Center for High Voltage Engeneering and Insulating Systems
The research field of high-voltage engeneering and insulation systems is of central importance in modern industrial society. High voltages or high field strengths in the insulation systems are required for the low-loss transmission of electrical energy as well as for a variety of industrial applications from medical to manufacturing to automotive technology.
High-voltage technology includes the control of high electric field strengths in all types of electrical insulation. The simple basic principle is:
Under all conditions, the electrical stress (i.e. the electrical field strength) must always be smaller than the electrical strength of the insulating media.
The task of high-voltage technology is therefore not to generate electrical discharges, even if these are always impressive for visitors to our laboratory, but rather to prevent them in order to ensure the safe operation of devices and systems.
It is now necessary to further exploit insulation systems for technical and economic reasons. That's why a deep understanding of the materials is essential, which is why research in the area of high-voltage insulation materials and systems has now become very much focused on materials science. The direct cooperation of several laboratories involved in the IEHT is a great advantage. Modern analysis methods such as FTIR or Raman spectroscopy are available in the materials science working group and in the chemical-physical laboratory.
The THWS high-voltage laboratory offers for student training, research and cooperation with industrial partners a partially worldwide unique infrasructure. A more detailed description of the equipment can be found on the laboratory's website.
Insulating materials and systems for high-voltage direct current transmission (HVDC)

... because in the future three-phase networks worldwide will reach their performance limits and will have to be networked with high-voltage direct current transmission (HVDC) ...
Research fields:
- Investigation of the electrical conductivity of insulating materials under defined boundary conditions
- Investigation of charge carrier generation and recombination as well as charge carrier transport in insulating liquids
- Measuring space charges with the electro-optical Kerr effect
- Measurement of space charges with the Pulsed Electro Acoustic Method (PEA)
- Multiscale modeling of charge transport in liquid and solid insulating materials
- Quantum chemistry
- Molecular dynamics
- Bipolar Charge Transport Models
- FEM simulation of charge transport in insulating materials and systems
Diagnosis, monitoring and condition assessment
... because the networks of industrialized nations were expanded decades ago, so that the safe operation of systems and devices requires reliable diagnostics of the aging condition ...
Research fields:
- Measurement and analysis of partial discharges, e.g. for HVDC applications
- Use of modern PD measurement technology and fault location detection for online and offline diagnosis
- Spectroscopic material analysis
Insulation systems for electrical machines and power electronic applicationsInsulation systems for electrical machines and power electronic applications
...because the new requirements in the area of electrical machines, such as an increase in efficiency, the use of modern, fast-switching power semiconductors and new insulating materials, are leading to increasing loads on the insulating systems...
Research fields:
- Investigation of the TE activity of engine test specimens
- Investigation of the aging behavior of engine insulation systems
- Investigation of the (aging) behavior of insulating materials at high frequencies
Transient behavior of power transformers
… since modern power transmission systems are becoming increasingly complex, and the integration of power-electronic components more frequently leads to fast, high-frequency overvoltages that stress transformer insulation systems in new ways, making a deep understanding of transient phenomena essential for safe and reliable operation …
Research fields:
- Modelling & Validation: Development of validated white-box, black-box, and grey-box models for ransformer simulation
- Assessment Methods: Application of severity indices (FDSF/TDSF) and investigation of internationally discussed approaches for the assessment of non-standard overvoltages
- Analysis of Recorded Transients: Evaluation of transient events measured on in-service transformers and comparison with EMTP models
Modeling, simulation and measurement of electric field strength distributions in insulating fluids under transient and steady-state DC loading of layered insulation systems (EFI-DC)
Management Prof. Zink, Prof. Dr. Kobus
Research partners Siemens Energy Global GmbH & Co. KG, Weidmann Electrical Technology AG
Duration 2018-2025
As a result of the energy transition and the restructuring of energy networks, high-voltage direct current transmission (HVDC) is becoming increasingly important and brings with it increasing demands on operating resources. The insulation systems of HVDC equipment, especially transformers, are of particular interest. The main components of such insulation systems are insulating fluids and oil-impregnated pressboard made of cellulose, which exhibit complex electrical conduction and polarization mechanisms under direct voltage stress that have not yet been studied in depth. Conventional RC circuit models are only partially suitable for the dielectric description of these materials and the mechanisms that occur. Rather, multiphysical modeling approaches are required that take different physical-chemical effects into account. These mainly include the Poisson-Nernst-Planck (PNP) system of equations. However, there has so far been no clear consensus regarding the parameterization when using it and the parameters on which the simulation is based are often only meaningfully estimated or varied empirically.
