This repository is a example on how to grid real aerogeophysical data using python. As an example, I'll be using the magnetometric survey "1113 - Projeto Aerogeofísico Sudeste do Mato Grosso" made by the Geological Survey of Brazil, or simply CPRM, which is the acronym for the company's official name in Portuguese.
This data is quite big, in both size, area and number of data points. Because of that, it reflects a good real use case. All the code was done thinking on a real use, so any desktop PC should run this workflow without problems. The notebooks have run time measurements for the most work intensive tasks. Either way, the heaviest tasks (file conversions) do not take more than 3-4 minutes. From data conversion to final interpolation, this workflow takes 7-10 minutes at most.
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File format checking and geometry plot: This notebook previews the file format and create shapefiles with a light (simplified) version of the aeromagnétic survey geometry.
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Convert file format: This notebook convert the decorrugated IGRF reduced magnetic anomaly flight and tie lines dataset to the NPY format for convenience.
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Check acquisiton geometry parameters: Basic checks of flight lines geometry.
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Data decimation: Decimate the data before gridding.
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Linear interpolation: Interpolate the decimated data using linear interpolation.
Figure 1 - Interpolated IGRF corrected magnetic field (WGS 84/UTM 22S).
See the file LICENSE for information on terms & conditions for usage.