Inhalt des Dokuments
Dipl.-Ing. Tobias Gränzig (geb. Schmidt)
Wissenschaftlicher Laborleiter
Tel.: +49 (0)30 / 314 - 29 19 7
Email: tobias.graenzig(at)tu-berlin.de
Raum: EB 205
seit 2017 | Wissenschaftlicher Laborleiter am Fachgebiet Geoinformation in der Umweltplanung der TU Berlin | |
2011-2017 | Wissenschaftlicher Mitarbeiter am Fachgebiet Geoinformation in der Umweltplanung der TU Berlin. Projekte:
| |
2010-2011 | Studentische Hilfskraft am Fachgebiet Geoinformation in der Umweltplanung der TU Berlin | |
2008-2010 | Freier Mitarbeiter bei der CS-Planungs- und Ingenieurgesellschaft mbH Berlin | |
2005-2011 | Studium der Landschaftsplanung an der TU Berlin | |
1983 | in Berlin geboren |
Forschungsschwerpunkte
Zeitreihenanalyse von räumlich hoch aufgelösten optischen Satellitendaten zur Untersützung von Grünlandmonitoring und zur Erkennung invasiver Pflanzenarten.
Publikationen
Zitatschlüssel | Schmidt20170 |
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Autor | Schmidt, J. and Fassnacht, F. E. and Neff, C. and Lausch, A. and Kleinschmit, B. and Förster, M. and Schmidtlein, S. |
Seiten | 61-71 |
Jahr | 2017 |
DOI | http://dx.doi.org/10.1016/j.jag.2017.04.005 |
Journal | International Journal of Applied Earth Observation and Geoinformation |
Jahrgang | 60 |
Zusammenfassung | 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. |
Typ der Publikation | Kleinschmit |
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Fachgebiet Geoinformation in der Umweltplanung
Sekretariat EB5
Raum 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-Anfrage
Sekretariat EB5
Raum 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-Anfrage
Projekte
- SaMovar - Satellitengestütztes Monitoring invasiver Arten in Zentral-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