Dr. Kristin Vogel

Contact

University of  Potsdam,
Institute of Geosciences

Dr. Kristin Vogel
Building 1, Room 1.22

Karl-Liebknecht-Str. 24-25
14476 Potsdam-Golm
E-mail:
kvog@geo.uni-potsdam.de
Phone:
+49 331 977 6257
Fax:
+49 331 977 5700
Dr. Kristin Vogel

 

  • Biography
  • Research
  • Teaching
  • Publications

Biography

since 2010
Research assistant at Inst. of Earth and Environmental Science, Potsdam University
2014
Doctor rer. nat. in General Geophysics, Potsdam University
2009 - 2010
Employee at DTU Aqua - National Institute of Aquatic Resources, Denmark
2009
Diploma in Mathematics, Potsdam University
2007
Intern at Tel-Tek (dept. POSTEC), Norway

Research

Considering natural hazards and risks, we are permanently confronted with issues of uncertainty, rising questions as "How can we determine and capture different kinds of uncertainty in our models?" or "How can we communicate uncertainty to decision makers, politicians and public?" 

My interest in the application and adoption of methods from (Bayesian) statistics and the field of machine learning (i.e. graphical networks such as Bayesian networks) for probabilistic natural hazard assessments. 

Teaching

MGEW23 Quantitative basis of the analysis of natural hazards

MGPW12 Introduction to Bayesian Networks for Geoscientists

Publications

Vogel, K., J. Laudan, T. Sieg, V. Rözer, B. Winter, A.H. Thieken (2017):
Data collection for a damage assessment after the flash flood in Braunsbach
(Germany) in May 2016. GFZ Data Services. DOI: 10.5880/fidgeo.2017.015

Laudan, J., V. Rözer, T. Sieg, K. Vogel, & A.H. Thieken (2017): Dam-
age assessment in Braunsbach 2016: data collection and analysis for an
improved understanding of damaging processes during flash floods. Natural
Hazards and Earth System Sciences, 17(12),2163-2179. DOI: 10.5194/nhess-17-2163-2017

Vogel, K. (2017): Learning Markov Blankets - Extending on a MAP
Criterion for Bayesian Network Learning. In Safety, Reliability, Risk, Re-
silience and Sustainability of Structures and Infrastructure, 12th Interna-
tional Conference on Structural Safety & Reliability, Vienna, Austria, 6-10
August 2017, 2868-2877.

Sieg, T., K. Vogel, B. Merz, and H. Kreibich (2017), Tree-based flood damage modeling of companies: Damage processes and model performance. Water Resour. Res., 53, 6050–6068, DOI: 10.1002/2017WR020784

Vogel, K., U. Ozturk, A. Riemer, J. Laudan, T. Sieg, D. Wendi, A. Agarwal, V. Rözer, O. Korup, A. Thieken, 2017. Die Sturzflut von Braunsbach am 29. Mai 2016 - Entstehung, Ablauf und Schäden eines “Jahrhundertereignisses”. Teil 2: Geomorphologische Prozesse und Schadensanalyse. Hydrologie & Wasserbewirtschaftung, 61(3), 163-175, DOI: 10.5675/HyWa_2017,3_2

Vogel, K., Riggelsen, C., Korup, O., Scherbaum, F., 2014. Bayesian network learning for natural hazard analyses, Natural Hazards and Earth System Science, 14(9), 2605-2626, DOI: 10.5194/nhess-14-2605-2014

Schröter, K., Kreibich, H., Vogel, K., Riggelsen, C., Scherbaum, F., Merz, B., 2014. How useful are complex flood damage models?, Water Resources Research, 50(4), 3378–3395, DOI: 10.1002/2013WR014396

Vogel, K., 2014. Applications of Bayesian networks in natural hazard assessmentsDoctoral dissertation, Universitätsbibliothek

Vogel, K., Riggelsen, C., Scherbaum, F., Schroeter, K., Kreibich, H., Merz, B., 2013. Challenges for Bayesian Network Learning in a Flood Damage Assessment Application. In Proceedings of the 11th International Conference on Structural Safety & Reliability, New York, NY, USA, ICOSSAR'13

Vogel, K., Riggelsen, C., Merz, B., Kreibich, H., and F. Scherbaum, 2012. Flood Damage and Influencing Factors: A Bayesian Network Perspective. Conf. on Probabilistic Graphical Models, Granada, Spain, PGM'12, ISBN: 978-84-15536-57-4, pp. 347-354.

