Bücher- und Zeitschriftenschau

Ohne Zusammenfassung     

Mitigation of atmospheric perturbations and solid Earth movements in a TerraSAR-X time-series

The TerraSAR-X (TSX) synthetic aperture radar (SAR) marks the recent emergence of a new generation of spaceborne radar sensors that can for the first time lay claim to localization accuracies in the sub-meter range. The TSX platform’s extremely high orbital stability and the sensor’s hardware timing accuracy combine to enable direct measurements of atmospheric refraction and solid Earth movements. By modeling these effects for individual TSX acquisitions, absolute pixel geolocation accuracy on the order of several centimeters can be achieved without need for even a single tiepoint. A 16-month time series of images was obtained over a fixed test site, making it possible to validate both an atmospheric refraction and a solid Earth tide model, while at the same time establishing the instrument’s long-term stability. These related goals were achieved by placing trihedral corner reflectors (CRs) at the test site and estimating their phase centers with centimeter-level accuracy using differential GPS (DGPS). Oriented in pairs toward a given satellite track, the CRs could be seen as bright “points” in the images, providing a geometric reference set. SAR images from the high-resolution spotlight (HS) mode were obtained in alternating ascending and descending orbit configurations. The highest-resolution products were selected for their small sample dimensions, as positions can be more precisely determined. Based on the delivered product annotations, the CR image positions were predicted, and these predictions were compared with their measured image positions both before and after compensation for atmospheric refraction and systematic solid Earth deviations. It was possible to show that when the atmospheric distortion and Earth tides are taken into account, the TSX HS products have geolocation accuracies far exceeding the specified requirements. Furthermore, this accuracy was maintained for the duration of the 16-month test period. It could be demonstrated that with a correctly calibrated sensor, and after accounting for atmospheric and tidal effects, tiepoint-free geolocation is possible with TSX with an absolute product accuracy of about 5 cm.     

Fusion of multi‐resolution surface (terrestrial laser scanning) and subsurface geodata (ERT,SRT) for karst landform investigation and geomorphometric quantification

A multi‐method research design based on terrestrial laser scanning, GIS, geophysical prospecting (electrical resistivity tomography, refraction seismics) and sedimentology is applied for the first time to investigate enclosed karst depressions in an integrated way. Fusing multi‐resolution surface and subsurface geodata provides profound insights into the formation, geometry and geomorphologic processes of dolines. The studied landforms, which are located in the Dikti Mountains of East Crete, are shown to be filled by loose sediments of thicknesses of up to 30 m that mainly consist of fine‐grained material overlying solid bedrock at depths below 35 to 45 m. By combining subsurface observations with geomorphometric calculations, local doline genesis can be traced back to initial collapse of fractured bedrock followed by subsequent infilling with colluvials. In order to define crucial methodological requirements and guidelines for data fusion, both the impact of different elevation models and the influence of data resolution are assessed. Surface volumes of depressions derived by the digital surface model are 7–21% higher than the results obtained from the terrain model due to vegetation. Similarly, estimates of infill volume calculated on the basis of geophysical outcomes and elevation data differ by up to 13%. Calculations of the landforms' current volumes (i.e. total surface and subsurface volume), however, are fairly insensitive to raster resolution. Hence, the distinct geomorphologic properties of landforms (e.g. shape, terrain roughness, slope inclination) substantially determine the geomorphometric analysis of both surface and subsurface data. As shown by the findings, data fusion to integrate digital terrain, geophysical and sedimentological datasets of varied resolutions benefits geomorphologic studies and helps provide a comprehensive image of landforms. Copyright © 2013 John Wiley & Sons, Ltd.     

Trophic modeling of the Northern Humboldt Current Ecosystem, Part II: Elucidating ecosystem dynamics from 1995 to 2004 with a focus on the impact of ENSO

The Northern Humboldt Current Ecosystem is one of the most productive in the world in terms of fish production. Its location near to the equator permits strong upwelling under relatively low winds, thus creating optimal conditions for the development of plankton communities. These communities ultimately support abundant populations of grazing fish such as the Peruvian anchoveta, Engraulis ringens. The ecosystem is also subject to strong inter-annual environmental variability associated with the El Niño Southern Oscillation (ENSO), which has major effects on nutrient structure, primary production, and higher trophic levels. Here our objective is to model the contributions of several external drivers (i.e. reconstructed phytoplankton changes, fish immigration, and fishing rate) and internal control mechanisms (i.e. predator-prey) to ecosystem dynamics over an ENSO cycle. Steady-state models and time-series data from the Instituto del Mar del Perú (IMARPE) from 1995 to 2004 provide the base data for simulations conducted with the program Ecopath with Ecosim. In simulations all three external drivers contribute to ecosystem dynamics. Changes in phytoplankton quantity and composition (i.e. contribution of diatoms and dino- and silicoflagellates), as affected by upwelling intensity, were important in dynamics of the El Niño of 1997–98 and the subsequent 3 years. The expansion and immigration of mesopelagic fish populations during El Niño was important for dynamics in following years. Fishing rate changes were the most important of the three external drivers tested, helping to explain observed dynamics throughout the modeled period, and particularly during the post-El Niño period. Internal control settings show a mix of predator–prey control settings; however a “wasp-waist” control of the ecosystem by small pelagic fish is not supported.     

