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Dr. Michael Förster

Lupe [1]
© M. Förster

Senior Scientist

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

Email: michael.foerster(at)tu-berlin.de [2]

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

Publications

  • Articles
  • Other Publications

Articles

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2021

Rocchini, D., Salvatori, N., Beierkuhnlein, C., Chiarucci, A., de Boissieu, F., Förster, M., Garzon-Lopez, C., Gillespie, T. W., Hauffe, H., He, K., Kleinschmit, B., Lenoir, J., Malavasi, M., Moudrý, V., Nagendra, H., Payne, D., Šímová, P., Torresani, M., Wegmann, M. and Féret, J.-B. (2021): From local spectral species to global spectral communities: A benchmark for ecosystem diversity estimate by remote sensing. [8]. Ecological Informatics, 61, pp. 1-10. doi: https://doi.org/10.1016/j.ecoinf.2020.101195 [9]

2020

Fersch, B., Francke, T., Heistermann, M., Schrön, M., Döpper, V., Jakobi, J., Baroni, G., Blume, T., Bogena, H., Budach, C., Gränzig, T., Förster, M., Güntner, A., Hendricks Franssen, H., Kasner, M., Köhli, M., Kleinschmit, B., Kunstmann, H., Patil, A., Rasche, D., Scheiffele, L., Schmidt, U., Szulc-Seyfried, S., Weimar, J., Zacharias, S., Zreda, M., Heber, B., Kiese, R., Mares, V., Mollenhauer, H., Völksch, I. and Oswald, S. (2020): A dense network of cosmic-ray neutron sensors for soil moisture observation in a highly instrumented pre-Alpine headwater catchment in Germany [10]. Earth System Science Data, 12, pp. 2289-2309. doi: https://doi.org/10.5194/essd-12-2289-2020 [11]

Fenske, K., Feilhauer, H., Förster, M., Stellmes, M. and Waske, B. (2020): Hierarchical classification with subsequent aggregation of heathland habitats using an intra-annual RapidEye time-series [12]. International Journal of Applied Earth Observation and Geoinformation, 87, pp. 1-13. doi: https://doi.org/10.1016/j.jag.2019.102036 [13]

Döpper, V., Gränzig, T., Kleinschmit, B. and Förster, M. (2020): Challenges in UAS-Based TIR Imagery Processing: Image Alignment and Uncertainty Quantification. [14]. remote sensing, 12(1552), pp. 1-22. doi: https://doi.org/10.3390/rs12101552 [15]

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 [16]. 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 [17]. 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 [18]. PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 2018, pp. 71–84.

2017

Möller, M., Gerstmann, H., Gao, F., Dahms, T. C. and Förster, M. (2017): Coupling of phenological information and simulated vegetation index time series: Limitations and potentials for the assessment and monitoring of soil erosion risk [19]. Catena, 170, pp. 192-205. doi: 10.1016/j.catena.2016.11.016 [20]

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 [21]. International Journal of Applied Earth Observation and Geoinformation, 60, pp. 61-71. doi: http://dx.doi.org/10.1016/j.jag.2017.04.005 [22]

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 [23]. Remote Sensing of Environment, 2016(177), pp. 237-247. doi: doi:10.1016/j.rse.2016.01.028 [24]

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Other Publications

You are at page:1 | 2 [30] | 3 [31] | 4 [32] | 5 [33] | 6 [34] | 7 [35] | 8 [36] | 9 [37]

next >> [38]

2021

Rocchini, D., Salvatori, N., Beierkuhnlein, C., Chiarucci, A., de Boissieu, F., Förster, M., Garzon-Lopez, C., Gillespie, T. W., Hauffe, H., He, K., Kleinschmit, B., Lenoir, J., Malavasi, M., Moudrý, V., Nagendra, H., Payne, D., Šímová, P., Torresani, M., Wegmann, M. and Féret, J.-B. (2021): From local spectral species to global spectral communities: A benchmark for ecosystem diversity estimate by remote sensing. [39]. Ecological Informatics, 61, pp. 1-10. doi: https://doi.org/10.1016/j.ecoinf.2020.101195 [40]

2020

Fersch, B., Francke, T., Heistermann, M., Schrön, M., Döpper, V., Jakobi, J., Baroni, G., Blume, T., Bogena, H., Budach, C., Gränzig, T., Förster, M., Güntner, A., Hendricks Franssen, H., Kasner, M., Köhli, M., Kleinschmit, B., Kunstmann, H., Patil, A., Rasche, D., Scheiffele, L., Schmidt, U., Szulc-Seyfried, S., Weimar, J., Zacharias, S., Zreda, M., Heber, B., Kiese, R., Mares, V., Mollenhauer, H., Völksch, I. and Oswald, S. (2020): A dense network of cosmic-ray neutron sensors for soil moisture observation in a highly instrumented pre-Alpine headwater catchment in Germany [41]. Earth System Science Data, 12, pp. 2289-2309. doi: https://doi.org/10.5194/essd-12-2289-2020 [42]

Fenske, K., Feilhauer, H., Förster, M., Stellmes, M. and Waske, B. (2020): Hierarchical classification with subsequent aggregation of heathland habitats using an intra-annual RapidEye time-series [43]. International Journal of Applied Earth Observation and Geoinformation, 87, pp. 1-13. doi: https://doi.org/10.1016/j.jag.2019.102036 [44]

Döpper, V., Gränzig, T., Kleinschmit, B. and Förster, M. (2020): Challenges in UAS-Based TIR Imagery Processing: Image Alignment and Uncertainty Quantification. [45]. remote sensing, 12(1552), pp. 1-22. doi: https://doi.org/10.3390/rs12101552 [46]

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 [47]. 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 [48]. 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 [49]. PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 2018, pp. 71–84.

2017

Möller, M., Gerstmann, H., Gao, F., Dahms, T. C. and Förster, M. (2017): Coupling of phenological information and simulated vegetation index time series: Limitations and potentials for the assessment and monitoring of soil erosion risk [50]. Catena, 170, pp. 192-205. doi: 10.1016/j.catena.2016.11.016 [51]

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 [52]. International Journal of Applied Earth Observation and Geoinformation, 60, pp. 61-71. doi: http://dx.doi.org/10.1016/j.jag.2017.04.005 [53]

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 [54]. Remote Sensing of Environment, 2016(177), pp. 237-247. doi: doi:10.1016/j.rse.2016.01.028 [55]

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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
e-mail query [65]
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