TY - JOUR A1 - Koyan, Philipp A1 - Tronicke, Jens A1 - Allroggen, Niklas T1 - 3D ground-penetrating radar attributes to generate classified facies models BT - a case study from a dune island JF - Geophysics N2 - Ground-penetrating radar (GPR) is a standard geophysical technique used to image near-surface structures in sedimentary environments. In such environments, GPR data acquisition and processing are increasingly following 3D strategies. However, the processed GPR data volumes are typically still interpreted using selected 2D slices and manual concepts such as GPR facies analyses. In seismic volume interpretation, the application of (semi-)automated and reproducible approaches such as 3D attribute analyses as well as the production of attribute-based facies models are common practices today. In contrast, the field of 3D GPR attribute analyses and corresponding facies models is largely untapped. We have developed and applied a workflow to produce 3D attribute-based GPR facies models comprising the dominant sedimentary reflection patterns in a GPR volume, which images complex sandy structures on the dune island of Spiekeroog (Northern Germany). After presenting our field site and details regarding our data acquisition and processing, we calculate and filter 3D texture attributes to generate a database comprising the dominant texture features of our GPR data. Then, we perform a dimensionality reduction of this database to obtain meta texture attributes, which we analyze and integrate using composite imaging and (also considering additional geometric information) fuzzy c-means cluster analysis resulting in a classified GPR facies model. Considering our facies model and a corresponding GPR facies chart, we interpret our GPR data set in terms of near-surface sedimentary units, the corresponding depositional environments, and the recent formation history at our field site. Thus, we demonstrate the potential of our workflow, which represents a novel and clear strategy to perform a more objective and consistent interpretation of 3D GPR data collected across different sedimentary environments. KW - ground-penetrating radar KW - attributes KW - interpretation KW - sedimentology Y1 - 2021 U6 - https://doi.org/10.1190/GEO2021-0204.1 SN - 0016-8033 SN - 1942-2156 VL - 86 IS - 6 SP - B335 EP - B347 PB - Society of Exploration Geophysicists CY - Tulsa ER - TY - THES A1 - Koyan, Philipp T1 - 3D attribute analysis and classification to interpret ground-penetrating radar (GPR) data collected across sedimentary environments: Synthetic studies and field examples T1 - 3D Attributanalyse und -klassifizierung zur Interpretation von Georadar-Daten in sedimentären Umgebungen: Synthetische Studien und Feldbeispiele N2 - Die Untersuchung des oberflächennahen Untergrundes erfolgt heutzutage bei Frage- stellungen aus den Bereichen des Bauwesens, der Archäologie oder der Geologie und Hydrologie oft mittels zerstörungsfreier beziehungsweise zerstörungsarmer Methoden der angewandten Geophysik. Ein Bereich, der eine immer zentralere Rolle in Forschung und Ingenieurwesen einnimmt, ist die Untersuchung von sedimentären Umgebungen, zum Beispiel zur Charakterisierung oberflächennaher Grundwassersysteme. Ein in diesem Kontext häufig eingesetztes Verfahren ist das des Georadars (oftmals GPR - aus dem Englischen ground-penetrating radar). Dabei werden kurze elektromagnetische Impulse von einer Antenne in den Untergrund ausgesendet, welche dort wiederum an Kontrasten der elektromagnetischen Eigenschaften (wie zum Beispiel an der Grundwasseroberfläche) reflektiert, gebrochen oder gestreut werden. Eine Empfangsantenne zeichnet diese Signale in Form derer Amplituden und Laufzeiten auf. Eine Analyse dieser aufgezeichneten Signale ermöglicht Aussagen über den Untergrund, beispielsweise über die Tiefenlage der Grundwasseroberfläche oder die Lagerung und Charakteristika oberflächennaher Sedimentschichten. Dank des hohen Auflösungsvermögens der GPR-Methode sowie stetiger technologischer Entwicklungen erfolgt heutzutage die Aufzeichnung von GPR- Daten immer häufiger in 3D. Trotz des hohen zeitlichen und technischen Aufwandes für die Datenakquisition und -bearbeitung werden die resultierenden 3D-Datensätze, welche den Untergrund hochauflösend abbilden, typischerweise von Hand interpretiert. Dies ist in der Regel ein äußerst zeitaufwendiger Analyseschritt. Daher werden oft repräsentative 2D-Schnitte aus dem 3D-Datensatz gewählt, in denen markante Reflektionsstrukuren markiert werden. Aus diesen Strukturen werden dann sich ähnelnde Bereiche im Untergrund als so genannte Radar-Fazies zusammengefasst. Die anhand von 2D-Schnitten erlangten Resultate werden dann als repräsentativ für die gesamte untersuchte Fläche angesehen. In dieser Form durchgeführte Interpretationen sind folglich oft unvollständig sowie zudem in hohem Maße von der Expertise der Interpretierenden abhängig und daher in der Regel nicht reproduzierbar. Eine vielversprechende Alternative beziehungsweise Ergänzung zur manuellen In- terpretation ist die Verwendung von so genannten GPR-Attributen. Dabei werden nicht die aufgezeichneten Daten selbst, sondern daraus abgeleitete Größen, welche die markanten Reflexionsstrukturen in 3D charakterisieren, zur Interpretation herangezogen. In dieser Arbeit wird anhand verschiedener Feld- und Modelldatensätze untersucht, welche Attribute sich dafür insbesondere eignen. Zudem zeigt diese Arbeit, wie ausgewählte Attribute mittels spezieller Bearbeitungs- und Klassifizierungsmethoden zur Erstellung von 3D-Faziesmodellen genutzt werden können. Dank der Möglichkeit der Erstellung so genannter attributbasierter 3D-GPR-Faziesmodelle können zukünftige Interpretationen zu gewissen Teilen automatisiert und somit effizienter durchgeführt werden. Weiterhin beschreiben die so erhaltenen Resultate den untersuchten Untergrund in reproduzierbarer Art und Weise sowie umfänglicher als es bisher mittels manueller Interpretationsmethoden typischerweise möglich war. N2 - Today, near-surface investigations are frequently conducted using non-destructive or minimally invasive methods of applied geophysics, particularly in the fields of civil engineering, archaeology, geology, and hydrology. One field that plays an increasingly central role in research and engineering is the examination of sedimentary environments, for example, for characterizing near-surface