Today rare earth elements are of great interest for the global economy. They are of particular importance in modern technology, such as batteries, LCD displays and catalytic converters. Hyperspectral imagers, like the Earth Observing-1 Hyperion and the future environmental mapping and analysis program (EnMAP) bear a potential to identify rare earth element enriched zones in hardly accessible terrains on Earth. Moreover, it is a brilliant technology for monitoring exploration with regard to environmental pollution and protection of local communities. Hence, a fast and accurate geological prospection algorithm using highly spectrally resolved satellite and airborne images is necessary. Since a lot of competing absorptions (e.g. vegetation, iron oxides and atmospheric water) take place in the VNIR spectral range and the shape of rare earth element absorption bands are usually similar to the shape of noise, a detection of Rare Earth Elements is hampered.

Imaging spectroscopy is a widely used tool in mineral exploration today where exploration companies offer the full service package to their clients (data acquisition, preprocessing and product delivery). These exploration projects rely mainly on airborne imaging spectrometers such as Hymap, AISA or HySpex. This data is usually scarce and expensive and may not be available to academic research. The only operational spaceborne imaging spectrometer that covers the full spectral range from the visible to the shortwave infrared is Hyperion aboard EO-1, which has been providing data for over a decade now. New and advanced spaceborne imaging spectrometers such as the Environmental Mapping and Analysis Program (EnMAP) will provide new data for research in the field of imaging spectroscopy for mineral exploration. This study presents a comparison of the mapping capabilities between the Hyperion and EnMAP sensors, on the basis of simulated EnMAP data. This is shown with an example from a porphyry copper complex in southern Namibia (Haib River). Results from multispectral sensors (Landsat-8 OLI, EO-1 ALI and simulated data from the next generation Sentinel-2) are shown to illustrate their potential to map the gossan-outcrops at the Haib River Complex using the Iron Feature Depth (IFD).

Imaging spectroscopy is a widely used tool in mineral exploration today where exploration companies offer the full service package to their clients: (data acquisition, preprocessing and product delivery). These exploration projects rely mainly on airborne imaging spectrometers such as Hymap, AISA or HySpex. This data is usually scarce and expensive and may not be available to academic research. The only operational spaceborne imaging spectrometer that covers the full spectral range from the visible to the shortwave infrared is Hyperion aboard EO-1, which has been providing data for over a decade now. New and advanced spaceborne imaging spectrometers such as the Environmental Mapping and analysis Program (EnMAP) will provide new data for research in the field of imaging spectroscopy for mineral exploration. This study presents a comparison of the mapping capabilities between the Hyperion and EnMAP sensors, on the basis of simulated EnMAP data. This is shown with an example from a porphyry copper complex in southern Namibia (Haib River). In addition to that results from multispectral sensors (Landsat-8 OLI, EO-1 ALI and simulated data from the next generation Sentinel-2) are shown to illustrate their potential to map the gossan-outcrops at the Haib River Complex using the Iron Feature Depth (IFD).

Hyperspectral imaging spectroscopy offers a broad range of spatial applications that are primarily based on the foregoing identification of surface cover materials. In this context, the future hyperspectral sensor EnMAP will provide a new standard of highly qualitative imaging spectroscopy data from space that enables spatiotemporal monitoring of surface materials. The high SNR of EnMAP offers the possibility to differentiate and to identify minerals that are showing characteristic absorption features as a 30 m x 30 m spatial mixture in the visible, the near infrared and the short wave infrared range (0.4 - 2.5 micrometre). For this purpose, spectral mixture analysis (SMA) approaches are traditionally used. However, these approaches lack in transferability, repeatability and inclusion of sensor characteristics. Additionally, they rely on image-based and randomly detected endmembers as well as on in situ or laboratory spectra that are not spatially stable in case of an image-based extraction and are assumed to be spectrally pure. In this work, a new framework is proposed that addresses these limitations considering the EnMAP sensor characteristics. It is named EnMAP Geological Mapper - EnGeoMAP. It consists of several new and adapted approaches to identify spectrally homogeneous regions. In parallel, minerals are identified and semiquantified by a se-nsor-related and knowledge-based fitting approach. Supplementary outputs are abundance, classification, homogeneity and uncertainty maps. First results show that the proposed approach offers 100% percent repeatability and gains an identification error for minerals of about 2 percent on average for different studies. In this work, an approach is proposed that aims on spectroscopic mineral modelling by image synthesis that might be applied for geological mapping.

Values of measured chlorophyll (HPLC=High Pressure Liquid Chromatography) are the mean concentrations of each sampling point from 5 to 30 m depth. For the OC2 chl-a calculations, the least clouded acquisitions in 2001 (2001/07/19) and 2002 (2002/07/20) were chosen. Note the considerable chl-a overestimation caused by the influences of terrigenous input in case 2 waters.