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Thüringen
(1995)
Hydrogeophysik : Erkundungen und Sicherung der Ressource Wasser : Antrittsvorlesung 2006-06-01
(2006)
Die weltweite Wasserversorgung basiert zu einem überwiegenden Teil auf Grundwasser. Die Erkundung, der Schutz, die nachhaltige Nutzung sowie die eventuelle Sanierung dieser Grundwasserressourcen sind somit global von fundamentalem gesellschaftlichem Interesse. Bei vielen dieser grundwasserbezogenen Fragestellungen ist häufig eine effiziente und detaillierte Charakterisierung des Untergrundes notwendig. Geophysikalische Messverfahren liefern Abbilder der physikalischen Eigenschaften, wie beispielsweise des elektrischen Widerstandes, die wichtige Informationen über den geometrischen und stofflichen Aufbau des verborgenen Untergrundes liefern. In der Vorlesung wird gezeigt, wie die Verfahren der Angewandten Geophysik auf Fragestellungen hinsichtlich der Präsenz, Ausbreitung und Qualität der Ressource Grundwasser eingesetzt werden können. Darüber hinaus werden aktuelle Forschungsthemen und offene Fragen angesprochen.
Python is used in a wide range of geoscientific applications, such as in processing images for remote sensing, in generating and processing digital elevation models, and in analyzing time series. This book introduces methods of data analysis in the geosciences using Python that include basic statistics for univariate, bivariate, and multivariate data sets, time series analysis, and signal processing; the analysis of spatial and directional data; and image analysis. The text includes numerous examples that demonstrate how Python can be used on data sets from the earth sciences. The supplementary electronic material (available online through Springer Link) contains the example data as well as recipes that include all the Python commands featured in the book.
MATLAB is used in a wide range of applications in geosciences, such as image processing in remote sensing, generation and processing of digital elevation models and the analysis of time series. This book introduces basic methods of data analysis in geosciences using MATLAB. The text includes a brief description of each method and numerous examples demonstrating how MATLAB can be used on data sets from earth sciences. All MATLAB recipes can be easily modified in order to analyse the reader's own data sets. The book comes with a CD containing exemplary data sets and a digital version of the MATLAB recipes. (Springer)
MATLAB is used in a wide range of applications in geosciences, such as image processing in remote sensing, generation and processing of digital elevation models and the analysis of time series. This book introduces basic methods of data analysis in geosciences using MATLAB. The text includes a brief description of each method and numerous examples on how MATLAB can be used on data sets from earth sciences. All MATLAB recipes can easily be modified in order to analyse the reader's own data sets. The book comes with a CD containing example data sets and a digital version of the MATLAB recipes.
Das Hochwasser im Juni 2013
(2015)
In this study we examine the tonal organization of a series of recordings of liturgical chants, sung in 1966 by the Georgian master singer Artem Erkomaishvili. This dataset is the oldest corpus of Georgian chants from which the time synchronous F0-trajectories for all three voices have been reliably determined (Müller et al. 2017). It is therefore of outstanding importance for the understanding of the tuning principles of traditional Georgian vocal music.
The aim of the present study is to use various computational methods to analyze what these recordings can contribute to the ongoing scientific dispute about traditional Georgian tuning systems. Starting point for the present analysis is the re-release of the original audio data together with estimated fundamental frequency (F0) trajectories for each of the three voices, beat annotations, and digital scores (Rosenzweig et al. 2020). We present synoptic models for the pitch and the harmonic interval distributions, which are the first of such models for which the complete Erkomaishvili dataset was used. We show that these distributions can be very compactly be expressed as Gaussian mixture models, anchored on discrete sets of pitch or interval values for the pitch and interval distributions, respectively. As part of our study we demonstrate that these pitch values, which we refer to as scale pitches, and which are determined as the mean values of the Gaussian mixture elements, define the scale degrees of the melodic sound scales which build the skeleton of Artem Erkomaishvili’s intonation. The observation of consistent pitch bending of notes in melodic phrases, which appear in identical form in a group of chants, as well as the observation of harmonically driven intonation adjustments, which are clearly documented for all pure harmonic intervals, demonstrate that Artem Erkomaishvili intentionally deviates from the scale pitch skeleton quite freely. As a central result of our study, we proof that this melodic freedom is always constrained by the attracting influence of the scale pitches. Deviations of the F0-values of individual note events from the scale pitches at one instance of time are compensated for in the subsequent melodic steps. This suggests a deviation-compensation mechanism at the core of Artem Erkomaishvili’s melody generation, which clearly honors the scales but still allows for a large degree of melodic flexibility. This model, which summarizes all partial aspects of our analysis, is consistent with the melodic scale models derived from the observed pitch distributions, as well as with the melodic and harmonic interval distributions. In addition to the tangible results of our work, we believe that our work has general implications for the determination of tuning models from audio data, in particular for non-tempered music.