groundwater systems. A commonly employed method in this context is ground-penetrating radar (GPR). In this technique, short electromagnetic pulses are emitted into the subsurface by an antenna, which are then reflected, refracted, or scattered at contrasts in electromagnetic properties (such as the water table). A receiving antenna records these signals in terms of their amplitudes and travel times. Analysis of the recorded signals allows for inferences about the subsurface, such as the depth of the groundwater table or the composition and characteristics of near-surface sediment layers. Due to the high resolution of the GPR method and continuous technological advancements, GPR data acquisition is increasingly performed in three-dimensional (3D) fashion today. Despite the considerable temporal and technical efforts involved in data acquisition and processing, the resulting 3D data sets (providing high-resolution images of the subsurface) are typically interpreted manually. This is generally an extremely time-consuming analysis step. Therefore, representative 2D sections highlighting distinctive reflection structures are often selected from the 3D data set. Regions showing similar structures are then grouped into so-called radar facies. The results obtained from 2D sections are considered representative of the entire investigated area. Interpretations conducted in this manner are often incomplete and highly dependent on the expertise of the interpreters, making them generally non-reproducible. A promising alternative or complement to manual interpretation is the use of GPR attributes. Instead of using the recorded data directly, derived quantities characterizing distinctive reflection structures in 3D are applied for interpretation. Using various field and synthetic data sets, this thesis investigates which attributes are particularly suitable for this purpose. Additionally, the study demonstrates how selected attributes can be utilized through specific processing and classification methods to create 3D facies models. The ability to generate attribute-based 3D GPR facies models allows for partially automated and more efficient interpretations in the future. Furthermore, the results obtained in this manner describe the subsurface in a reproducible and more comprehensive manner than what has typically been achievable through manual interpretation methods. KW - ground-penetrating radar KW - sedimentary environments KW - 3D KW - applied geophysics KW - near-surface geophysics KW - Georadar KW - sedimentäre Systeme KW - angewandte Geophysik KW - oberflächennahe Geophysik KW - Attribute KW - attributes KW - geophysics KW - Geophysik Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-639488 ER - TY - JOUR A1 - Farinotti, Daniel A1 - King, Edward C. A1 - Albrecht, Anika A1 - Huss, Matthias A1 - Gudmundsson, Gudmundur Hilmar T1 - The bedrock topography of Starbuck Glacier, Antarctic Peninsula, as determined by radio-echo soundings and flow modeling JF - Annals of glaciology KW - Antarctic glaciology KW - glaciological instruments and methods KW - ground-penetrating radar KW - ice-shelf tributary glaciers KW - radio-echo sounding Y1 - 2014 U6 - https://doi.org/10.3189/2014AoG67A025 SN - 0260-3055 SN - 1727-5644 VL - 55 IS - 67 SP - 22 EP - 28 PB - International Glaciological Society CY - Cambridge ER - TY - GEN A1 - Angermann, Lisa A1 - Jackisch, Conrad A1 - Allroggen, Niklas A1 - Sprenger, Matthias A1 - Zehe, Erwin A1 - Tronicke, Jens A1 - Weiler, Markus A1 - Blume, Theresa T1 - Form and function in hillslope hydrology BT - characterization of subsurface flow based on response observations T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - The phrase form and function was established in architecture and biology and refers to the idea that form and functionality are closely correlated, influence each other, and co-evolve. We suggest transferring this idea to hydrological systems to separate and analyze their two main characteristics: their form, which is equivalent to the spatial structure and static properties, and their function, equivalent to internal responses and hydrological behavior. While this approach is not particularly new to hydrological field research, we want to employ this concept to explicitly pursue the question of what information is most advantageous to understand a hydrological system. We applied this concept to subsurface flow within a hillslope, with a methodological focus on function: we conducted observations during a natural storm event and followed this with a hillslope-scale irrigation experiment. The results are used to infer hydrological processes of the monitored system. Based on these findings, the explanatory power and conclusiveness of the data are discussed. The measurements included basic hydrological monitoring methods, like piezometers, soil moisture, and discharge measurements. These were accompanied by isotope sampling and a novel application of 2-D time-lapse GPR (ground-penetrating radar). The main finding regarding the processes in the hillslope was that preferential flow paths were established quickly, despite unsaturated conditions. These flow paths also caused a detectable signal in the catchment response following a natural rainfall event, showing that these processes are relevant also at the catchment scale. Thus, we conclude that response observations (dynamics and patterns, i.e., indicators of function) were well suited to describing processes at the observational scale. Especially the use of 2-D time-lapse GPR measurements, providing detailed subsurface response patterns, as well as the combination of stream-centered and hillslope-centered approaches, allowed us to link processes and put them in a larger context. Transfer to other scales beyond observational scale and generalizations, however, rely on the knowledge of structures (form) and remain speculative. The complementary approach with a methodological focus on form (i.e., structure exploration) is presented and discussed in the companion paper by Jackisch et al. (2017). T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 658 KW - ground-penetrating radar KW - preferential flow KW - water-flow KW - runoff generation KW - vadose zone KW - catchment KW - scale KW - tracer KW - time KW - pore Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-419161 SN - 1866-8372 IS - 658 ER -