Aeromagnetic and Gamma-Ray Spectrometric Data for Geological Mapping: A Python-Based Automated Workflow Applied to the Djelfa Region, Northern Algeria
DOI:
https://doi.org/10.22399/ijcesen.5312Keywords:
Aeromagnetic, Gamma-ray spectrometry, EMD micro-levelling, Geological mapping, Northern Algeria, Python; Open-source workflowAbstract
This study presents an automated open-source Python-based workflow for the processing and interpretation of airborne geophysical data, applied to the Djelfa region of northern Algeria (R=[4.75°–6.0°E / 34.0°–34.75°N]). The dataset comprises 144,623 measurement points from a legacy airborne survey covering both total magnetic intensity (TMI) and gamma-ray spectrometric channels (K, Th, U). A complete quality control and correction chain was implemented including median statistical levelling, EMD-based micro-levelling, altitude correction and empirical calibration, following IAEA (2003) and Groun et al. (2018). Radiometric crossover RMS errors were reduced by 49.8%, 54.3% and 60.8% for K, Th and U respectively. The processed data were gridded and interpreted through magnetic enhancement filters (HGM, TDR) and spectrometric analysis (RGB ternary composite, K-means classification with five units) to constrain and refine the existing 1:200,000 geological map of the region. TMI gradient analysis delineated major geological contacts consistent with the regional Atlasic tectonic framework. The entire workflow is implemented using open-source Python libraries (Verde, Harmonica, PyEMD, scikit-learn, Matplotlib) and is fully reproducible.
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