Passive seismic source localization via common-reflection-surface attributes

The common-reflection-surface (CRS) stack can be viewed as a physically justified extension of the classical common-midpoint (CMP) stack, utilizing redundant information not only in a single, but in several neighboring CMP gathers. The zero-offset CRS moveout is parameterized in terms of kinematic attributes, which utilize reciprocity and raypath symmetries to describe the two-way process of the actual wave propagation in active seismic experiments by the propagation of auxiliary one-way wavefronts. For the diffraction case, only the attributes of a single one-way wavefront, originating from the diffractor are sufficient to explain the traveltime differences observed at the surface. While paraxial ray theory gives rise to a second-order approximation of the CRS traveltime, many higher-order approximations were subsequently introduced either by squaring the second-order expression or by employing principles of optics and geometry. It was recently discovered that all of these higher-order operators can be formulated either for the optical projection or in an auxiliary medium of a constant effective velocity. Utilizing this duality and the one-way nature of the CRS parameters, we present a simple data-driven stacking scheme that allows for the estimation of the a priori unknown excitation time of a passive seismic source. In addition, we demonstrate with a simple data example that the output of the suggested workflow can directly be used for subsequent focusing-based normal-incidence-point (NIP) tomography, leading to a reliable localization in depth.     

Calibration of the MDCO dust collector and of four versions of the inverted frisbee dust deposition sampler

Wind tunnel experiments were conducted to determine the efficiency of sediment samplers designed to measure the deposition of aeolian dust. Efficiency was ascertained relative to a water surface, which was considered the best alternative for simulating a perfectly absorbent surface. Two types of samplers were studied: the Marble Dust Collector (MDCO) and the inverted frisbee sampler. Four versions of the latter catcher were tested: an empty frisbee, an empty frisbee surrounded by an aerodynamic flow deflector ring, a frisbee filled with glass marbles, and a frisbee filled with glass marbles and surrounded by a flow deflector ring. Efficiency was ascertained for five wind velocities (range: 1–5 m s^− 1) and eight grain size classes (range: 10–89 μm). The efficiency of dust deposition catchers diminishes rapidly as the wind speed increases. It also diminishes as the particles caught become coarser. Adding a flow deflector ring to a catcher substantially improves the catcher's efficiency, by up to 100% in some cases. The addition of glass marbles to a catcher, on the other hand, does not seem to increase the efficiency, at least not at wind velocities inferior to the deflation threshold. For higher velocities the marbles protect the settled particles from resuspension, keeping them in the catcher. The following five parameters determine the accumulation of aeolian dust in a catcher: the horizontal dust flux, the weight of the particles, atmospheric turbulence, resuspension, and the dust shadow effect created by the catcher. The final accumulation flux depends on the combination of these parameters. The catchers tested in this study belong to the best catchers currently in use in earth science and have been the subject of various aerodynamic studies to improve their efficiency. Nevertheless the catching efficiency remains low, in the order of 20–40% for wind speeds above 2 m s^− 1. Other catchers suffer from the same low efficiencies. There is, thus, evidence to believe that dust deposition rates published in the aeolian literature and obtained by collecting the sediment in a catcher largely underestimate the true deposition. The errors are considerable, of the order of 100% and more. A reconsideration of the literature data on aeolian dust deposition measured by catchers is, therefore, required.     

Sensitivity of tropical-African aquatic invertebrates to short-term trends in lake level and salinity: a paleolimnological test at Lake Oloidien,Kenya

