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Dr. Michael Förster
- © M. Förster
Senior Scientist
Phone: +49 (0)30 / 314 - 72 79 8
Email: michael.foerster(at)tu-berlin.de
Room: EB 236b
Consultation hour: by arrangement
| Date and place of birth: 1975 (Burgstädt, Saxony, Germany) |
| 2018 | Visiting Scientist at the Joint Research Center (JRC) in Ispra, Italy (Bioeconomy Unit) |
| 2012 | Visiting Scientist at the University Utrecht, Netherlands (Department of Physical Geography) |
| 2010 | Visiting Scientist at the European Academy Bolzano (EURAC), Italy (Institute for Applied Remote Sensing) |
| since 2009 | Post-doctoral Research Fellow Technische Universität Berlin, Institute of Landscape Architecture and Environmental Planning, Department of Geoinformation Processing for Landscape and Environmental Planning |
| 2003-2008 | Research Scientist Technische Universität Berlin, Institute of Landscape Architecture and Environmental Planning, Department of Geoinformation Processing for Landscape and Environmental Planning |
| 2001-2003 | Consultant and GIS-Coordinator Environmental Consulting and Planning Agency - Froelich & Sporbeck, Potsdam, Germany |
| 1999-2001 | Research Associate Geo-Forschungs-Zentrum (GFZ) Potsdam, Section 1.4 (Remote Sensing) |
| 1998-1999 | Exchange Student (ERASMUS) University of Southampton, UK |
| 1996-2003 | Studies of Geoecology Universität Potsdam, Germany |
| 2003 | Diploma, University of Potsdam Grade: 1,1 (on a scale from 1 to 6, where 1 is highest) |
| 2009 | Doctorate, Technische Universität Berlin, summa cum laude |
Research Topics
- Development of methods to analyse the dynamics of ecosystems from time-series (optical and SAR), especially for degradation processes or abrupt damages (e.g. caused by fire or storms)
- Relation of temporal and spectral signals to plant traits and biophysical variables (xantophyll, nitrogen, chlorophyll and fluorescence)
- Derivation of operationalizable and comprehensive environmental indicators that are needed for the effective implementation of management measures (e.g. within the framework of the European NATURA 2000 requirements) or for a better understanding of ecosystems
- Interaction of vegetation structure, which can be measured with LiDAR or SAR, with spectral information for the evaluation of forest properties
- Combining spatially very high resolution data (drones) with satellite data to understand ecohydrological processes and especially to derive hydrological variables such as soil moisture content or interception
Other Publications
| Citation key | baur2015a |
|---|---|
| Author | Baur, A. H. and Förster, M. and Kleinschmit, B. |
| Year | 2015 |
| DOI | 10.1007/s10980-015-0169-5 |
| Journal | Landscape Ecology |
| Publisher | Springer |
| Abstract | Abstract Context Integrative mitigation and adaptation strategies are needed to counter climate change. Indicators can be valuable that focus on the specific relevance of cities’ socioeconomic and spatial properties. While previous analyses have identified socioeconomic influences on urban greenhouse gas emissions, information about the role of spatial urban structures and land use and land cover patterns is sparse. Objective This study advances the use of spatial metrics for analyzing the linkages between the spatial properties of a city and its greenhouse gas emissions. Methods The relationship between nine types of spatial structure, four land use and land cover-based indicators, and the emissions of 52 European cities is investigated by spatially and statistically analyzing high resolution data from European Union’s ‘‘Urban Atlas’’. Results Spatial determinants of urban greenhouse gas emissions are identified, indicating a strong connection between urban sprawl and increasing emissions. In particular, high amounts of sparsity in the urban fabric within large distances to the city center relate to increased per capita emissions. Thus, a 10 % reduction of very low density urban fabrics is correlated with 9 % fewer emissions per capita. In contrast, high amounts of fragmented, dense urban patches relate with lower emissions. Conclusions This study links urban spatial properties and land use and land cover compositions to greenhouse gas emissions and advances the understanding of urban sprawl. Future research needs to combine knowledge about socioeconomic drivers with information about the identified spatial influences of urban greenhouse gas emissions to help cities realize their climate change mitigation potential. |