As part of the EFI-DC project, the layered insulation system will therefore be examined with different DC loads and configurations of the insulation system in order to gain a deeper understanding of the dominant charge carrier phenomena. Additional environmental parameters (temperature, pressure, etc.) can be varied, which can be used to test various hypotheses. The primary measurement methods for verification are the simultaneous measurement of the transient polarization current (PDC measurement) and the stationary and transient field strength in existing transparent areas of the insulating medium. Field and current curves resulting from these measurements can be used to parameterize or verify the existing models. With an accurate model and the understanding gained from it, the design of the insulation system of various equipment under DC load can be designed more effectively in terms of weak points and a potential reduction in the installation space of the transformers, which at the same time significantly increases the competitiveness of HVDC technology.
Elastomers with specific conductivity and their aging behavior (ELSA)
Management Prof. Zink, Prof. Kobus
Research partner Pfisterer contact systems
Duration 2022-2025
Elastomers, among other things, are used as insulating materials in complex insulation systems for cable applications (cable sleeves) in high-voltage direct current (HVDC) transmission. The selection and qualification of suitable materials for specific applications is challenging. In addition to the electrical parameters that are important for the design, knowledge about the aging behavior of these materials also plays a central role. In particular, construction and assembly-related situations in a cable sleeve, such as the "noble joint", or additives (lubricants) required for assembly can significantly influence the service life behavior. The combination or layering of various insulating materials such as silicones or EPDM (ethylene-propylene-diene rubbers) with the XLPE (Cross-linked Polyethylene) used in the cable as part of HVDC also brings with it new challenges for the insulation systems. The electrical conductivity has a decisive influence on the field distribution within the layer insulation system. However, this is significantly influenced by its dependence on various influencing factors such as the ambient temperature, the applied electrical field or production-related defects.
As part of the ELSA project (elastomers with specific conductivity and their aging behavior), different aging mechanisms of different elastomers are being investigated in collaboration with the project partner Pfisterer. By using dielectric diagnostic methods, such as polarization and depolarization measurements or space charge measurements using the PEA method, the condition of the insulating material is assessed over its service life. By additionally interpreting the dielectric properties using spectral investigation methods such as infrared and Raman spectroscopy, which allow information to be drawn about the bonding situation in the polymer, a uniform picture of the aging stage can be obtained.
This newly gained knowledge should make a significant contribution to the better qualification and testing of insulating materials, which should lead to advanced and more reliable fittings.
