direkt zum Inhalt springen

direkt zum Hauptnavigationsmenü

Sie sind hier

TU Berlin

Page Content

Prof. Dr. Birgit Kleinschmit

Lupe

Head

Phone: +49 (0)30 / 314 - 72 84 7

Email:

Room: EB 235a
Consultation hour: by arrangement

Personal Data
Date and place of birth: 1973 (Münster, Westphalia, Germany)
Employment and academic vita
2011
Announced as University Professor and Head of the Department of Geoinformation in Environmental Planning at the Institute of Landscape Architecture and Environmental Planning of the Berlin University of Technology
2003-2011
Assistant Professor (“Juniorprofessorin”) at the Department of Geoinformation Processing for Landscape and Environmental Planning of the Berlin University of Technology
2001-2003
Consultant and software developer, INTEND Geoinformatik GmbH, Kassel, Germany
1998-2001
Scientific staff member ("Wissenschaftliche Mitarbeiterin"), Georg-August-Universität, Göttingen, Department of Forest Assessment & Remote Sensing, Forest Growth, Forest Planning
1993-1998
Diploma study of forest science at the University of Göttingen
Degrees
2001
Doctorate (doctor forest), Georg-August Universität Göttingen, Grade: magna cum laude
1998
Diploma, Georg-August Universität Göttingen, Grade: 1,9 (on a scale from 1 to 6, where 1 is highest)

Research Topics

    • Studying land use dynamics on different scales to understand natural and human environmental systems using geospatial information technologies (GIS & Remote Sensing)
    • Modelling environmental changes and assessing the impacts on humans and ecosystems
    • Knowledge-based combination of geoinformation and remote sensing data
    • Evaluating of new sensor technologies

      Important Functions, Awards, Honors

      • Since 2019     
        Member of Scientific Advisory Board on Forest Policy at the Federal Ministry of Food and Agriculture

      • Since 2019      
        Research Transfer advisory board Member, TU Berlin

      • Since 2018
        Deputy Director, Institute of Landscape Architecture and Environmental Planning, TU Berlin

      • Since 2015      
        Co-speaker of the DFG research training group Urban water interfaces

      • Since 2016      
        Admissions and Steering Committee member of the Berlin International Graduate School in Model and Simulation based Research (BIMoS), TU Berlin

      • 2012-2018        
        Leader of the Special Interest Group „Analysis of remote sensing data” of the German Association for Photogrammetry, Remote Sensing and Geoinformation

      • Since 2018      
        Member of the Commission for the Allocation of Doctoral Grants of Elsa Neumann Scholarships

      • Since 2010      
        Steering Committee member of Geo.X – Research Network for Geosciences in Berlin and Potsdam

      Articles

      Adapting a Natura 2000 field guideline for a remote sensing-based assessment of heathland conservation status
      Citation key Schmidt20170
      Author Schmidt, J. and Fassnacht, F. E. and Neff, C. and Lausch, A. and Kleinschmit, B. and Förster, M. and Schmidtlein, S.
      Pages 61-71
      Year 2017
      DOI http://dx.doi.org/10.1016/j.jag.2017.04.005
      Journal International Journal of Applied Earth Observation and Geoinformation
      Volume 60
      Abstract Remote sensing can be a valuable tool for supporting nature conservation monitoring systems. However, for many areas of conservation interest, there is still a considerable gap between field-based operational monitoring guidelines and the current remote sensing-based approaches. This hampers application in practice of the latter. Here, we propose a remote sensing approach for mapping the conservation status of Calluna-dominated Natura 2000 dwarf shrub habitats that is closely related to field mapping schemes. We transferred the evaluation criteria of the field guidelines to three related variables that can be captured by remote sensing: (1) coverage of the key species, (2) stand structural diversity, and (3) co-occurring species. Continuous information on these variables was obtained by regressing ground reference data from field surveys and UAV flights against airborne hyperspectral imagery. Merging the three resulting quality layers in an RGB representation allowed for illustrating the habitat quality in a continuous way. User-defined thresholds can be applied to this stack of quality layers to derive an overall assessment of habitat quality in terms of nature conservation, i.e. the conservation status. In our study, we found good accordance of the remotely sensed data with field-based information for the three variables key species, stand structural diversity and co-occurring vegetation (R2 of 0.79, 0.69, and 0.71, respectively) and it was possible to derive meaningful habitat quality maps. The conservation status could be derived with an accuracy of 65%. In interpreting these results it should be considered that the remote sensing based layers are independent estimates of habitat quality in their own right and not a mere replacement of the criteria used in the field guidelines. The approach is thought to be transferable to similar regions with minor adaptions. Our results refer to Calluna heathland which we consider a comparably easy target for remote sensing. Hence, the transfer of field guidelines to remote sensing indicators was rather successful in this case but needs further evaluation for other habitats.
      Bibtex Type of Publication Kleinschmit
      Link to original publication Download Bibtex entry

