Faculty of Mathematics and Natural Sciences - Geographisches Institut

M.Sc. Thilo Wellmann

Fachliche Schwerpunkte | Projekt(e) | Vorträge
Foto
Name
M.Sc. Thilo Wellmann
Email
thilo.wellmann (at) geo.hu-berlin.de
Homepage
https://www.geographie.hu-berlin.de/Members/wellmann_thilo

Thilo Wellmann is PhD student at the urban ecology lab of Humboldt-Universität zu Berlin. He explores integrative means for enabling ecologically viable and socially just urban governance. A key research area is thereby the integration of remote sensing based monitoring techniques for creating accessible evidence bases around planning and development processes.

With his work, he contributes to the projects Faktencheck Artenvielfalt of the BMBF-research initiative for the safeguarding of biodiversity in Germany;

and to the Biodiversa BiNatUr (Bringing Nature Back) project researching biodiversity-friendly nature-based solutions (NbS) in cities.

A selection of key publications:

 

Wellmann, T., E. Andersson, S. Knapp, S. Scheuer, A. Lausch, J. Palliwoda, and D. Haase. 2022. Reinforcing nature-based solutions through tools providing social-ecological-technological integration. Ambio. doi:10.1007/s13280-022-01801-4 https://link.springer.com/article/10.1007/s13280-022-01801-4

 

Scheuer, S., J. Jache, M. Kičić, T. Wellmann, M. Wolff, and D. Haase. 2022. A trait-based typification of urban forests as nature-based solutions. Urban Forestry & Urban Greening 78: 127780. doi:10.1016/j.ufug.2022.127780 https://www.sciencedirect.com/science/article/pii/S1618866722003235

 

Wellmann, T., Lausch, A., Andersson, E., Knapp, S., Cortinovis, C., Jache, J., Scheuer, S., Kremer, P., Mascarenhas, A., Kraemer, R., Haase, A., Schug, F., & Haase, D. (2020). Remote sensing in urban planning: Contributions towards ecologically sound policies? Landscape and Urban Planning, 204(June), 103921.

       https://doi.org/10.1016/j.landurbplan.2020.103921

 

Wellmann, T., Schug, F., Haase, D., Pflugmacher, D., & van der Linden, S. (2020). Green growth? On the relation between population density, land use and vegetation cover fractions in a city using a 30-years Landsat time series. Landscape and Urban Planning, 202(October), 103857.

       https://doi.org/10.1016/j.landurbplan.2020.103857

 

Andersson, E., Haase, D., Scheuer, S., & Wellmann, T. (2020). Neighbourhood character affects the spatial extent and magnitude of the functional footprint of urban green infrastructure. Landscape Ecology.

       https://doi.org/10.1007/s10980-020-01039-z

 

Wellmann, T., Lausch, A., Scheuer, S., & Haase, D. (2020). Earth observation based indication for avian species distribution models using the spectral trait concept and machine learning in an urban setting. Ecological Indicators, 111(April 2020), 106029.

       https://doi.org/10.1016/j.ecolind.2019.106029

Haase, D., Jänicke, C., & Wellmann, T. (2019). Front and back yard green analysis with subpixel vegetation fractions from earth observation data in a city. Landscape and Urban Planning, 182(March 2018), 44–54.

       https://doi.org/10.1016/j.landurbplan.2018.10.010

Wellmann, T., Haase, D., Knapp, S., Salbach, C., Selsam, P., & Lausch, A. (2018). Urban land use intensity assessment: The potential of spatio-temporal spectral traits with remote sensing. Ecological Indicators, 85, 190–203.

       https://doi.org/10.1016/j.ecolind.2017.10.029

 

For more information on me you can visit: https://thilowellmann.de/

Or regarding our current project you will find more information here: http://remotesensingforcities.org