Thilo Wellmann
Thilo Wellmann
Humboldt Universität zu Berlin
Bestätigte E-Mail-Adresse bei hu-berlin.de - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Urban land use intensity assessment: The potential of spatio-temporal spectral traits with remote sensing
T Wellmann, D Haase, S Knapp, C Salbach, P Selsam, A Lausch
Ecological Indicators 85, 190-203, 2018
452018
Remote sensing in urban planning: Contributions towards ecologically sound policies?
T Wellmann, A Lausch, E Andersson, S Knapp, C Cortinovis, J Jache, ...
Landscape and Urban Planning 204, 103921, 2020
392020
Front and back yard green analysis with subpixel vegetation fractions from earth observation data in a city
D Haase, C Jänicke, T Wellmann
Landscape and urban planning 182, 44-54, 2019
362019
Green growth? On the relation between population density, land use and vegetation cover fractions in a city using a 30-years Landsat time series
T Wellmann, F Schug, D Haase, D Pflugmacher, S van der Linden
Landscape and Urban Planning 202, 103857, 2020
252020
Neighbourhood character affects the spatial extent and magnitude of the functional footprint of urban green infrastructure
E Andersson, D Haase, S Scheuer, T Wellmann
Landscape Ecology, 2020
122020
Earth observation based indication for avian species distribution models using the spectral trait concept and machine learning in an urban setting
T Wellmann, A Lausch, S Scheuer, D Haase
Ecological Indicators 111, 106029, 2020
82020
Linking the Remote Sensing of Geodiversity and Traits Relevant to Biodiversity—Part II: Geomorphology, Terrain and Surfaces
A Lausch, ME Schaepman, AK Skidmore, SC Truckenbrodt, JM Hacker, ...
Remote sensing 12 (22), 3690, 2020
42020
What are the traits of a social-ecological system: towards a framework in support of urban sustainability
E Andersson, D Haase, P Anderson, C Cortinovis, J Goodness, D Kendal, ...
npj Urban Sustainability 1 (1), 1-8, 2021
22021
A glimpse into the future of exposure and vulnerabilities in cities? Modelling of residential location choice of urban population with random forest
S Scheuer, D Haase, A Haase, M Wolff, T Wellmann
Natural Hazards and Earth System Sciences 21 (1), 203-217, 2021
12021
Urban Green Fabric Analysis Promoting Sustainable Planning in Guatemala City
F Castillo-Cabrera, T Wellmann, D Haase
Land 10 (1), 18, 2021
12021
EcoSystem Integrity–Sensor/EO-Service (ESIS) for monitoring bio-geodiversity and human health by traits, remote sensing and data science approaches
A Lausch, J Bumberger, P Dietrich, T Wellmann, N Kabisch, D Haase, ...
AGU Fall Meeting 2021, 2021
2021
Integrating Quantity and Quality to Assess Urban Green Space Improvement in the Compact City
S Chen, D Haase, B Xue, T Wellmann, S Qureshi
Land 10 (12), 1367, 2021
2021
Creating accessible evidence bases: Opportunities through the integration of interactive tools into literature review synthesis
S Scheuer, J Jache, L Sumfleth, T Wellmann, D Haase
MethodsX 8, 101558, 2021
2021
Umweltgerechtigkeit aus bürgerschaftlicher Perspektive: Handlungsempfehlung am Beispiel Berlin-Schöneberg
T Lessel, T Wellmann
Stadt+Grün, 38 - 42, 2021
2021
A glimpse into the future of exposure and vulnerabilities in cities? Modelling of residential location choice of urban population with random forest
S Scheuer, D Haase, A Haase, M Wolff, T Wellmann
Natural Hazards and Earth System Sciences Discussions 2020, 1-27, 2020
2020
Modelling the distribution of 44 urban bird species using Earth observation based plant trait indicators and machine learning.
T Wellmann, S Scheuer, A Lausch, D Haase
Geophysical Research Abstracts 21, 2019
2019
Assessing trends in future exposure and vulnerability of population to natural hazards based on tacit knowledge and data mining techniques.
S Scheuer, T Wellmann, D Haase, M Wolff, A Haase
Geophysical Research Abstracts 21, 2019
2019
Modelling urban bird breeding ranges with remotely sensed heterogeneity in plant traits using a random forest
T Wellmann, A Lausch, S Scheuerl, D Haase
ICEI 2018: 10th International Conference on Ecological Informatics …, 2018
2018
Modelling the distribution of 44 urban bird species using Earth observation based plant traits and machine learning
T Wellmann, S Scheuer, A Lausch, D Haase
Modelling urban bird breeding ranges
T Wellmann
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