Mapping of NiCu–PGE ore hosting ultramafic rocks using airborne and simulated EnMAP hyperspectral imagery, Nunavik, Canada

This study first investigates using AISA airborne hyperspectral imagery (2 m spatial resolution) to produce detailed lithologic maps in a subarctic region (Nunavik, Canada) where ultramafic rock units associated with Ni–Cu-(PGE) mineralization are exposed in the presence of lichen coatings. Twenty A...

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Bibliographic Details
Published in:Remote Sensing of Environment
Main Authors: Rogge, Derek, Rivard, Benoit, Segl, Karl, Grant, Brian, Feng, Jilu
Format: Other Non-Article Part of Journal/Newspaper
Language:unknown
Published: Elsevier 2014
Subjects:
Leitungsbereich DFD
Arctic
Canada
Nunavik
Subarctic
Online Access:https://elib.dlr.de/90135/
https://doi.org/10.1016/j.rse.2014.06.024
Description
Summary:This study first investigates using AISA airborne hyperspectral imagery (2 m spatial resolution) to produce detailed lithologic maps in a subarctic region (Nunavik, Canada) where ultramafic rock units associated with Ni–Cu-(PGE) mineralization are exposed in the presence of lichen coatings. Twenty AISA flight-lines were radiometrically leveled and merged to form a 10 × 20 km mosaic, which then served to generate a simulated spaceborne EnMAP scene (30 m spatial resolution) using the End-to-End Simulation Tool to assess the sensors mapping capabilities. Spatial Spectral Endmember Extraction was used to derive spectral endmembers for the AISA and EnMAP data. Image endmemberswere comparedwith spectralmeasurements of field samples to assess how well key rock typeswere represented. Results showthat the AISA imagery provided a better representation of mafic and ultramafic rock types compared with the EnMAP simulation. Endmembers were then used to map the distribution of geological materials using Iterative Spectral Mixture Analysis. Results indicate the airborne data provided more detailed maps compared with EnMAP simulated data. However, EnMAP data could still discriminate and map broad scale lithological units, specifically mafic and ultramafic rocks. This study demonstrates the feasibility of EnMAP to provide large scale reconnaissance mapping capability of geologic materials over vast subarctic and arctic regions (potentially 30 × 5000 km of imagery per day) using expert knowledge combined with automated spectral analysis methods.

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