Conductivity investigation of insulating materials with field strength-dependent behavior (LUISE)
Management Prof. Zink
Internal research partner
Duration 2023-2026
The development of energy transmission with high-voltage direct current (HVDC) is a central element of the energy transition. A particular challenge is the safe design of high-voltage insulation systems, whose task is to safely control the high voltages and field strengths within the equipment. While in applications for alternating voltage the electric field (displacement field) can be controlled by the geometry of the electrodes and interfaces, this is not possible for direct voltage (flow field). The conductivities of the insulating materials determine the field distribution in the insulation system. However, the conductivities of the insulating materials are not only very different from one another, but are also highly dependent on the parameters field strength and temperature, whereas this dependence does not apply to the permittivity, which makes the design in the displacement field easier than in the flow field. During operation of the insulation systems, especially when, for example, the temperature distribution changes or temperature gradients develop, the above-mentioned dependencies can lead to the formation of space or surface charge zones, which can drastically change the field strength distribution in the insulation system, so-called field migration or inversion, see . Figure 1. Under certain circumstances, this can lead to the formation of (partial) discharges, which can then erode the materials and damage the insulation system to the point of total failure. Such problems occur not only in the insulation systems of HVDC equipment, but also, for example, in high-tech applications with high direct voltage, such as fundamental physics, semiconductor technology or microscopy. An innovative approach to improve the problems described lies in the use of so-called field grading materials (FGM) with a specifically adjusted or even field strength-dependent electrical conductivity. With these materials, areas with higher field strength can be automatically relieved and the field distribution in the insulation system can be evened out. Such materials are based on a carrier material, e.g. varnish or epoxy resin, in which filling materials (e.g. silicon carbides or metal oxides) are embedded, which show a field strength-dependent, varistor-like conductivity behavior.
Measurement of Motorettes (MEMO)
Management Prof. Zink, Prof. Rahimpour
Research partner NN
Duration 2023-2024
The transformation of the automotive industry towards fully electric vehicles brings with it various challenges in the design and development of individual components. Due to ever-increasing electrical consumers, the need for high voltages in the on-board electrical system is increasing in order to keep currents low and thus enable economical design of the machines. This results in a high electrical load on the insulating materials in the drive train, which is why proven insulation systems are often no longer sufficient. In order to ensure reliable operation over the service life in the future, it is important to examine the aging behavior of the insulation systems.
In the MEMO research project, the aging mechanisms under different types of stress are to be investigated in order to gain knowledge about the dominant aging factors. The accelerated aging tests take place on complete stators and motor formats with various insulation systems. In order to evaluate the aging condition of the test specimens in the individual aging stages, various non-destructive dielectric measurements from high-voltage technology are used. Among other things, the measurement of the insulation resistance (PDC measurement), the loss factor, the partial discharge activity at surge and alternating voltage as well as the frequency domain measurement (FDS) are used to determine the aging condition. If necessary, additional breakdown tests (HiPot) are used to determine the degradation of the insulation systems.
The characteristic values resulting from the tests should be used to parameterize a service life model. Particular attention is also paid to the partial discharge behavior of the test specimens in different aging states, which will be investigated using phase-resolved partial discharge analysis (PRPDA) and pulse sequence analysis (PSA). This serves to further understand the aging mechanisms of the insulation systems and offers the cooperation partner the opportunity to continue to guarantee the usual and required reliability. The results of the investigations show the limits of the insulation systems and offer a comparison with each other. In addition, the tests used can be used in the qualification and manufacturing process of a new product.
Studying the effect of biodegradable molecule on dielectric failure of high voltage liquid insulation system: environmentally friendly dielectric liquids based on natural esters (BioLiq)

Management Prof. Zink, Prof. Kobus
Research partner Alexander von Humboldt Foundation
Duration 2023-2025
The remarkable development in high-voltage direct current and high-voltage alternating current transmission systems calls for a renewed assessment of dielectric liquids for insulation systems of transformers. The function of liquid insulation used in high voltage equipment is cooling and insulation. It should have several features like high dielectric strength, low viscosity, high flash point, very low moisture or water content, high specific resistance and many more. Petroleum dependent synthetic and mineral oil has been conventionally applied as dielectric fluids in transformers during previous some decades that disturbs the environment on account of their low biodegradability and low fire point which have persuaded the exploration of substitutes. The application of alternate insulating fluids is increasing gradually, with safety and environmental apprehensions at the lead of the grounds for shifting from mineral oil.
