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EnGeoMAP 2.0—Automated Hyperspectral Mineral Identification for the German EnMAP Space Mission
Open AccessArticle

Potential of Resolution-Enhanced Hyperspectral Data for Mineral Mapping Using Simulated EnMAP and Sentinel-2 Images

Department of Advanced Interdisciplinary Studies, University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8904, Japan
Department of Electronics and Informatics, Vrije Universiteit Brussel, Pleinlaan 2, Brussels 1050, Belgium
Helmholtz Center Potsdam, GFZ German Research Center for Geosciences, Remote Sensing Section, Telegrafenberg A17, Potsdam 14473, Germany
Author to whom correspondence should be addressed.
Academic Editors: Saskia Foerster, Véronique Carrere, Michael Rast, Karl Staenz, Magaly Koch and Prasad S. Thenkabail
Remote Sens. 2016, 8(3), 172;
Received: 11 December 2015 / Revised: 22 January 2016 / Accepted: 17 February 2016 / Published: 24 February 2016
Spaceborne hyperspectral images are useful for large scale mineral mapping. Acquired at a ground sampling distance (GSD) of 30 m, the Environmental Mapping and Analysis Program (EnMAP) will be capable of putting many issues related to environment monitoring and resource exploration in perspective with measurements in the spectral range between 420 and 2450 nm. However, a higher spatial resolution is preferable for many applications. This paper investigates the potential of fusion-based resolution enhancement of hyperspectral data for mineral mapping. A pair of EnMAP and Sentinel-2 images is generated from a HyMap scene over a mining area. The simulation is based on well-established sensor end-to-end simulation tools. The EnMAP image is fused with Sentinel-2 10-m-GSD bands using a matrix factorization method to obtain resolution-enhanced EnMAP data at a 10 m GSD. Quality assessments of the enhanced data are conducted using quantitative measures and continuum removal and both show that high spectral and spatial fidelity are maintained. Finally, the results of spectral unmixing are compared with those expected from high-resolution hyperspectral data at a 10 m GSD. The comparison demonstrates high resemblance and shows the great potential of the resolution enhancement method for EnMAP type data in mineral mapping. View Full-Text
Keywords: image fusion; mineral mapping; EnMAP; Sentinel-2 image fusion; mineral mapping; EnMAP; Sentinel-2
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Yokoya, N.; Chan, J.C.-W.; Segl, K. Potential of Resolution-Enhanced Hyperspectral Data for Mineral Mapping Using Simulated EnMAP and Sentinel-2 Images. Remote Sens. 2016, 8, 172.

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