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Dr. Michael Förster

Lupe

Senior Scientist

Phone: +49 (0)30 / 314 - 72 79 8

Email:

Room: EB 236b
Consultation hour: by arrangement

Personal Data
Date and place of birth: 1975 (Burgstädt, Saxony, Germany)
Employment and academic vita
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
Degrees
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

Articles

2019

Kattenborn, T., Lopatina, J., Förster, M., Braun, A. C. and Fassnacht, F. E. (2019): UAV data as alternative to field sampling to map woody invasive species based on combined Sentinel-1 and Sentinel-2 data. Remote Sensing of Environment, 227(2019), pp. 61-73.


2018

Holtgrave, A.-K., Förster, M., Greifeneder, F., Notarnicola, C. and Kleinschmit, B. (2018): Estimation of Soil Moisture in Vegetation-Covered Floodplains with Sentinel-1 SAR Data Using Support Vector Regression. PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 2018, pp. 85–101.


Klinke, R., Kuechly, H., Frick, A., Förster, M., Schmidt, T., Holtgrave, A.-K. a. K. B., Spengler, D. and Neumann, C. (2018): Indicator-Based Soil Moisture Monitoring ofWetlands by Utilizing Sentinel and Landsat Remote Sensing Data. PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 2018, pp. 71–84.


2017


Schmidt, J., Fassnacht, F. E., Neff, C., Lausch, A., Kleinschmit, B., Förster, M. and Schmidtlein, S. (2017): Adapting a Natura 2000 field guideline for a remote sensing-based assessment of heathland conservation status. International Journal of Applied Earth Observation and Geoinformation, 60, pp. 61-71. doi: http://dx.doi.org/10.1016/j.jag.2017.04.005


2016

Gärtner, P., Förster, M. and Kleinschmit, B. (2016): The benefit of synthetically generated RapidEye and Landsat 8 data fusion time series for riparian forest disturbance monitoring. Remote Sensing of Environment, 2016(177), pp. 237-247. doi: doi:10.1016/j.rse.2016.01.028


Neumann, C., Förster, M., Kleinschmit, B. and Itzerott, S. (2016): Utilizing a PLSR-Based Band-Selection Procedure for Spectral Feature Characterization of Floristic Gradients. EEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2016, pp. 1-15. doi: 10.1109/JSTARS.2016.2536199


2015

Clasen, A., Somers, B., Pipkins, K., Tits, L., Segl, K., Brell, M., Kleinschmit, B., Spengler, D., Lausch, A. and Förster, M. (2015): Spectral Unmixing of Forest Crown Components at Close Range, Airborne and Simulated Sentinel-2 and EnMAP Spectral Imaging Scale. remote sensing, 2015(7), pp. 26. doi: 10.3390/rs71115361


Baur, A. H., Lauf, S., Förster, M. and Kleinschmit, B. (2015): Estimating greenhouse gas emissions of European cities — Modeling emissions with only one spatial and one socioeconomic variable. Science of the Total Environment, 2015(520), pp. 49-58. doi: 10.1016/j.scitotenv.2015.03.030


Rocchini, D., Andreo, V., Förster, M., Gutierrez, A., Gillespie, W., Hauffe, H., He, K., Kleinschmit, B., Mairota, P., Marcantonio, M., Metz, M., Nagendra, H., Pareeth, S., Ponti, L., Ricotta, C., Rizzoli, A., Schaab, G., Zebisch, M., Zorer, R. and Neteler, M. (2015): Potential of remote sensing to predict species invasions: A modelling perspective. Progress in Physical Geography, 39(3), pp. 283-309. doi: 10.1177/0309133315574659


Other Publications

The spatial dimension of urban greenhouse gas emissions: analyzing the influence of spatial structures and LULC patterns in European cities
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.
Link to original publication Download Bibtex entry

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Fachgebiet Geoinformation in der Umweltplanung
Sekretariat EB5
Room EB 236a
Straße des 17. Juni 145
D - 10623 Berlin
Tel.: +49 (0)30 314 - 73 29 0
Fax: +49 (0)30 314 - 23 50 7