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Prof. Dr. Birgit Kleinschmit
- © B. Kleinschmit
Head
Phone: +49 (0)30 / 314 - 72 84 7
Email: birgit.kleinschmit(at)tu-berlin.de
Room: EB 235a
Consultation hour: by arrangement
| Date and place of birth: 1973 (Münster, Westphalia, Germany) |
| 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 |
| 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
| Citation key | Holtgrave2020 |
|---|---|
| Author | Holtgrave, A. and Röder, N. and Ackermann, A. and Erasmi, S. and Kleinschmit, B. |
| Pages | 1-27 |
| Year | 2020 |
| ISSN | 2072-4292 |
| DOI | 10.3390/rs12182919 |
| Journal | remote sensing |
| Number | 12 |
| Abstract | Agricultural vegetation development and harvest date monitoring over large areas requires frequent remote sensing observations. In regions with persistent cloud coverage during the vegetation season this is only feasible with active systems, such as SAR, and is limited for optical data. To date, optical remote sensing vegetation indices are more frequently used to monitor agricultural vegetation status because they are easily processed, and the characteristics are widely known. This study evaluated the correlations of three Sentinel-2 optical indices with Sentinel-1 SAR indices over agricultural areas to gain knowledge about their relationship. We compared Sentinel-2 Normalized Difference Vegetation Index, Normalized Difference Water Index, and Plant Senescence Radiation Index with Sentinel-1 SAR VV and VH backscatter, VH/VV ratio, and Sentinel-1 Radar Vegetation Index. The study was conducted on 22 test sites covering approximately 35,000 ha of four different main European agricultural land use types, namely grassland, maize, spring barley, and winter wheat, in Lower Saxony, Germany, in 2018. We investigated the relationship between Sentinel-1 and Sentinel-2 indices for each land use type considering three phenophases (growing, green, enescence). The strength of the correlations of optical and SAR indices differed among land use type and phenophase. There was no generic correlation between optical and SAR indices in our study. However, when the data were split by land use types and phenophases, the correlations increased remarkably. Overall, the highest correlations were found for the Radar Vegetation Index and VH backscatter. Correlations for grassland were lower than for the other land use types. Adding auxiliary data to a multiple linear regression analysis revealed that, in addition to land use type and phenophase information, the lower quartile and median SAR values per field, and a spatial variable, improved the models. Other auxiliary data retrieved from a digital elevation model, Sentinel-1 orbit direction, soil type information, and other SAR values had minor impacts on the model performance. In conclusion, despite the different nature of the signal generation, there were distinct relationships between optical and SAR indices which were independent of environmental variables but could be stratified by land use type and phenophase. These relationships showed similar patterns across different test sites. However, a regional clustering of landscapes would significantly improve the relationships. |
| Bibtex Type of Publication | Kleinschmit |
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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
e-mail query
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
e-mail query