Electrical resistivity imaging of hydrologic flow through surface coal mine valley fills with comparison to other landforms

Surface coal mining has altered land cover, near‐surface geologic structure, and hydrologic processes of large areas in central Appalachia, USA. These alterations are associated with changes in water quality such as elevated total‐dissolved solids, which is usually measured via its surrogate, specific conductance (SC). The SC of valley fill effluent streams is a function of fill construction methods, materials, and age; yet hydrologic studies that relate these variables to water quality are sparse due to the difficulty of conducting traditional hydrologic studies in mined landscapes. We used electrical resistivity imaging (ERI) to visualize the subsurface geologic structure and hydrologic flow paths within a valley fill. ERI is a noninvasive geophysical technique that maps spatiotemporal changes in resistivity of the subsurface. We paired ERI with artificial rainfall experiments to track infiltrated water as it moved through the valley fill. Results indicate that ERI can be used to identify subsurface geologic structure and track advancing wetting fronts or preferential flow paths. Our results suggest that the upper portion of the fill contains significant fines, whereas the deeper profile is primarily large rocks and void spaces. Water tended to pond on the surface of compacted areas until it reached preferential flow paths, where it appeared to infiltrate quickly down to >15 m depth in 75 min. ERI applications can improve understanding of how fill construction techniques influence subsurface water movement, and in turn may aid in the development of valley fill construction methods to reduce water quality effects.     

150 Jahre Geologie

Ohne ZusammenfassungVortrag, gehalten am 29. Juni 1935 in Bad Ems auf den Hauptversammlungen des Naturhistorischen Vereins der Rheinlande und Westfalens, des Niederrheinischen Geologischen Vereins und des Botanischen und Zoologischen Vereins für Rheinland-Westfalen.     

Erinnerung an Werner

Ohne Zusammenfassung     

Patterns in the spatial distribution of Peruvian anchovy (Engraulis ringens) revealed by spatially explicit fishing data

Peruvian anchovy (Engraulis ringens) stock abundance is tightly driven by the high and unpredictable variability of the Humboldt Current Ecosystem. Management of the fishery therefore cannot rely on mid- or long-term management policy alone but needs to be adaptive at relatively short time scales. Regular acoustic surveys are performed on the stock at intervals of 2 to 4 times a year, but there is a need for more time continuous monitoring indicators to ensure that management can respond at suitable time scales. Existing literature suggests that spatially explicit data on the location of fishing activities could be used as a proxy for target stock distribution. Spatially explicit commercial fishing data could therefore guide adaptive management decisions at shorter time scales than is possible through scientific stock surveys. In this study we therefore aim to (1) estimate the position of fishing operations for the entire fleet of Peruvian anchovy purse–seiners using the Peruvian satellite vessel monitoring system (VMS), and (2) quantify the extent to which the distribution of purse–seine sets describes anchovy distribution. To estimate fishing set positions from vessel tracks derived from VMS data we developed a methodology based on artificial neural networks (ANN) trained on a sample of fishing trips with known fishing set positions (exact fishing positions are known for approximately 1.5% of the fleet from an at-sea observer program). The ANN correctly identified 83% of the real fishing sets and largely outperformed comparative linear models. This network is then used to forecast fishing operations for those trips where no observers were onboard. To quantify the extent to which fishing set distribution was correlated to stock distribution we compared three metrics describing features of the distributions (the mean distance to the coast, the total area of distribution, and a clustering index) for concomitant acoustic survey observations and fishing set positions identified from VMS. For two of these metrics (mean distance to the coast and clustering index), fishing and survey data were significantly correlated. We conclude that the location of purse–seine fishing sets yields significant and valuable information on the distribution of the Peruvian anchovy stock and ultimately on its vulnerability to the fishery. For example, a high concentration of sets in the near coastal zone could potentially be used as a warning signal of high levels of stock vulnerability and trigger appropriate management measures aimed at reducing fishing effort.