Dielectric failure phenomenon in high voltage (HV) liquid dielectric insulation is still not well understood and it poses major scientific and technological complications. The understanding of dielectric failure is required to get insight about breakdown process mechanisms and theoretical basis for molecular modification hence application of dielectric insulation at appropriate applications. Hydrocarbon based liquids extracted from finite resources have been used as insulation in HV applications for more than a century. They have been long tested with long history and set design rules for applications in HV equipment. The non-renewable nature of these hydrocarbon-based liquids presents much burden on the energy security and environmental protection. Renewable oils (natural esters/vegetable oils) mainly composed of triacylglycerol molecules extracted from plants are increasingly being adopted for use in electrical insulation, lubricants, and biodiesel. Natural esters, as the renewable resources, present excellent physiochemical and dielectric features, e.g., fire resistance, high biodegradability, and satisfactory dielectric breakdown performance. Their environmental performance makes these materials extremely popular, and they are being anticipated as potential dielectric liquid insulation. Until now, despite all these mentioned advantages, they could only find applications in medium voltage applications. The main reason for their limited applications at high voltage levels is non-availability of fundamental data about dielectric parameters and the knowledge about failure phenomena, which is significant for design rules to achieve a long-term reliable performance. The absence of fundamental data about natural esters makes the equipment manufacturers, utilities, regulators and especially insulation community demotivated for their application. Hence the electrical performance of natural esters with different structures needs further evaluations, which is in the focus of the project BioLiq.
Contact
Prof. Dr. Melanie Brandmeier
97070 Würzburg
Research Professor for Environmental Remote Sensing
News
Supervised Thesis
Phd:
Marco Lutz (M.Eng.): Projekt AIVY
Jan Vahrenhold (M. Eng.): Projekt AIVY
Maximilian Hell (MSc): Kl an Radardaten (Zeitreihen) und Spektraldaten des Copernicus Programms zur Landnutzungsklassifikation
Master Thesis:
2025
Emilie Lüdicke (B. Eng.): Multisensor Data for Evaluating the Quantification of Photosynthetic Activity in Grapevines
Stefan Schönebeck (BSc.): Investigating climate variability with respect to viticulture in Franconia
Clara Eggers (B. Eng.): Investigating spectral properties for early detection of powdery mildew (Erysiphe Nectaron) on grapewine
2024
Raphael Lochschmidt (B. Eng): Comparative Analysis of Large Language Models Mistral 7B and RWKV - Concerning the Specific Mail Classification Task of Network Operator Responses on the Request of Line Information for Construction Projects
Laura Fehlhaber (BSc.): Al-based Classification of High-Resolution UAV Data for Monitoring Permafrost Dynamics in the Mackenzie Delta Region
Sönke Speckenwirth (BSc.): Instance Segmentation at Single Tree Level Using Multispectral UAV Images
Julia Anwander (BSc.): Evaluating different Deep Learning and Machine Learning approaches for tree health classification in the Black Forest, Harz region and Göttinger Forest
2023
Madeleine Speck (B.Eng.): Habitat characteristics and the decline of Erebia epistygne population - a Remote Sensing and GIS study.
