@inproceedings{Kaufmann2006,
  author    = {Kaufmann, Hermann},
  title     = {Abbildende Spektrometrie},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-7104},
  year      = {2006},
  abstract  = {Interdisziplin{\"a}res Zentrum f{\"u}r Musterdynamik und Angewandte Fernerkundung Workshop vom 9. - 10. Februar 2006},
  language  = {de}
}
@misc{BoescheRogassLubitzetal.2017,
  author    = {B{\"o}sche, Nina Kristine and Rogass, Christian and Lubitz, Christin and Brell, Maximilian and Herrmann, Sabrina and Mielke, Christian and Tonn, Sabine and Appelt, Oona and Altenberger, Uwe and Kaufmann, Hermann},
  title     = {Hyperspectral REE (Rare Earth Element) mapping of outcrops},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-400171},
  pages     = {27},
  year      = {2017},
  abstract  = {In this study, an in situ application for identifying neodymium (Nd) enriched surface materials that uses multitemporal hyperspectral images is presented (HySpex sensor). Because of the narrow shape and shallow absorption depth of the neodymium absorption feature, a method was developed for enhancing and extracting the necessary information for neodymium from image spectra, even under illumination conditions that are not optimal. For this purpose, the two following approaches were developed: (1) reducing noise and analyzing changing illumination conditions by averaging multitemporal image scenes and (2) enhancing the depth of the desired absorption band by deconvolving every image spectrum with a Gaussian curve while the rest of the spectrum remains unchanged (Richardson-Lucy deconvolution). To evaluate these findings, nine field samples from the Fen complex in Norway were analyzed using handheld X-ray fluorescence devices and by conducting detailed laboratory-based geochemical rare earth element determinations. The result is a qualitative outcrop map that highlights zones that are enriched in neodymium. To reduce the influences of non-optimal illumination, particularly at the studied site, a minimum of seven single acquisitions is required. Sharpening the neodymium absorption band allows for robust mapping, even at the outer zones of enrichment. From the geochemical investigations, we found that iron oxides decrease the applicability of the method. However, iron-related absorption bands can be used as secondary indicators for sulfidic ore zones that are mainly enriched with rare earth elements. In summary, we found that hyperspectral spectroscopy is a noninvasive, fast and cost-saving method for determining neodymium at outcrop surfaces},
  language  = {en}
}
@article{BoescheRogassLubitzetal.2015,
  author    = {B{\"o}sche, Nina Kristine and Rogass, Christian and Lubitz, Christin and Brell, Maximilian and Herrmann, Sabrina and Mielke, Christian and Tonn, Sabine and Appelt, Oona and Altenberger, Uwe and Kaufmann, Hermann},
  title     = {Hyperspectral REE (Rare Earth Element) Mapping of Outcrops-Applications for Neodymium Detection},
  series = {Remote sensing},
  volume    = {7},
  journal   = {Remote sensing},
  number    = {5},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {2072-4292},
  doi       = {10.3390/rs70505160},
  pages     = {5160 -- 5186},
  year      = {2015},
  abstract  = {In this study, an in situ application for identifying neodymium (Nd) enriched surface materials that uses multitemporal hyperspectral images is presented (HySpex sensor). Because of the narrow shape and shallow absorption depth of the neodymium absorption feature, a method was developed for enhancing and extracting the necessary information for neodymium from image spectra, even under illumination conditions that are not optimal. For this purpose, the two following approaches were developed: (1) reducing noise and analyzing changing illumination conditions by averaging multitemporal image scenes and (2) enhancing the depth of the desired absorption band by deconvolving every image spectrum with a Gaussian curve while the rest of the spectrum remains unchanged (Richardson-Lucy deconvolution). To evaluate these findings, nine field samples from the Fen complex in Norway were analyzed using handheld X-ray fluorescence devices and by conducting detailed laboratory-based geochemical rare earth element determinations. The result is a qualitative outcrop map that highlights zones that are enriched in neodymium. To reduce the influences of non-optimal illumination, particularly at the studied site, a minimum of seven single acquisitions is required. Sharpening the neodymium absorption band allows for robust mapping, even at the outer zones of enrichment. From the geochemical investigations, we found that iron oxides decrease the applicability of the method. However, iron-related absorption bands can be used as secondary indicators for sulfidic ore zones that are mainly enriched with rare earth elements. In summary, we found that hyperspectral spectroscopy is a noninvasive, fast and cost-saving method for determining neodymium at outcrop surfaces.},
  language  = {en}
}
@article{MielkeBoescheRogassetal.2015,
