For documentation: https://ocgis.readthedocs.io/en/latest/
For additional project information: http://www.earthsystemcog.org/projects/openclimategis/
For questions or to file a bug report, please create a GitHub issue.
OpenClimateGIS (OCGIS) is a Python package designed for geospatial manipulation, subsetting, computation, and translation of spatiotemporal datasets stored in local NetCDF files or files served through THREDDS data servers. OpenClimateGIS has a straightforward, request-based API that is simple to use yet complex enough to perform a variety of computational tasks. The software is built entirely from open source packages.
OpenClimateGIS supports many file formats and NetCDF metadata conventions:
- Climate & Forecast (CF) Grid
- Unstructured Grid (UGRID)
- SCRIP
- ESMF Unstructured
- GDAL-supported vector formats (ESRI Shapefiles, File Geodatabases, GeoPackage, GeoJSON, etc.)
- Comma-Separated Value (CSV)
- Subsetting (intersects and intersection) of climate datasets by bounding box, Shapely geometries, or shapefiles (city centroid, river reach, a single county or watershed, state boundaries).
- Time and level range subsetting. Also allows for arbitrary label-based slicing.
- Single or multi-dataset requests (concatenation).
- Area-weighted aggregation (spatial averaging) to selection geometries.
- Handles CF-based coordinate systems with full support for coordinate transformations (including the rotated pole coordinate system)
- Geometry wrapping and unwrapping to maintain logically consistent longitudinal domains.
- Polygon, line, and point geometric abstractions.
- ESMPy regridding
- Access to local NetCDF data or data hosted remotely on a THREDDS (OPeNDAP protocol) data server. Only the piece of data selected by an area-of-interest is transferred from the remote server.
- Stream climate data to multiple formats.
- Extensible converter framework to add custom formats.
- Automatic generation of request metadata.
- Push data to a familiar format to perform analysis or keep the data as NumPy arrays, perform analysis, and dump to a supported format.
- Extensible computational framework for arbitrary inclusion of NumPy-based calculations.
- Apply computations to entire data arrays or temporal groups.
- Computed data may be streamed to any supported formats.