Anja Kraus (B.Eng.): Impact of Climate Change on Soil Moisturein viticulture: A time series analysis
Adrian Meyer-Spelbrink (B.Eng.): Monitoring Vineyard Plant Health through Time-Series Analysis of Vegetation Indices and In-Situ Soil Moisture Measurements
Julia Anwander (B.Eng.): Evaluating different Deep Learning and Machine Learning approaches for tree health classification in the Black Forest, Harz region and Göttinger Forest
Levin Krämer (B.Eng.): Analyse der visuellen Auswirkungen des Ausbaus von Windenergieanlagen in der Planungsregion Mittelhessen im Rahmen des Wind-an-Land-Gesetzes anhand von Sichtbarkeitsanalysen, Landnutzungsklassen und Schutzgebieten
2021
Maximilian Hell (B.Eng.): Tree Species Classification using Deep Neural Networks on Lidar Point Clouds. (cooperation with Prof. Dr. Peter Krzystek)
2020
Wolfgang Deigele (BSc): Wind throw detection using deep learning on PlanetScope and high-resolution aerial images (cooperation with TUM. Prof. T. Kolbe)
Daniel Scharvogel (BSc): Detection of windthrows from Sentinel-2 data based on Deep Learning Algorithms (cooperation with University of Applied Sciences Weihnstephan-Triesdorf)
Eya Cherif (BSc): Synergetic use of Sentinel-2 and multi-temporal Sentinel-1 data for Land cover classification using advanced Deep Learning algorithms (cooperation with University of Passau, Prof. H. Kosch)
2019
Yuanze Chen (BSc): Lithological Classification based on Convolutional Neural Networks (CNNs) using multi-sensor data (coopertion with TUM, Prof. T. Huckle)
Nikolaos-Ioannis Bountos (BSc): Subpixel Classification of anthropogenic features using Deep-Learning on Sentinel-2 data (coopertion with TUM, Prof. T. Huckle)
Arthur Freddy Tchuente Tagne (BSc): Evaluation of boosting algorithms for exploration targeting using ArcGIS in the Mount Isa Inlier, Australia (cooperation with TU Clausthal, Prof. W. Busch)
2018
Zayd Mahmoud Hamdi (BSc): Forest Damage Assessment Using Deep Lerning on high-resolution Remote Sensing Data (cooperation with TUM, Prof. D. Straub)
2017
Mathias Wessel (BSc): The potential of Sentinel-2 data to classify tree species (cooperation with the University of Salzburg, Dirk Tiede)
Irving Gibran Cabrera Zamora (BSc): The use of Boosting Methods for Mineral Prospectivity Mapping within the ArcGIS Platform (cooperation with TUM, Prof. T. Huckle)
Bachelor Thesis:
2023
Marco Lutz: Die Austrocknung des Aralsees und ihre Flogen. Zeitreihenanalyse anhand Landsat Collection 2 Daten in der Google Earth Engine.
Emilie Lüdicke: Evaluierung vortrainierter KI-Algorithmen zur automatischen Erkennung von Siedlungen in historischen Topographischen Karten.
2022
Louisa Rall: Multitemporal Vocano Monitoring at Cumbre Vieja Volcano using Sentinel-2 data.
Nicola Schöpplein: Evaluating different methods for flood mapping using Sentinel-1 data from Sri Lanka
Teaching Areas
Teaching
- System Earth/Geoscience
- Machine Learning/Computer Vision
- Remote Sensing/ GIS
Publications
Publication list
2025
M. Lutz, E. Lüdicke, D. Heßdörfer, T. Ullmann, and M. Brandmeier: Estimating plant physiological parameters for vitis vinifera l. using in situ hyperspectral measurements and ensemble machine learning, Remote Sensing, vol. 17, no. 23, 2025, DOI: 10.3390/rs17233918.
Lutz, M., Brandmeier, M., Plank, S.: Assessment of different Synthetic Aperture Radar (SAR) systems for mapping floating pumice rafts after submarine volcanic eruptions. Remote Sensing Letters 17(1):26-39, 2025. DOI: 10.1080/2150704X.2025.2594764.