  author    = {Mielke, Christian and B{\"o}sche, Nina Kristine and Rogass, Christian and Kaufmann, Hermann and Gauert, Christoph},
  title     = {New geometric hull continuum removal algorithm for automatic absorption band detection from spectroscopic data},
  series = {Remote sensing letters : an official journal of the Remote Sensing and Photogrammetry Society},
  volume    = {6},
  journal   = {Remote sensing letters : an official journal of the Remote Sensing and Photogrammetry Society},
  number    = {2},
  publisher = {Routledge, Taylor \& Francis Group},
  address   = {Abingdon},
  issn      = {2150-704X},
  doi       = {10.1080/2150704X.2015.1007246},
  pages     = {97 -- 105},
  year      = {2015},
  abstract  = {Modern imaging spectrometers produce an ever-growing amount of data, which increases the need for automated analysis techniques. The algorithms employed, such as the United States Geological Survey (USGS) Tetracorder and the Mineral Identification and Characterization Algorithm (MICA), use a standardized spectral library and expert knowledge for the detection of surface cover types. Correct absorption feature definition and isolation are key to successful material identification using these algorithms. Here, a new continuum removal and feature isolation technique is presented, named the 'Geometric Hull Technique'. It is compared to the well-established, knowledge-based Tetracorder feature database together with the adapted state of the art techniques scale-space filtering, alpha shapes and convex hull. The results show that the geometric hull technique yields the smallest deviations from the feature definitions of the MICA Group 2 library with a median difference of only 8nm for the position of the features and a median difference of only 15\% for the feature shapes. The modified scale-space filtering hull technique performs second best with a median feature position difference of 16nm and a median difference of 25\% for the feature shapes. The scale-space alpha hull technique shows a 23nm median position difference and a median deviation of 77\% for the feature shapes. The geometric hull technique proposed here performs best amongst the four feature isolation techniques and may be an important building block for next generation automatic mapping algorithms.},
  language  = {en}
}
@article{SeglGuanterKaufmannetal.2010,
  author    = {Segl, Karl and Guanter, Luis and Kaufmann, Hermann and Schubert, Josef and Kaiser, Stefan and Sang, Bernhard and Hofer, Stefan},
  title     = {Simulation of spatial sensor characteristics in the context of the EnMAP Hyperspectral mission},
  issn      = {0196-2892},
  doi       = {10.1109/Tgrs.2010.2042455},
  year      = {2010},
  abstract  = {The simulation of remote sensing images is a valuable tool for defining future Earth observation systems, optimizing instrument parameters, and developing and validating data-processing algorithms. A scene simulator for optical Earth observation data has been developed within the Environmental Mapping and Analysis Program (EnMAP) hyperspectral mission. It produces EnMAP-like data following a sequential processing approach consisting of five independent modules referred to as reflectance, atmospheric, spatial, spectral, and radiometric modules. From a modeling viewpoint, the spatial module is the most complex. The spatial simulation process considers the satellite-target geometry, which is adapted to the EnMAP orbit and operating characteristics, the instrument spatial response, and the sources of spatial nonuniformity (keystone, telescope distortion and smile, and detector coregistration). The spatial module of the EnMAP scene simulator is presented in this paper. The EnMAP spatial and geometric characteristics will be described, the simulation methodology will be presented in detail, and the capability of the EnMAP simulator will be shown by illustrative examples.},
  language  = {en}
}
@article{MielkeBoescheRogassetal.2014,
  author    = {Mielke, Christian and B{\"o}sche, Nina Kristine and Rogass, Christian and Kaufmann, Hermann and Gauert, Christoph and de Wit, Maarten},
  title     = {Spaceborne mine waste mineralogy monitoring in South Africa, applications for modern push-broom missions: Hyperion/OLI and EnMAP/Sentinel-2},
  series = {Remote sensing},
  volume    = {6},
  journal   = {Remote sensing},
  number    = {8},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {2072-4292},
  doi       = {10.3390/rs6086790},
  pages     = {6790 -- 6816},
  year      = {2014},
