Integrated Multisource Radar and Geophysical Data for Depth-Resolved Structural Analysis and Mineral Prospectivity: DEM, NISAR, BIOMASS, and Aeromagnetic Data

This study introduces a multisource, multiscale approach to delineate structural lineaments and assess mineralization controls in Wadi El-Markh, Central Eastern Desert, Egypt. Four datasets (ALOS PALSAR DEM, NISAR L-band SAR, BIOMASS P-band SAR, and aeromagnetic data) were processed using tailored workflows to extract lineaments at complementary depths, from the surface to deep crustal levels. The AP-DEM workflow employed multi-azimuth hill-shading and directional Prewitt filtering. NISAR data were speckle-denoised before directional filtering of the HH and HV polarizations. BIOMASS data underwent polarimetric decomposition followed by directional filtering. Aeromagnetic data were reduced to the pole, analyzed using power-spectrum for depth estimation and regional–residual separation, and then processed using a CET grid-analysis workflow for lineaments extraction and generation of a Contact Occurrence Density (COD) map. Directional analysis revealed sensor-dependent biases: NISAR HH favored an E-W trend, whereas HV yielded a more isotropic distribution; BIOMASS surface scattering highlighted E-W and N-S trends, whereas volume scattering emphasized NW-SE and NE-SW trends. Aeromagnetic data identified both shallow- and deep-seated structures, with a dominant NW-SE trend. GIS-based fuzzy overlay produced a consensus structural complexity map. Validation against 15 known mining sites showed spatial coincidence rates ranging from 60% (AP-DEM and NISAR HH) to 86.7% (BIOMASS volume scattering and fuzzy overlay) for mining sites falling within high-structural-complexity zones. The results establish a reliable framework for identifying structurally controlled mineralization targets in arid terrains.