Polymetallic mineralization prospectivity modelling using multi-geospatial data in logistic regression: The Diapiric Zone, Northeastern Algeria

Abstract

Prospecting and exploring minerals present major challenges in
tectonically complex regions for sustainable development as in
Northeastern Algeria. This area is promising for its mineral potential,
especially the metallogenic province ‘The Diapiric Zone’. This
study concerns mapping and predicting potential polymetallic
mineralization locations by integration of remote sensing, gravity,
and magnetic datasets. Several enhancement and processing
methods have been applied on Landsat8_OLI and ASTER_1T
remote sensed data to reduce uncertainty for achieving the best
detection of hydrothermal alteration zones and lithological mapping.
Furthermore, the Centre for Exploration Targeting grid analysis
technique, the contact occurrence density and entropy
orientation tools were employed on ground-gravity and aeromagnetic
data to understand and visualize the pathways for hydrothermal
fluids circulation of mineral deposits. The polymetallic
mineralization prospective areas were produced using a logistic
regression model on the resulting multifactor. High zones of leadzinc
cover most the area that has been confirmed by field
investigation.

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