Geophysical Survey (GS) Data Standard and Open-source Python Toolbox (GSPy)
Standardizing data and sharing open-source tools helps the geophysical community increase the long-term impact of its data.
Geophysical data help us understand the physical properties of Earth’s subsurface. For example, measurements of Earth’s magnetic and gravitational fields are considered geophysical data. There are many other types of geophysical data, each with their own data formats and structures. The lack of community standards for these datasets limits the long-term impact and use of these high-value investments.
The USGS developed a new Geophysical Survey (GS) data standard and an open-source Python toolbox (GSPy) to help people use the data standard. The GS data standard uses the established NetCDF Climate and Forecast conventions. The initial standard is for large airborne geophysical data such as electromagnetic, magnetic, and radiometric surveys. Future developments will expand its use to other datatypes.
Early-on, there was a lot of interest within the USGS in using the GS standard, with several USGS data releases following the new format. Recently, private geophysical acquisition and software companies have reached out to learn more about the GS standard. These companies are considering how they can incorporate the standard into their workflows.
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Journal article: https://doi.org/10.3389/feart.2022.907614
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GSPy software and documentation: https://doi.org/10.5066/P9XNQVGQ
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Example USGS data release: https://doi.org/10.5066/P93SY9LI
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