Aquatic invertebrates are intrinsically capable of rapid and sensitive response to changes in their lacustrine habitat. Fossil invertebrate assemblages preserved in the sediments of a climate-sensitive lake can thus produce high-resolution proxy records of past climate. In shallow lakes, however, a potential conflict exists between the sensitivity of biota to frequent habitat change in their fluctuating environment and the increased probability of disturbance of selected proxy records by bioturbation and physical mixing of sediments. I investigated this problem with tropical-African aquatic invertebrate faunas in a paleolimnological sensitivity study that incorporates both the response of biota to short-term habitat change and the taphonomic integrity of fossil assemblages in a small, shallow, and hydrologically closed lacustrine basin. Analysis of chironomid, cladoceran, and ostracode remains in a²¹⁰Pb-dated short core from Lake Oloidien (Kenya) indicates that habitat changes accompanying the late 19th- and 20th-century fluctuations in lake level (Z _max range: 3 to 18 m) and salinity (conductivity range:c. 400 toc. 2000–4000 µS cm^–1) were sufficient to drastically alter the composition of local benthic and planktonic invertebrate faunas. This response remained relatively unaffected by taphonomic phenomena during its incorporation into the sediment record. Results indicate that tropical-African aquatic invertebrate faunas in suitable climate-sensitive lakes are a valuable tool to resolve paleoclimatic fluctuations on a timescale of decades.This paper was presented at the VI Palaeolimnology Symposium, held at Canberra in April 1993. Dr. Mark Brenner guest edited this contribution.     

A conceptual framework for studying collective reactions to events in location-based social media

Events are a core concept of spatial information, but location-based social media (LBSM) provide information on reactions to events. Individuals have varied degrees of agency in initiating, reacting to or modifying the course of events, and reactions include observations of occurrence, expressions containing sentiment or emotions, or a call to action. Key characteristics of reactions include referent events and information about who reacted, when, where and how. Collective reactions are composed of multiple individual reactions sharing common referents. They can be characterized according to the following dimensions: spatial, temporal, social, thematic and interlinkage. We present a conceptual framework, which allows characterization and comparison of collective reactions. For a thematically well-defined class of event such as storms, we can explore differences and similarities in collective attribution of meaning across space and time. Other events may have very complex spatio-temporal signatures (e.g. political processes such as Brexit or elections), which can be decomposed into series of individual events (e.g. a temporal window around the result of a vote). The purpose of our framework is to explore ways in which collective reactions to events in LBSM can be described and underpin the development of methods for analysing and understanding collective reactions to events.     

How much information is geospatially referenced? Networks and cognition

The aim of this article is to provide a basis in evidence for (or against) the much-quoted assertion that 80% of all information is geospatially referenced. For this purpose, two approaches are presented that are intended to capture the portion of geospatially referenced information in user-generated content: a network approach and a cognitive approach. In the network approach, the German Wikipedia is used as a research corpus. It is considered a network with the articles being nodes and the links being edges. The Network Degree of Geospatial Reference (NDGR) is introduced as an indicator to measure the network approach. We define NDGR as the shortest path between any Wikipedia article and the closest article within the network that is labeled with coordinates in its headline. An analysis of the German Wikipedia employing this approach shows that 78% of all articles have a coordinate themselves or are directly linked to at least one article that has geospatial coordinates. The cognitive approach is manifested by the categories of geospatial reference (CGR): direct, indirect, and non-geospatial reference. These are categories that may be distinguished and applied by humans. An empirical study including 380 participants was conducted. The results of both approaches are synthesized with the aim to (1) examine correlations between NDGR and the human conceptualization of geospatial reference and (2) to separate geospatial from non-geospatial information. From the results of this synthesis, it can be concluded that 56–59% of the articles within Wikipedia can be considered to be directly or indirectly geospatially referenced. The article thus describes a method to check the validity of the ‘80%-assertion’ for information corpora that can be modeled using graphs (e.g., the World Wide Web, the Semantic Web, and Wikipedia). For the corpus investigated here (Wikipedia), the ‘80%-assertion’ cannot be confirmed, but would need to be reformulated as a ‘60%-assertion’.     

