ABSTRACT:

This workshop covers the geodetic and cartographic foundations for working with satellite data, then introduces Satpy as a Python tool for projecting and georeferencing it. The first part lays out the reference framework: geographic coordinate systems, the geoid, and the role of geodesy. It distinguishes horizontal from vertical datums and contrasts local datums (NAD27, ED50) with geocentric ones (NAD83, WGS84), using a timeline of NAD, WGS, and ITRF realizations to show how datums shift over time. The next section covers projected coordinate systems and the geometry of flattening a curved surface onto a plane, walking through planar, cylindrical, and conical projections with common examples including UTM, State Plane, Web Mercator, Lambert Conformal Conic, and Albers Equal Area Conic. The final section introduces Satpy, an open-source Python library developed by the Pytroll community and used operationally by NOAA, EUMETSAT, and meteorological services. It reads more than 70 satellite file formats, calibrates sensor counts to physical units, builds RGB composites, resamples swath data to arbitrary projections, and exports to GeoTIFF, NetCDF, and PNG, with support for major geostationary and polar-orbiting platforms. An accompanying Jupyter notebook demonstrates these capabilities on real satellite data.

Acknowledgements:
This research was supported by the Cooperative Institute for Research to Operations in Hydrology (CIROH) with funding under award NA22NWS4320003 from the NOAA Cooperative Institute Program. The statements, findings, conclusions, and recommendations are those of the author(s) and do not necessarily reflect the opinions of NOAA.