers

description: Landsat 5 Fractional Cover 25 metre, 100km tile, Australian Albers Equal Area projection (EPSG:3577)
product_type: fractional_cover

location: '/g/data/fk4/datacube/002/'
file_path_template: 'LS5_TM_FC/{tile_index[0]}_{tile_index[1]}/LS5_TM_FC_3577_{tile_index[0]}_{tile_index[1]}_{start_time}_v{version}.nc'

So here the output files are saved to /g/data/fk4/datacube/002/FC/LS5_TM_FC/<tile_index>/*.nc

Specify a template string used to name the output files. Uses the python format() string syntax, with the following placeholders available:

For example:

file_path_template: '{y}_{x}/LS_PQ_COUNT_3577_{y}_{x}_{epoch_start:%Y-%m-%d}_{epoch_end:%Y-%m-%d}.nc'

Will output filenames similar to:

10_15/LS_PQ_COUNT_3577_10_15_2010-01-01_2011-01-01.nc

This repository is licensed under the Apache License 2.0. See the LICENSE file in this repository for details.

Geoscience Australia developers:

Joshua Sixsmith [email protected]

Jeremy Hooke [email protected]

Damien Ayers [email protected]

Duncan Gray [email protected]

Algorithm developer:

Peter Scarth [email protected]