The Elbe Fault System in North Central Europe—a basement controlled zone of crustal weakness

The Elbe Fault System (EFS) is a WNW-striking zone extending from the southeastern North Sea to southwestern Poland along the present southern margin of the North German Basin and the northern margin of the Sudetes Mountains. Although details are still under debate, geological and geophysical data reveal that upper crustal deformation along the Elbe Fault System has taken place repeatedly since Late Carboniferous times with changing kinematic activity in response to variation in the stress regime. In Late Carboniferous to early Permian times, the Elbe Fault System was part of a post-Variscan wrench fault system and acted as the southern boundary fault during the formation of the Permian Basins along the Trans-European Suture Zone (sensu [Geol. Mag. 134 (5) (1997) 585]). The Teisseyre–Tornquist Zone (TTZ) most probably provided the northern counterpart in a pull-apart scenario at that time. Further strain localisation took place during late Mesozoic transtension, when local shear within the Elbe Fault System caused subsidence and basin formation along and parallel to the fault system. The most intense deformation took place along the system during late Cretaceous–early Cenozoic time, when the Elbe Fault System responded to regional compression with up to 4 km of uplift and formation of internal flexural highs. Compressional deformation continued during early Cenozoic time and actually may be ongoing. The upper crust of the Elbe Fault System, which itself reacted in a more or less ductile fashion, is underlain by a lower crust characterised by low P-wave velocities, low densities and a weak rheology. Structural, seismic and gravimetric data as well as rheology models support the assumption that a weak, stress-sensitive zone in the lower crust is the reason for the high mobility of the area and repeated strain localisation along the Elbe Fault System.     

A new geospatial overlay method for the analysis and visualization of spatial change patterns using object-oriented data modeling concepts

Traditional geographic information system (GIS)-overlay routines usually build on relatively simple data models. Topology is – if at all – calculated on the fly for very specific tasks only. If, for example, a change comparison is conducted between two or more polygon layers, the result leads mostly to a complete and also very complex from–to class intersection. A lot of additional processing steps need to be performed to arrive at aggregated and meaningful results. To overcome this problem a new, automated geospatial overlay method in a topologically enabled (multi-scale) framework is presented. The implementation works with polygon and raster layers and uses a multi-scale vector/raster data model developed in the object-based image analysis software eCognition (Trimble Geospatial Imaging, Munich, Germany). Advantages are the use of the software inherent topological relationships in an object-by-object comparison, addressing some of the basic concepts of object-oriented data modeling such as classification, generalization, and aggregation. Results can easily be aggregated to a change-detection layer; change dependencies and the definition of different change classes are interactively possible through the use of a class hierarchy and its inheritance (parent–child class relationships). Implementation is exemplarily shown for a change comparison of CORINE Land Cover data sets. The result is a flexible and transferable solution which is – if parameterized once – fully automated.     

Estimation of Hydraulic Conductivity and Its Uncertainty from Grain-Size Data Using GLUE and Artificial Neural Networks

Various approaches exist to relate saturated hydraulic conductivity (K _s) to grain-size data. Most methods use a single grain-size parameter and hence omit the information encompassed by the entire grain-size distribution. This study compares two data-driven modelling methods??multiple linear regression and artificial neural networks??that use the entire grain-size distribution data as input for K _s prediction. Besides the predictive capacity of the methods, the uncertainty associated with the model predictions is also evaluated, since such information is important for stochastic groundwater flow and contaminant transport modelling. Artificial neural networks (ANNs) are combined with a generalised likelihood uncertainty estimation (GLUE) approach to predict K _s from grain-size data. The resulting GLUE-ANN hydraulic conductivity predictions and associated uncertainty estimates are compared with those obtained from the multiple linear regression models by a leave-one-out cross-validation. The GLUE-ANN ensemble prediction proved to be slightly better than multiple linear regression. The prediction uncertainty, however, was reduced by half an order of magnitude on average, and decreased at most by an order of magnitude. This demonstrates that the proposed method outperforms classical data-driven modelling techniques. Moreover, a comparison with methods from the literature demonstrates the importance of site-specific calibration. The data set used for this purpose originates mainly from unconsolidated sandy sediments of the Neogene aquifer, northern Belgium. The proposed predictive models are developed for 173 grain-size K _s-pairs. Finally, an application with the optimised models is presented for a borehole lacking K _s data.