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Miscellanea Geographica

Regional Studies on Development

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CiteScore 2016: 0.40

SCImago Journal Rank (SJR) 2016: 0.227
Source Normalized Impact per Paper (SNIP) 2016: 0.404

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2084-6118
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Assessment of Imaging Spectroscopy for rock identification in the Karkonosze Mountains, Poland

Monika Mierczyk
  • Department of Geoinformatics, Cartography and Remote Sensing, Faculty of Geography and Regional Studies, University of Warsaw, Poland
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Bogdan Zagajewski
  • Department of Geoinformatics, Cartography and Remote Sensing, Faculty of Geography and Regional Studies, University of Warsaw, Poland
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Anna Jarocińska
  • Department of Geoinformatics, Cartography and Remote Sensing, Faculty of Geography and Regional Studies, University of Warsaw, Poland
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Roksana Knapik
Published Online: 2016-04-20 | DOI: https://doi.org/10.1515/mgrsd-2015-0016

Abstract

Based on laboratory, field and airborne-acquired hyperspectral data, this paper aims to analyse the dominant minerals and rocks found in the Polish Karkonosze Mountains. Laboratory spectral characteristics were measured with the ASD FieldSpec 3 spectrometer and images were obtained from VITO’s Airborne Prism EXperiment (APEX) scanner. The terrain is covered mainly by lichens or vascular plants creating significant difficulties for rock identification. However, hyperspectral airborne imagery allowed for subpixel classifications of different types of granites, hornfels and mica schist within the research area. The hyperspectral data enabled geological mapping of bare ground that had been masked out using three advanced algorithms: Spectral Angle Mapper, Linear Spectral Unmixing and Matched Filtering. Though all three methods produced positive results, the Matched Filtering method proved to be the most effective. The result of this study was a set of maps and post classification statistical data of rock distribution in the area, one for each method of classification.

Keywords: Rock identification; Imaging Spectroscopy; APEX hyperspectral airborne imagery data; Spectral Angle Mapper; Linear Spectral Unmixing; Matched Filtering

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About the article

Received: 2015-05-20

Accepted: 2015-08-20

Published Online: 2016-04-20

Published in Print: 2016-03-01


Citation Information: Miscellanea Geographica, ISSN (Online) 2084-6118, DOI: https://doi.org/10.1515/mgrsd-2015-0016.

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© by Monika Mierczyk. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0

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