Experimental impact cratering: A summary of the major results of the MEMIN research unit

This paper reviews major findings of the Multidisciplinary Experimental and Modeling Impact Crater Research Network (MEMIN). MEMIN is a consortium, funded from 2009 till 2017 by the German Research Foundation, and is aimed at investigating impact cratering processes by experimental and modeling approaches. The vision of this network has been to comprehensively quantify impact processes by conducting a strictly controlled experimental campaign at the laboratory scale, together with a multidisciplinary analytical approach. Central to MEMIN has been the use of powerful two-stage light-gas accelerators capable of producing impact craters in the decimeter size range in solid rocks that allowed detailed spatial analyses of petrophysical, structural, and geochemical changes in target rocks and ejecta. In addition, explosive setups, membrane-driven diamond anvil cells, as well as laser irradiation and split Hopkinson pressure bar technologies have been used to study the response of minerals and rocks to shock and dynamic loading as well as high-temperature conditions. We used Seeberger sandstone, Taunus quartzite, Carrara marble, and Weibern tuff as major target rock types. In concert with the experiments we conducted mesoscale numerical simulations of shock wave propagation in heterogeneous rocks resolving the complex response of grains and pores to compressive, shear, and tensile loading and macroscale modeling of crater formation and fracturing. Major results comprise (1) projectile–target interaction, (2) various aspects of shock metamorphism with special focus on low shock pressures and effects of target porosity and water saturation, (3) crater morphologies and cratering efficiencies in various nonporous and porous lithologies, (4) in situ target damage, (5) ejecta dynamics, and (6) geophysical survey of experimental craters.     

Classifier ensembles for land cover mapping using multitemporal SAR imagery

SAR data are almost independent from weather conditions, and thus are well suited for mapping of seasonally changing variables such as land cover. In regard to recent and upcoming missions, multitemporal and multi-frequency approaches become even more attractive. In the present study, classifier ensembles (i.e., boosted decision tree and random forests) are applied to multi-temporal C-band SAR data, from different study sites and years. A detailed accuracy assessment shows that classifier ensembles, in particularly random forests, outperform standard approaches like a single decision tree and a conventional maximum likelihood classifier by more than 10% independently from the site and year. They reach up to almost 84% of overall accuracy in rural areas with large plots. Visual interpretation confirms the statistical accuracy assessment and reveals that also typical random noise is considerably reduced. In addition the results demonstrate that random forests are less sensitive to the number of training samples and perform well even with only a small number. Random forests are computationally highly efficient and are hence considered very well suited for land cover classifications of future multifrequency and multitemporal stacks of SAR imagery.     

Significance of the remotely sensed thermal infrared measurements obtained over a citrus orchard

In this work we have developed a theoretical model that helps the interpretation of the remotely sensed thermal infrared measurements carried out over citrus orchards. A detailed analysis of the different factors which take part in the definition of the effective emissivity and temperature (observation height, viewing angle, type of soil, dimensions and separation between orange trees) is made. The model was validated under vertical observation in a citrus orchard during seven nights. In this situation we have determined that the model performs to an accuracy of about 1%.     

A GIS-based glacier inventory for the Antarctic Peninsula and the South Shetland Islands —A first case study on King George Island

The aim of the international project “Global Land Ice Measurements from Space (GLIMS)” headed by the US Geological Survey is to establish a world wide glacier inventory based on satellite imagery. This data set will form a first digital baseline study for future glacier monitoring. The presented GIS-based glacier inventory for King George Island is a case study for the area of the Antarctic Peninsula. In the database of the glacier inventory topographic information, specific glaciological parameters as well as metadata will be included. The topographic data consists of drainage basin limits, basin areas, altitudinal ranges, perimeters and mean lengths. Glaciological data sets should comprise information on glacier retreat in different periods, glacier velocities, ice thickness and bedrock topography as well as derived parameters. Modelled and measured mass balance parameters could be included as additional data layers. In particular, these metadata records must comprise background information on data accuracy and data sources and should be compatible with a future data model for the King George Island GIS (KGIS). Three examples illustrate that the GLIMS database will not only contain information valuable for glaciological applications, but also other environmental studies on the island will benefit from this standardised remote sensing data sets. Therefore, a very close link between the data models of KGIS and GLIMS has to be established to enable these synergisms. Finally, better access to historic aerial photography would enable a continuous record of glacier retreat from the beginning of the 1950's onward.     

High Resolution Köppen‐Geiger Classifications of Paleoclimate Simulations

The development and application of an algorithm to compute Köppen‐Geiger climate classifications from the Coupled Model Intercomparison Project (CMIP) and Paleo Model Intercomparison Project (PMIP) climate model simulation data is described in this study. The classification algorithm was applied to data from the PMIP III paleoclimate experiments for the Last Glacial Maximum, 21k years before present (yBP), Mid‐Holocene (6k yBP) and the Pre‐Industrial (0k yBP, control run) time slices. To infer detailed classification maps, the simulation datasets were interpolated to a higher resolution. The classification method presented is based on the application of Open Source Software, and the implementation is described with attention to detail. The source code and the exact input data sets as well as the resulting data sets are provided to enable the application of the presented approach.     

Dissociative excitation of SO2 by controlled electron impact

The fragmentation of SO₂ following dissociative electron impact excitation has been studied under single collision conditions for incident electron energies up to 500 eV. The emission spectrum in the far v.u.v. spectral range (450–1100Å) shows many features arising from excited neutral oxygen and ionized oxygen and sulphur fragments. Absolute emission cross sections have been measured for the most intense lines and the maximum values were found to range from 1–12 × 10^?19 cm² with an uncertainty of approx. ± 35%. Dissociation mechanisms are discussed and in some cases the dissociation path could be uniquely identified. The striking differences between the v.u.v. emission spectrum produced by single step dissociation of SO₂ and the spectra emitted by the plasma torus around Jupiter are discussed.     

The Nuclear Stellar Cluster in NGC 1068

We present new near-infrared integral field spectroscopy and adaptive optics imaging of the nucleus of NGC 1068. Using the stellar CO absorption features in the H and K bands, we have identified a moderately extincted stellar core centered on the nuclear position and of intrinsic size ~50 pc. We show that this nuclear stellar core is probably 5-16 × 108 years in age and contributes at least 7% of the total nuclear luminosity of ~1 × 1011 L⊙. This revised version was published online in July 2006 with corrections to the Cover Date.