@article{ec23cbe753d64343a23ad7fcb3519d62,
title = "Mapping ultramafic complexes using airborne imaging spectroscopy and spaceborne data in Arctic regions with abundant lichen cover, a case study from the Niaqornarssuit complex in South West Greenland",
abstract = "This study investigates the usage of HyMAP airborne hyperspectral and Sentinel-2, ASTER and Landsat-8 OLI spaceborne multispectral data for detailed mapping of mineral resources in the Arctic. The EnMAP Geological Mapper (EnGeoMAP) and Iterative Spectral Mixture Analysis (ISMA) approaches are tested for mapping of mafic-ultramafic rocks in areas covered by abundant lichen. Using the Structural Similarity Index Measure (SSIM), the output classification results from airborne data are quantitatively compared to the available geological map and to the HyMAP reference data in case of using spaceborne dataset. Results demonstrate the capability of both airborne and spaceborne data to provide large-scale reconnaissance mapping of geologic materials over vast arctic regions where field access is limited. The distributions of three ultramafic units (dunite, peridotite, pyroxenite) and one mafic unit (gabbro) are mapped based on analyzing specific visible and near-infrared and short-wave-infrared spectral features. The extent of peridotite and dunite units mapped using both approaches is consistent with geological map, whereas pyroxenite abundance maps show different patterns in their distribution as compared to the geological map. The results suggest that EnGeoMAP method has a better performance than ISMA method for mapping the dunite unit, whilst ISMA performs better for mapping peridotite and pyroxenite rocks.",
keywords = "arctic, lichen, mineral mapping, non-invasive, Spectroscopy, ultramafic, unmixing",
author = "Sara Salehi and Christian Mielke and Christian Rogass",
note = "Funding Information: This work was supported by the Geocenter Danmark [2-2014]. The authors would like to thank the three anonymous reviewers whose comments have greatly improved this manuscript. The Geocenter Denmark is thanked for funding the Geological Remote Sensing PhD project of which this work is a part. Further, Geological Survey of Denmark and Greenland is gratefully acknowledged for providing the airborne hyperspectral dataset. We sincerely thank the 21st North Company for access to the rock samples and expedition reports. Agnieszka Kuras and the entire group in the German Research Centre for Geosciences are thanked for their support with the XRF measurements and sample preparation. Funding Information: The authors would like to thank the three anonymous reviewers whose comments have greatly improved this manuscript. The Geocenter Denmark is thanked for funding the Geological Remote Sensing PhD project of which this work is a part. Further, Geological Survey of Denmark and Greenland is gratefully acknowledged for providing the airborne hyperspectral dataset. We sincerely thank the 21st North Company for access to the rock samples and expedition reports. Agnieszka Kuras and the entire group in the German Research Centre for Geosciences are thanked for their support with the XRF measurements and sample preparation. Publisher Copyright: {\textcopyright} 2020, {\textcopyright} 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.",
year = "2020",
doi = "10.1080/22797254.2020.1760733",
language = "English",
volume = "53",
pages = "156--175",
journal = "European Journal of Remote Sensing",
issn = "1129-8596",
publisher = "Associazione Italiana di Telerilevamento",
number = "1",
}