@article{MielkeRogassBoescheetal.2016,
  author    = {Mielke, Christian and Rogass, Christian and B{\"o}sche, Nina Kristine and Segl, Karl and Altenberger, Uwe},
  title     = {EnGeoMAP 2.0-Automated Hyperspectral Mineral Identification for the German EnMAP Space Mission},
  series = {Remote sensing},
  volume    = {8},
  journal   = {Remote sensing},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {2072-4292},
  doi       = {10.3390/rs8020127},
  pages     = {392 -- 414},
  year      = {2016},
  abstract  = {Algorithms for a rapid analysis of hyperspectral data are becoming more and more important with planned next generation spaceborne hyperspectral missions such as the Environmental Mapping and Analysis Program (EnMAP) and the Japanese Hyperspectral Imager Suite (HISUI), together with an ever growing pool of hyperspectral airborne data. The here presented EnGeoMAP 2.0 algorithm is an automated system for material characterization from imaging spectroscopy data, which builds on the theoretical framework of the Tetracorder and MICA (Material Identification and Characterization Algorithm) of the United States Geological Survey and of EnGeoMAP 1.0 from 2013. EnGeoMAP 2.0 includes automated absorption feature extraction, spatio-spectral gradient calculation and mineral anomaly detection. The usage of EnGeoMAP 2.0 is demonstrated at the mineral deposit sites of Rodalquilar (SE-Spain) and Haib River (S-Namibia) using HyMAP and simulated EnMAP data. Results from Hyperion data are presented as supplementary information.},
  language  = {en}
}
@article{MielkeMuediPapenfussetal.2016,
  author    = {Mielke, Christian and Muedi, T. and Papenfuss, Anne and B{\"o}sche, Nina Kristine and Rogass, C. and Gauert, C. D. K. and Altenberger, Uwe and de Wit, M. J.},
  title     = {Multi- and hyperspectral spaceborne remote sensing of the Aggeneys base metal sulphide mineral deposit sites in the Lower Orange River region, South Africa},
  series = {South African Journal of Geology},
  volume    = {119},
  journal   = {South African Journal of Geology},
  publisher = {Geological Society of South Africa},
  address   = {Marshalltown},
  issn      = {1012-0750},
  doi       = {10.2113/gssajg.119.1.63},
  pages     = {63 -- 76},
  year      = {2016},
  abstract  = {New tools and algorithms for geological femote Sensing are developed and verified at test sites throughout the world in preparation of the German hyperspectral satellite Mission (EnMAP), which is an Environmental Mapping and Analysis Program. The aggeneys Cu-Pb-Zn deposit, situated in the arid north western part of South Africa, represents a unique field laboratory for testing these new tools. Here spaceborne hyperspectral data covering the Swartberg, and hyperspectral spaceborne data can be demonkrated, such as the Iron Feature Depth index (IFD), which has recently been proposed for mine waste mapping in the North West Province of South Africa and for gossan detection at Haib River in South Namibia. The work presented here explores the potential of the IFD for gossan mapping and characterization at Gamsberg and Big Syncline, from EO-1 ALI and Landsat-8 OLI data together with mineral maps from expert systems such as the United States Geological Survey (USGS) Material Identification and Characterization Algorithm (MICA), and first results from EnMAPs EnGeoMAP algorithm. Field spectroscopic measurements and field sampling were carried out to validate and calibrate the results from the expert systems and the IFD. This ground truthing is a necessary complementary step to link the results from the expert systems and the IFD to in-situ field spectroscopy. Future mineral exploration initiatives may benefit from the techniques described here, because they can significantly narrow the expensive, exploration activities such as hyperspectral airborne data, field activities and drilling, by identifying the most promising mineral anomalies in an area from the spaceborne data.},
  language  = {en}
}