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GMES4Mining - Description of a flooding process in mining areas using spectral indices on multioral landsat imagery

Millán, Virginia Elena García LU ; Teuwsen, Sebastian and Pakzad, Kian (2013) In Photogrammetrie, Fernerkundung, Geoinformation 2013(5). p.427-436
Abstract

The R&D project GMES4Mining aims to support particular tasks within the different phases of a mining life cycle. Within this project one task concentrates on vegetation monitoring in order to detect damages caused by mining. In Germany several mining districts have been exploited for a long time. Mining areas are associated with certain environmental hazards, such as surface subsidence and flooding. The change in substrate compaction due to mineral extraction provokes surface subsidence, down to the point that the surface can reach the groundwater level. This phenomenon provokes negative effects on vegetation, which can be observed using remote sensing. A temporal series of Landsat images from 1999 to 2012 has been used to detect... (More)

The R&D project GMES4Mining aims to support particular tasks within the different phases of a mining life cycle. Within this project one task concentrates on vegetation monitoring in order to detect damages caused by mining. In Germany several mining districts have been exploited for a long time. Mining areas are associated with certain environmental hazards, such as surface subsidence and flooding. The change in substrate compaction due to mineral extraction provokes surface subsidence, down to the point that the surface can reach the groundwater level. This phenomenon provokes negative effects on vegetation, which can be observed using remote sensing. A temporal series of Landsat images from 1999 to 2012 has been used to detect temporal changes in vegetation by calculating 3 spectral indices. The spectral indices relate to vegetation greenness, leaf pigments and water content. The aim of this study is to detect early indications and to monitor the process of flooding in abandoned mining sites, to prevent environmental and civil hazards. Moreover, it is investigated whether these indices are appropriate to detect flooded areas and to describe the vegetation succession, once a flooded area is drained. It is expected that this methodology will be applicable to the future Sentinel-2 data, in order to monitor and prevent hazards in mining areas.

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author
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type
Contribution to journal
publication status
published
subject
keywords
Flooding, Mining areas, Multioral, Spectral vegetation and water indices
in
Photogrammetrie, Fernerkundung, Geoinformation
volume
2013
issue
5
pages
10 pages
publisher
E. Schweizerbartsche Verlagsbuchhandlung
external identifiers
  • scopus:84886037162
ISSN
1432-8364
DOI
10.1127/1432-8364/2013/0189
language
English
LU publication?
no
id
95af7f01-57ff-4890-a00e-3842b2275839
date added to LUP
2019-06-12 12:09:22
date last changed
2020-01-13 01:59:43
@article{95af7f01-57ff-4890-a00e-3842b2275839,
  abstract     = {<p>The R&amp;D project GMES4Mining aims to support particular tasks within the different phases of a mining life cycle. Within this project one task concentrates on vegetation monitoring in order to detect damages caused by mining. In Germany several mining districts have been exploited for a long time. Mining areas are associated with certain environmental hazards, such as surface subsidence and flooding. The change in substrate compaction due to mineral extraction provokes surface subsidence, down to the point that the surface can reach the groundwater level. This phenomenon provokes negative effects on vegetation, which can be observed using remote sensing. A temporal series of Landsat images from 1999 to 2012 has been used to detect temporal changes in vegetation by calculating 3 spectral indices. The spectral indices relate to vegetation greenness, leaf pigments and water content. The aim of this study is to detect early indications and to monitor the process of flooding in abandoned mining sites, to prevent environmental and civil hazards. Moreover, it is investigated whether these indices are appropriate to detect flooded areas and to describe the vegetation succession, once a flooded area is drained. It is expected that this methodology will be applicable to the future Sentinel-2 data, in order to monitor and prevent hazards in mining areas.</p>},
  author       = {Millán, Virginia Elena García and Teuwsen, Sebastian and Pakzad, Kian},
  issn         = {1432-8364},
  language     = {eng},
  number       = {5},
  pages        = {427--436},
  publisher    = {E. Schweizerbartsche Verlagsbuchhandlung},
  series       = {Photogrammetrie, Fernerkundung, Geoinformation},
  title        = {GMES4Mining - Description of a flooding process in mining areas using spectral indices on multioral landsat imagery},
  url          = {http://dx.doi.org/10.1127/1432-8364/2013/0189},
  doi          = {10.1127/1432-8364/2013/0189},
  volume       = {2013},
  year         = {2013},
}