      Other Publications

      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.. Ecological Informatics. Elsevier, 1-10.


      Kleinschmit, B., Singelton, A. and Gärtner, P. (2021). Identifying drivers and barriers of floodplain vegetation growth in the lower reaches of the Tarim River, China.. Sustainable Management of River Oases along the Tarim River/China (SuMaRiO). Schwerzerbart, 87-101.


      Hölzl, S. E., Veskov, M., Scheibner, T., Le, T. T. and Kleinschmit, B. (2021). Vulnerable socioeconomic groups are disproportionately exposed to multiple environmental burden in Berlin - implications– for planning. International journal of urban sustainable development, 1-18.


      Gränzig, T., Fassnacht, F. E., Kleinschmit, B. and Förster, M. (2021). Mapping the fractional coverage of the invasive shrub Ulex europaeus with multi-temporal Sentinel-2 imagery utilizing UAV orthoimages and a new spatial optimization approach.. International Journal of Applied Earth Observation and Geoinformation


      Bauhus, J., Seeling, U., Dieter, M., Farwig, N., Hafner, A., Kätzel, R., Kleinschmit, B., Lang, F., Lindner, M., Möhring, B., Müller, J., M., N., Richter, K. and Schraml, U. (2021). Die Anpassung von Wäldern und Waldwirtschaft an den Klimawandel. Berichte über Landwirtschaft-Zeitschrift für Agrarpolitik und Landwirtschaft, 1-158.


      Vulova, S., Meier, F., Rocha, A. D., Quanz, J., Nouri, H. and and Kleinschmit, B. (2021). Modeling urban evapotranspiration using remote sensing, flux footprints, and artificial intelligence. Science of The Total Environment, 1-13.


      Döpper, V. U., Rocha, A. D., Gränzig, T., Kleinschmit, B. and Förster, M. (2021). Using radiative transfer models for mapping soil moisture content under grassland with UAS-borne hyperspectral data. Proc. SPIE 11856, Remote Sensing for Agriculture, Ecosystems, and Hydrology XXIII


      2020

      Vulova, S., Meier, F., Fenner, D., Nouri, H. and Kleinschmit, B. (2020). Summer Nights in Berlin, Germany: Modeling Air Temperature Spatially With Remote Sensing, Crowdsourced Weather Data, and Machine Learning. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 1-15.


      Holtgrave, A., Röder, N., Ackermann, A., Erasmi, S. and Kleinschmit, B. (2020). Comparing Sentinel-1 and -2 Data and Indices for Agricultural Land Use Monitoring. remote sensing, 1-27.


      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. Earth System Science Data, 2289-2309.


      Zusatzinformationen / Extras

      Quick Access:

      Schnellnavigation zur Seite über Nummerneingabe

      Auxiliary Functions

      This site uses Matomo for anonymized webanalysis. Visit Data Privacy for more information and opt-out options.

      Geoinformation in Environmental Planning Lab
      Office EB5
      Straße des 17. Juni 145
      D - 10623 Berlin
      Phone: +49 (0)30 314 - 73 29 0
      Fax: +49 (0)30 314 - 23 50 7