Tutorials for using PGC data, tools, and workflows
PGC Dynamic STAC API
Python Jupyter Notebook Workflow Tutorial
ArcGIS Pro and QGIS Desktop Tutorials
View the Project on GitHub PolarGeospatialCenter/pgc-code-tutorials
This repo includes tutorials for using Polar Geospatial Center (PGC) data and tools in geospatial workflows.
STAC - Spatio Temporal Asset Catalog is a standard for organizing geospatial data for convenient access. Essentially, it is a set of GeoJSON-formatted metadata describing location and time for geospatial information, with links to the actual data, so tools can query by spatial and temporal filters and retrieve just the data necessary for your project. The STAC spec website includes useful tutorials for getting familiar with using these data tools.
We use the dynamic STAC API to enable queryable access to PGC data products via python or desktop GIS applications. The tutorials in the dynamic_stac_api folder in this repo demonstrate basic functionality for interacting with the STAC API using built-in tools for ArcGIS and QGIS desktop software and with a python jupyter notebook.
To jump in directly, the dynamic STAC API link is: https://stac.pgc.umn.edu/api/v1/
The STAC API provides access to the public DEM data that PGC produces from high resolution satellite imagery, specifically for the polar regions through the ArcticDEM and Reference Elevation Model of Antarctica (REMA) products, as well as a subset of the EarthDEM data for the area around the Great Lakes region. These are continent-scale, high resolution (2m), repeat coverage elevation models published as time-stamped DEM Strips and (mostly) seamless Mosaics. You can find out more about this elevation data on our website.