aus-ref-clim-data-nci / shapefiles

Collection of shapefiles commonly used by the Australian climate research community
Apache License 2.0
3 stars 2 forks source link

Shapefiles

The Australian Community Reference Climate Data Collection @ NCI shapefile collection contains the following:

/g/data/ia39/aus-ref-clim-data-nci/shapefiles/data/aus_local_gov/

/g/data/ia39/aus-ref-clim-data-nci/shapefiles/data/aus_states_territories/

/g/data/ia39/aus-ref-clim-data-nci/shapefiles/data/australia/

/g/data/ia39/aus-ref-clim-data-nci/shapefiles/data/broadacre_regions/

/g/data/ia39/aus-ref-clim-data-nci/shapefiles/data/NCRA_Marine_region/

/g/data/ia39/aus-ref-clim-data-nci/shapefiles/data/ncra_regions/

/g/data/ia39/aus-ref-clim-data-nci/shapefiles/data/NCRA_regions_coastal_waters_GDA94/

/g/data/ia39/aus-ref-clim-data-nci/shapefiles/data/nrm_regions/

/g/data/ia39/aus-ref-clim-data-nci/shapefiles/data/river_regions/

Software

Most programming languages have libraries for reading in shapefiles and selecting geographic data points that fall within them.

Python

If your workflow is based around Python and xarray, you can typically read a shapefile using geopandas. The resulting GeoDataFrame can then be passed to a function from the regionmask or clisops library to select grid points from an xarray data set that fall within the shape/s.

See python_tutorial.ipynb for a worked example using regionmask and the shapefiles in this collection.

Other languages

TODO.