Teja Kattenborn
Teja Kattenborn
Department for Sensor-based Geoinformatics, University of Freiburg
Bestätigte E-Mail-Adresse bei - Startseite
Zitiert von
Zitiert von
TRY plant trait database–enhanced coverage and open access
J Kattge, G Bönisch, S Díaz, S Lavorel, IC Prentice, P Leadley, ...
Global change biology 26 (1), 119-188, 2020
Review on Convolutional Neural Networks (CNN) in vegetation remote sensing
T Kattenborn, J Leitloff, F Schiefer, S Hinz
ISPRS Journal of Photogrammetry and Remote Sensing 173, 24-49, 2021
Previsual symptoms of Xylella fastidiosa infection revealed in spectral plant-trait alterations
PJ Zarco-Tejada, C Camino, PSA Beck, R Calderon, A Hornero, ...
Nature Plants 4 (7), 432-439, 2018
Mapping forest tree species in high resolution UAV-based RGB-imagery by means of convolutional neural networks
F Schiefer, T Kattenborn, A Frick, J Frey, P Schall, B Koch, S Schmidtlein
ISPRS Journal of Photogrammetry and Remote Sensing 170, 205-215, 2020
UAV-based Photogrammetric Point Clouds – Tree Stem Mapping in open Stands in comparison to Terrestrial Laser Scanner Point Clouds
A Fritz, T Kattenborn, B Koch
ISPRS - International Archives of the Photogrammetry, Remote Sensing and …, 2013
UAV data as alternative to field sampling to map woody invasive species based on combined Sentinel-1 and Sentinel-2 data
T Kattenborn, J Lopatin, M Förster, AC Braun, FE Fassnacht
Remote sensing of environment 227, 61-73, 2019
Convolutional Neural Networks enable efficient, accurate and fine-grained segmentation of plant species and communities from high-resolution UAV imagery
T Kattenborn, J Eichel, FE Fassnacht
Scientific reports 9 (1), 17656, 2019
Chlorophyll content estimation in an open-canopy conifer forest with Sentinel-2A and hyperspectral imagery in the context of forest decline
PJ Zarco-Tejada, A Hornero, PSA Beck, T Kattenborn, P Kempeneers, ...
Remote sensing of environment 223, 320-335, 2019
Building a hybrid land cover map with crowdsourcing and geographically weighted regression
L See, D Schepaschenko, M Lesiv, I McCallum, S Fritz, A Comber, ...
ISPRS Journal of Photogrammetry and Remote Sensing 103, 48-56, 2015
Convolutional Neural Networks accurately predict cover fractions of plant species and communities in Unmanned Aerial Vehicle imagery
T Kattenborn, J Eichel, S Wiser, L Burrows, Fassnacht, F Ewald, ...
Remote Sensing in Ecology and Conservation, 15, 2020
Automatic Single Palm Tree Detection in Plantation using UAV-based Photogrammetric Point Clouds
T Kattenborn, M Sperlich, K Bataua, B Koch
Remote Sensing and Spatial Information Sciences 3 (XL-3), 139-146, 2014
Differentiating plant functional types using reflectance: which traits make the difference?
T Kattenborn, FF Ewald, S Schmidtlein
Remote Sensing in Ecology and Conservation, 2018
Mapping plant species in mixed grassland communities using close range imaging spectroscopy
J Lopatin, FE Fassnacht, T Kattenborn, S Schmidtlein
Remote Sensing of Environment 201, 12-23, 2017
How canopy shadow affects invasive plant species classification in high spatial resolution remote sensing
J Lopatin, K Dolos, T Kattenborn, FE Fassnacht
Remote Sensing in Ecology and Conservation 5 (4), 302-317, 2019
Mapping forest biomass from space – Fusion of hyperspectral EO1-hyperion data and Tandem-X and WorldView-2 canopy height models
T Kattenborn, J Maack, F Faßnacht, F Enßle, J Ermert, B Koch
International Journal of Applied Earth Observation and Geoinformation 35 …, 2014
Linking plant strategies and plant traits derived by radiative transfer modelling
T Kattenborn, FE Fassnacht, S Pierce, J Lopatin, JP Grime, S Schmidtlein
Journal of Vegetation Science 28 (4), 717-727, 2017
Detection of Xylella fastidiosa infection symptoms with airborne multispectral and thermal imagery: Assessing bandset reduction performance from hyperspectral analysis
T Poblete, C Camino, PSA Beck, A Hornero, T Kattenborn, M Saponari, ...
ISPRS Journal of Photogrammetry and Remote Sensing 162, 27-40, 2020
Segmentation of forest to tree objects
B Koch, T Kattenborn, C Straub, J Vauhkonen
Forestry applications of airborne laser scanning: Concepts and case studies …, 2013
Explaining Sentinel 2-based dNBR and RdNBR variability with reference data from the bird’s eye (UAS) perspective
FE Fassnacht, E Schmidt-Riese, T Kattenborn, J Hernández
International Journal of Applied Earth Observation and Geoinformation 95, 102262, 2021
Advantages of retrieving pigment content [μg/cm2] versus concentration [%] from canopy reflectance
T Kattenborn, F Schiefer, P Zarco-Tejada, S Schmidtlein
Remote Sensing of Environment 230, 111195, 2019
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