Integration of hyperspectral and magnetic data for geological characterization of the Niaqornarssuit ultramafic complex in West-Greenland

• Published in: Remote Sensing
• Main Authors: Kuras, A., Heincke, B.H., Salehi, S., Mielke, C., Köllner, N., Rogass, Christian, Altenberger, U., Burud, I.
• Format: Article in Journal/Newspaper
• Language: English
• Published: MDPI, Basel 2022
• Subjects: geological remote sensing; magnetics; hyperspectral; hyperspectral-magnetic integration; ultramafic complex; Greenland; iron; susceptibility; imaging spectroscopy; data fusion; Niaqornarssuit
• Online Access: https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=26744; https://doi.org/10.3390/rs14194877

The integration of imaging spectroscopy and aeromagnetics provides a cost-effective and promising way to extend the initial analysis of a mineral deposit. While imaging spectroscopy retrieves surface spectral information, magnetic responses are used to determine magnetization at both shallower and greater depths using 2D and 3D modeling. Integration of imaging spectroscopy and magnetics improves upon knowledge concerning lithology with magnetic properties, enhances understanding of the geological origin of magnetic anomalies, and is a promising approach for analyzing a prospective area for minerals having a high iron-bearing content. To combine iron diagnostic information from airborne hyperspectral and magnetic data, we (a) used an iron absorption feature ratio to model pseudo-magnetic responses and compare them with the measured magnetic data and (b) estimated the apparent susceptibility along the surface by some equivalent source modeling, and compared them with iron ratios along the surface. For this analysis, a Modified Iron Feature Depth index was developed and compared to the surface geochemistry of the rock samples in order to validate the spectral information of iron. The comparison revealed a linear increase in iron absorption feature depths with iron content. The analysis was performed by empirically modeling the statistical relationship between the diagnostic absorption features of hyperspectral (HS) image spectra of selected rock samples and their corresponding geochemistry. Our results clearly show a link between the spectral absorption features and the magnetic response from iron-bearing ultra/-mafic rocks. The iron absorption feature ratio of Fe3+/Fe2+ integrated with aeromagnetic data (residual magnetic anomaly) allowed us to distinguish main rock types based on physical properties. This separation matches the lithology of the Niaqornarssuit complex, our study area in West Greenland.