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Dipl.-Ing. Tobias Gränzig (geb. Schmidt)
Scientific Head of Laboratory
Phone: +49 (0)30 / 314 - 29 19 7
Email: tobias.graenzig(at)tu-berlin.de
Room: EB 205
Date and place of birth: 1983 (Berlin, Germany) |
since 2017 | Scientific Head of Laboratory |
2011-2017 | Research Assistant Technische Universität Berlin, Department of Landscape Architecture and Environmental Planning, Geoinformation in Environmental Planning. Projects:
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2010-2011 | Tutor Technische Universität Berlin, Department of Landscape Architecture and Environmental Planning, Geoinformation in Environmental Planning. |
2007-2010 | Internship and freelance collaborator CS Planungs- und Ingenieurgesellschaft mbH (Planning and Engineering Corporation), Berlin |
2005-2011 | Studies of Landscape Planning Technische Universität Berlin, Germany |
Research Topics
Time-series analysis of high-resolution satellite images to support grassland monitoring and to detect invasive plant species.
Publications
Citation key | Schmidt20170 |
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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 |
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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
Projects
- SaMovar - Satellite-based Monitoring of invasive species in central-Chile
- InBoMo - Indikatorenbasiertes Bodenfeuchtemonitoring an Flussauen
- Habit-Change - Adaptive Management of Climate-induced Changes of Habitat Diversity in Protected Areas
- CARE-X - Change Detection Analysis mit RapidEye- und TerraSAR-X-Daten