Matthias moved for a PostDoc position to the Remote Sensing research group at TU Wien. |
Role of vegetation phenology and dynamics in the Earth system |
Methods - model-data integration - remote sensing of vegetation - time series analysis: trends, breakpoints, land surface phenology - global vegetation modelling |
Regional focus: global, with focus on boreal and arctic regions |
technical: (spatial) data analysis with R; see for example the course material about how to use spatial data in R or the greenbrown package for analysis of trends and trend changes on earth observation data. |
since 01/2016 PostDoc, Technische Universität Wien, Austria |
06/2015 Graduation (Dr. rer. nat.), University Jena, Germany Thesis: "Controls on Global Greening, Phenology, and the Enhanced Seasonal CO2 Amplitude. Integrating Decadal Satellite Observations and Global Ecosystem Models" |
01/2011-12/2015 Researcher (PhD candidate, PostDoc) at MPI for Biogeochemistry, Jena, Germany |
06/2010-11/2010 Visiting MSc student at Potsdam-Institute for Climate Impact Research, Research Domain Earth System Analysis, Potsdam, Germany |
08/2009-11/2010 Scientific assistant at Department for Earth Observation, University Jena, Germany Organization of a hyperspectral field campaign inside ESA's EO-LDAS project (Earth Observation Land Data Assimilation Scheme) |
10/2008-12/2010 Study of Geoinformatics, University Jena, Germany Master of Science (Geoinformatics), University Jena, Germany Majors: Remote Sensing, Hydrological Modeling, GIS Thesis: "Permafrost-Fire Interactions in the Circumpolar Boreal Zone - An Analysis using Earth Observation Products and Simulations with a Dynamic Global Vegetation Model based on Global Climate Projections" |
10/2005-09/2008 Study of Geography, University Jena Bachelor of Science (Geography), University Jena, Germany Thesis: "Raum-zeitliche Analyse atmosphärischen Kohlenstoffs in Sibirien mit ENVISAT-SCIAMACHY-Daten" |
The greenbrown R package is a collection of functions to analyse trends and trend changes in gridded time series like from satellite observations or climate model simulations. See http://greenbrown.r-forge.r-project.org/ for a description and to receive the code. |
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