Vahrenhold, J.R.; Brandmeier, M.; Müller, M.S. MMTSCNet: Multimodal Tree Species Classification Network for Classification of Multi-Source, Single-Tree LiDAR Point Clouds. Remote Sens. 2025, 17, 1304. doi.org/10.3390/rs17071304
2024
Speckenwirth, S.; Brandmeier, M.; Paczkowski, S. TreeSeg—A Toolbox for Fully Automated Tree Crown Segmentation Based on High-Resolution Multispectral UAV Data. Remote Sens. 2024, 16, 3660. doi.org/10.3390/rs16193660
Hell, M.; Brandmeier, M. Identifying Plausible Labels from Noisy Training Data for a Land Use and Land Cover Classification Application in Amazônia Legal. Remote Sens. 2024, 16, 2080. doi.org/10.3390/rs16122080
Brandmeier, M.; Heßdörfer, D.; Siebenlist, P.; Meyer-Spelbrink, A.; Kraus, A. Time Series Analysis of Multisensor Data for Precision Viticulture—Assessing Microscale Variations in Plant Development with Respect to Irrigation and Topography. Remote Sens. 2024, 16, 1419. doi.org/10.3390/rs16081419
Anwander, J.; Brandmeier, M.; Paczkowski, S.; Neubert, T.; Paczkowska, M. Evaluating Different Deep Learning Approaches for Tree Health Classification Using High-Resolution Multispectral UAV Data in the Black Forest, Harz Region, and Göttinger Forest. Remote Sens. 2024, 16, 561.
2023
Hell, M., Brandmeier, M., Nüchter, A.: Transferability of Deep Learning Models for Land Use/Land Cover Classification. Publikationen der DGPF, Band 31, 2023.
I. Hahn, M. R. S. von der Wense Goncalves P. and M. Brandmeier, and G. Markl, “Habitat use of zygaena brizae and zygaena cynarae (lepidoptera, zygaenidae) in southern france.,” Nachr. entomol. Ver. Apollo, N.F. 44 (2), 65–80., 2023.
2022
Erbe, K., Brandmeier, M., Schmitt, M., Donaubauer, A., Liebscher, J.A., Kolbe, T.: Detektion von Fahrradständern in Luftbildern mittels Deep Learning, Publikationen der DGPF, Band 30, 2022
Cherif, E.; Hell, M.; Brandmeier, M. DeepForest: Novel Deep Learning Models for Land Use and Land Cover Classification Using Multi-Temporal and -Modal Sentinel Data of the Amazon Basin. Remote Sens. 2022, 14, 5000. doi.org/10.3390/rs14195000
Hell, M., Brandmeier, M., Briechle, S., Krzystek, P. (2022): Classification of Tree Species and Standing Dead Trees with Lidar Point Clouds Using Two Deep Neural Networks: PointCNN and 3DmFV-Net. PFG. doi.org/10.1007/s41064-022-00200-4
2020
Scharvogel, D., Brandmeier, M., Weis, M. (2020): A Deep Learning Approach for Calamity Assessment Using Sentinel-2 Data. Forests 11(12).
Deigele, W.; Brandmeier, M.; Straub, C. (2020): A Hierarchical Deep-Learning Approach for Rapid Windthrow Detection on PlanetScope and High-Resolution Aerial Image Data. Remote Sensing 12(2121).
2019
Brandmeier, M., Chen, Y. (2019): Lithological classification using multi-sensor data and convolutional neural networks. ISPRS Archives. Volume: XLII-2-W16-55-2019.
Hamdi, Z., Brandmeier, M., Straub, C. (2019): Forest Damage Assessment Using Deep Learning on High Resolution Remote Sensing Data. Remote Sensing 11(17).
Brandmeier, M. (2019): The Anatomy of Supervolcanoes. In: GIS for Science: Applying Mapping and Spatial Analytics. Esri Press.
Brandmeier, M., Cabrera, I., Nykänen, V., Middleton, M. (2019): The potential of boosting for prospectivity modelling: Introducing a new GIS toolbox. Natural Resources Research. doi.org/10.1007/s11053-019-09483-8.
2018
Wessel, M; Brandmeier, M.; Tiede, D. (2018) Evaluation of Different Machine Learning Algorithms for Scalable Classification of Tree Types and Tree Species Based on Sentinel-2 Data. Remote Sensing 10(9).