  abstract  = {Remote sensing analysis is a crucial tool for monitoring the extent of mine waste surfaces and their mineralogy in countries with a long mining history, such as South Africa, where gold and platinum have been produced for over 90 years. These mine waste sites have the potential to contain problematic trace element species (e. g., U, Pb, Cr). In our research, we aim to combine the mapping and monitoring capacities of multispectral and hyperspectral spaceborne sensors. This is done to assess the potential of existing multispectral and hyperspectral spaceborne sensors (OLI and Hyperion) and future missions, such as Sentinel-2 and EnMAP (Environmental Mapping and Analysis Program), for mapping the spatial extent of these mine waste surfaces. For this task we propose a new index, termed the iron feature depth (IFD), derived from Landsat-8 OLI data to map the 900-nm absorption feature as a potential proxy for monitoring the spatial extent of mine waste. OLI was chosen, because it represents the most suitable sensor to map the IFD over large areas in a multi-temporal manner due to its spectral band layout; its (183 km x 170 km) scene size and its revisiting time of 16 days. The IFD is in good agreement with primary and secondary iron-bearing minerals mapped by the Material Identification and Characterization Algorithm (MICA) from EO-1 Hyperion data and illustrates that a combination of hyperspectral data (EnMAP) for mineral identification with multispectral data (Sentinel-2) for repetitive area-wide mapping and monitoring of the IFD as mine waste proxy is a promising application for future spaceborne sensors. A maximum, absolute model error is used to assess the ability of existing and future multispectral sensors to characterize mine waste via its 900-nm iron absorption feature. The following sensor-signal similarity ranking can be established for spectra from gold mining material: EnMAP 100\% similarity to the reference, ALI 97.5\%, Sentinel-2 97\%, OLI and ASTER 95\% and ETM+ 91\% similarity.},
  language  = {en}
}
@article{BrosinskyFoersterSegletal.2014,
  author    = {Brosinsky, Arlena and F{\"o}rster, Saskia and Segl, Karl and Kaufmann, Hermann},
  title     = {Spectral fingerprinting: sediment source discrimination and contribution modelling of artificial mixtures based on VNIR-SWIR spectral properties},
  series = {Journal of soils and sediments : protection, risk assessment and remediation},
  volume    = {14},
  journal   = {Journal of soils and sediments : protection, risk assessment and remediation},
  number    = {12},
  publisher = {Springer},
  address   = {Heidelberg},
  issn      = {1439-0108},
  doi       = {10.1007/s11368-014-0925-1},
  pages     = {1949 -- 1964},
  year      = {2014},
  abstract  = {Knowledge of the origin of suspended sediment is important for improving our understanding of sediment dynamics and thereupon support of sustainable watershed management. An direct approach to trace the origin of sediments is the fingerprinting technique. It is based on the assumption that potential sediment sources can be discriminated and that the contribution of these sources to the sediment can be determined on the basis of distinctive characteristics (fingerprints). Recent studies indicate that visible-near-infrared (VNIR) and shortwave-infrared (SWIR) reflectance characteristics of soil may be a rapid, inexpensive alternative to traditional fingerprint properties (e.g. geochemistry or mineral magnetism). To further explore the applicability of VNIR-SWIR spectral data for sediment tracing purposes, source samples were collected in the Isabena watershed, a 445 km(2) dryland catchment in the central Spanish Pyrenees. Grab samples of the upper soil layer were collected from the main potential sediment source types along with in situ reflectance spectra. Samples were dried and sieved, and artificial mixtures of known proportions were produced for algorithm validation. Then, spectral readings of potential source and artificial mixture samples were taken in the laboratory. Colour coefficients and physically based parameters were calculated from in situ and laboratory-measured spectra. All parameters passing a number of prerequisite tests were subsequently applied in discriminant function analysis for source discrimination and mixing model analyses for source contribution assessment. The three source types (i.e. badlands, forest/grassland and an aggregation of other sources, including agricultural land, shrubland, unpaved roads and open slopes) could be reliably identified based on spectral parameters. Laboratory-measured spectral fingerprints permitted the quantification of source contribution to artificial mixtures, and introduction of source heterogeneity into the mixing model decreased accuracies for some source types. Aggregation of source types that could not be discriminated did not improve mixing model results. Despite providing similar discrimination accuracies as laboratory source parameters, in situ derived source information was found to be insufficient for contribution modelling. The laboratory mixture experiment provides valuable insights into the capabilities and limitations of spectral fingerprint properties. From this study, we conclude that combinations of spectral properties can be used for mixing model analyses of a restricted number of source groups, whereas more straightforward in situ measured source parameters do not seem suitable. However, modelling results based on laboratory parameters also need to be interpreted with care and should not rely on the estimates of mean values only but should consider uncertainty intervals as well.},
  language  = {en}
}