Vogel, K., Riggelsen, C., Kühn, N., Scherbaum, F., 2012. Graphical Models as Surrogates for Complex Ground Motion Models. 11th International Conference on Artificial Intelligence and Soft Computing, ICAISC'12, ISBN 978-3-642-29346-7, pp. 188-195.

Biography

since 2010
Research assistant at Inst. of Earth and Environmental Science, Potsdam University
2014
Doctor rer. nat. in General Geophysics, Potsdam University
2009 - 2010
Employee at DTU Aqua - National Institute of Aquatic Resources, Denmark
2009
Diploma in Mathematics, Potsdam University
2007
Intern at Tel-Tek (dept. POSTEC), Norway

Research

Considering natural hazards and risks, we are permanently confronted with issues of uncertainty, rising questions as "How can we determine and capture different kinds of uncertainty in our models?" or "How can we communicate uncertainty to decision makers, politicians and public?" 

My interest in the application and adoption of methods from (Bayesian) statistics and the field of machine learning (i.e. graphical networks such as Bayesian networks) for probabilistic natural hazard assessments. 

Teaching

MGEW23 Quantitative basis of the analysis of natural hazards

MGPW12 Introduction to Bayesian Networks for Geoscientists

Publications

Vogel, K., J. Laudan, T. Sieg, V. Rözer, B. Winter, A.H. Thieken (2017):
Data collection for a damage assessment after the flash flood in Braunsbach
(Germany) in May 2016. GFZ Data Services. DOI: 10.5880/fidgeo.2017.015

Laudan, J., V. Rözer, T. Sieg, K. Vogel, & A.H. Thieken (2017): Dam-
age assessment in Braunsbach 2016: data collection and analysis for an
improved understanding of damaging processes during flash floods. Natural
Hazards and Earth System Sciences, 17(12),2163-2179. DOI: 10.5194/nhess-17-2163-2017

Vogel, K. (2017): Learning Markov Blankets - Extending on a MAP
Criterion for Bayesian Network Learning. In Safety, Reliability, Risk, Re-
silience and Sustainability of Structures and Infrastructure, 12th Interna-
tional Conference on Structural Safety & Reliability, Vienna, Austria, 6-10
August 2017, 2868-2877.

Sieg, T., K. Vogel, B. Merz, and H. Kreibich (2017), Tree-based flood damage modeling of companies: Damage processes and model performance. Water Resour. Res., 53, 6050–6068, DOI: 10.1002/2017WR020784

Vogel, K., U. Ozturk, A. Riemer, J. Laudan, T. Sieg, D. Wendi, A. Agarwal, V. Rözer, O. Korup, A. Thieken, 2017. Die Sturzflut von Braunsbach am 29. Mai 2016 - Entstehung, Ablauf und Schäden eines “Jahrhundertereignisses”. Teil 2: Geomorphologische Prozesse und Schadensanalyse. Hydrologie & Wasserbewirtschaftung, 61(3), 163-175, DOI: 10.5675/HyWa_2017,3_2

Vogel, K., Riggelsen, C., Korup, O., Scherbaum, F., 2014. Bayesian network learning for natural hazard analyses, Natural Hazards and Earth System Science, 14(9), 2605-2626, DOI: 10.5194/nhess-14-2605-2014

Schröter, K., Kreibich, H., Vogel, K., Riggelsen, C., Scherbaum, F., Merz, B., 2014. How useful are complex flood damage models?, Water Resources Research, 50(4), 3378–3395, DOI: 10.1002/2013WR014396

Vogel, K., 2014. Applications of Bayesian networks in natural hazard assessmentsDoctoral dissertation, Universitätsbibliothek

Vogel, K., Riggelsen, C., Scherbaum, F., Schroeter, K., Kreibich, H., Merz, B., 2013. Challenges for Bayesian Network Learning in a Flood Damage Assessment Application. In Proceedings of the 11th International Conference on Structural Safety & Reliability, New York, NY, USA, ICOSSAR'13

Vogel, K., Riggelsen, C., Merz, B., Kreibich, H., and F. Scherbaum, 2012. Flood Damage and Influencing Factors: A Bayesian Network Perspective. Conf. on Probabilistic Graphical Models, Granada, Spain, PGM'12, ISBN: 978-84-15536-57-4, pp. 347-354.

Vogel, K., Riggelsen, C., Kühn, N., Scherbaum, F., 2012. Graphical Models as Surrogates for Complex Ground Motion Models. 11th International Conference on Artificial Intelligence and Soft Computing, ICAISC'12, ISBN 978-3-642-29346-7, pp. 188-195.