2017
Brandmeier, M., Wessel, M. (2017) Workflows für Bilddaten und Big Data Analytics - Das Potenzial von Sentinel-2-Daten zur Baumartenklassifizierung. In: Meinel, Gotthard; Schumacher, Ulrich; Schwarz, Steffen; Richter, Benjamin (Hrsg.): Flächennutzungsmonitoring IX: Nachhaltigkeit der Siedlungs- und Verkehrsentwicklung?. Berlin : Rhombos-Verlag, 2017, (IÖR-Schriften; 73), S. 135-142
2016
Brandmeier, M. and Wörner, G. (2016): Compositional variations of ignimbrite magmas in the Central Andes over the past 26 Ma — A multivariate statistical perspective. Lithos 262, 713-728.
Zimmermann, R., Brandmeier, M., Andreani, L., Mhopjeni, K. and Gloaguen, R. (2016) Remote Sensing Exploration of Nb-Ta-LREE-Enriched Carbonatite (Epembe/Namibia). Remote Sensing 8, 620.
2015
Freymuth, H., Brandmeier, M., Wörner, G. (2015): The origin and crust/mantle mass balance of Central Andean ignimbrite magmatism constrained by oxygen and strontium isotopes and erupted volumes: Contributions to Mineralogy and Petrology, v. 169, p. 1-24.
2014
Székely, B., Koma, Z., Karátson, D., Dorninger, P., Wörner, G., Brandmeier, M., Nothegger, C. (2014): Automated recognition of quasi‐planar ignimbrite sheets as paleosurfaces via robust segmentation of digital elevation models: an example from the Central Andes. Earth Surface Processes and Landforms.
2013
Brandmeier, M., Erasmi, S., Hansen, C., Höweling, A., Nitzsche, K., Ohlendorf, T., Mamani, M. and Wörner, G. (2013): Mapping patterns of mineral alteration in volcanic terrains using ASTER data and field spectrometry in Southern Peru. Journal of South American Earth Sciences 48, 296-314.
2011
Brandmeier, M., Kuhlemann, J., Krumrei, I., Kappler, A., and Kubik, P.W. (2011): New challenges for tafoni research. A new approach to understand processes and weathering rates: Earth Surface Processes and Landforms, v. 36, p. 839-852.
2010
Brandmeier, M. (2010): Remote sensing of Carhuarazo volcanic complex using ASTER imagery in Southern Peru to detect alteration zones and volcanic structures – a combined approach of image processing in ENVI and ArcGIS/ArcScene: Geocarto International, v. 25, p. 629-648
Career
Vita
2021 Professorin für Geoinformatik und Fernerkundung
2017 Associate Researcher GFZ Potsdam
2016-2021 Senior Scientist Esri Deutschland
2014-2016 Postdoc Helmholtz Institut Dresden-Rossendorf
2014 Promotion (Dr.rer.nat.), Georg-August-Universität Göttingen
Titel der Dissertation: "A remote sensing and geospatial statstical approach to understanding distribution and evolution of ignimbrites in the Central Andes with a focus on Southern Peru"
2010 Auslandsaufenthalt Australien (University of Wollongong, CSIRO)
2008 Diplom Geographie, Geologie und Geochemie, Eberhard-Karls-Universität Tübingen
Titel der Diplomarbeit: "Raten und Prozesse der Tafoniverwitterung auf Korsika"
2004/2005 Auslandssemester Universidad Nacional San Miguel de Tucumán, Argentinien
2004 Vordiplom Geographie, Lateinamerikanistik und Umweltpsychologie, Katholische Universität Eichstätt-Ingolstadt
2002 Staatlich geprüfter Management Assistant (Tourismus), Freiburg
Additional Information
Membership
European Geoscience Union (EGU)
International Society for Photogrammetry and Remote Sensing (ISPRS)
Deutsche Gesellschaft für Photogrammetrie, Fernerkundung und Geoinformatik (DGPF)
Member of the Editorial Board Zeitschrift für Geodäsie, Geoinformatik und Landmanagement
Association of Wildlife and Nature Photographers (GDT)





