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  1. Temporal dynamics in vertical leaf angles can confound vegetation indices widely used in Earth observations

    Article • Communications Earth & Environment, October 2024, Springer Science + Business Media

    Dr Teja Kattenborn

  2. Forest dieback in drinking water protection areas – a hidden threat to water quality

    Article • August 2024, Cold Spring Harbor Laboratory Press

    Dr Teja Kattenborn

  3. Macrophenological dynamics from citizen science plant occurrence data

    Article • Methods in Ecology and Evolution, July 2024, Wiley

    Dr Teja Kattenborn

  4. From simple labels to semantic image segmentation: leveraging citizen science plant photographs for tree species mapping in drone imagery

    Article • Biogeosciences, June 2024, Copernicus GmbH

    Dr Teja Kattenborn

  5. DeepFeatures: Remote sensing beyond spectral indices

    Article • March 2024, Copernicus GmbH

    Dr Teja Kattenborn

  6. High-resolution mapping of tree mortality in European forests

    Article • March 2024, Copernicus GmbH

    Dr Teja Kattenborn

  7. Plant macrophenological dynamics - from individuals to plant group behaviour using citizen science data

    Article • March 2024, Copernicus GmbH

    Dr Teja Kattenborn

  8. Global-scale plant trait-environment relationships based on sPlotOpen and TRY data

    Article • March 2024, Copernicus GmbH

    Dr Teja Kattenborn

  9. deadtrees.earth - an open, dynamic database for accessing, contributing, analyzing, and visualizing remote sensing-based tree mortality data.

    Article • March 2024, Copernicus GmbH

    Dr Teja Kattenborn

  10. Combining citizen science and Earth observation data to produce global maps of 31 plant traits

    Article • March 2024, Copernicus GmbH

    Dr Teja Kattenborn

  11. How trees sway and what it tells us about their overall vitality

    Article • March 2024, Copernicus GmbH

    Dr Teja Kattenborn

  12. Investigating Deep Learning Techniques to Estimate Fractional Vegetation Cover in the Australian Semi-arid Ecosystems combining Drone-based RGB imagery, multispectral Imagery and LiDAR data.

    Article • March 2024, Copernicus GmbH

    Dr Teja Kattenborn

  13. Leveraging Crowd-sourced Biodiversity Data for an Enhanced Plant Functional Trait Mapping

    Article • March 2024, Copernicus GmbH

    Dr Teja Kattenborn

  14. TRY - Plant Trait Database

    Article • March 2024, Copernicus GmbH

    Dr Teja Kattenborn

  15. Crowd-sourced trait data can be used to delimit global biomes

    Article • February 2024, Copernicus GmbH

    Dr Teja Kattenborn

  16. Supplementary material to "Crowd-sourced trait data can be used to delimit global biomes"

    Article • February 2024, Copernicus GmbH

    Dr Teja Kattenborn

  17. Intercomparison of global foliar trait maps reveals fundamental differences and limitations of upscaling approaches

    Article • December 2023, California Digital Library (CDL)

    Dr Teja Kattenborn

  18. From simple labels to semantic image segmentation: Leveraging citizen science plant photographs for tree species mapping in drone imagery

    Article • December 2023, Copernicus GmbH

    Dr Teja Kattenborn

  19. Biodiversity and climate extremes: known interactions and research gaps

    Article • September 2023, Authorea, Inc.

    Claudia Guimaraes-Steinicke, Dr Teja Kattenborn

  20. Pattern to process, research to practice: remote sensing of plant invasions

    Article • Biological Invasions, August 2023, Springer Science + Business Media

    Dr Teja Kattenborn

  21. Data Cubes for Earth System Research: Challenges Ahead

    Article • July 2023, California Digital Library (CDL)

    Dr Teja Kattenborn

  22. Monitoring solifluction movement in space and time: A semi-automated high-resolution approach

    Article • Geomorphology, July 2023, Elsevier

    Dr Teja Kattenborn

  23. UAV-based reference data for the prediction of fractional cover of standing deadwood from Sentinel time series

    Article • ISPRS Open Journal of Photogrammetry and Remote Sensing, April 2023, Elsevier

    Dr Teja Kattenborn

  24. AngleCam - Tracking leaf angle distributions through time with image series and deep learning

    Article • February 2023, Copernicus GmbH

    Dr Teja Kattenborn

  25. From spectra to functional plant traits: Transferable multi-trait models from heterogeneous and sparse data

    Article • February 2023, Copernicus GmbH

    Dr Teja Kattenborn

  26. Transfer learning from citizen science photos enables plantspecies identification in UAV imagery

    Article • February 2023, Copernicus GmbH

    Dr Teja Kattenborn

  27. Citizen science observations capture global patterns of plant traits

    Article • February 2023, Copernicus GmbH

    Dr Teja Kattenborn

  28. Citizen science plant observations encode global trait patterns

    Article • Nature Ecology & Evolution, October 2022, Springer Science + Business Media

    Dr Teja Kattenborn

  29. AngleCam : Predicting the temporal variation of leaf angle distributions from image series with deep learning

    Article • Methods in Ecology and Evolution, October 2022, Wiley

    Dr Teja Kattenborn, Claudia Guimaraes-Steinicke

  30. Spatially autocorrelated training and validation samples inflate performance assessment of convolutional neural networks

    Article • ISPRS Open Journal of Photogrammetry and Remote Sensing, June 2022, Elsevier

    Dr Teja Kattenborn

  31. Review on Convolutional Neural Networks (CNN) in vegetation remote sensing

    Article • ISPRS Journal of Photogrammetry and Remote Sensing, March 2021, Elsevier

    Dr Teja Kattenborn

  32. The retrieval of plant functional traits from canopy spectra through RTM-inversions and statistical models are both critically affected by plant phenology

    Article • Ecological Indicators, February 2021, Elsevier

    Dr Teja Kattenborn

  33. Mapping forest tree species in high resolution UAV-based RGB-imagery by means of convolutional neural networks

    Article • ISPRS Journal of Photogrammetry and Remote Sensing, December 2020, Elsevier

    Dr Teja Kattenborn

  34. Convolutional Neural Networks accurately predict cover fractions of plant species and communities in Unmanned Aerial Vehicle imagery

    Article • Remote Sensing in Ecology and Conservation, February 2020, Wiley

    Dr Teja Kattenborn

  35. Unmanned aerial vehicle-based mapping of turf-banked solifluction lobe movement and its relation to material, geomorphometric, thermal and vegetation properties

    Article • Permafrost and Periglacial Processes, January 2020, Wiley

    Dr Teja Kattenborn

  36. Deep Learning enables to identify plant species in aerial imagery

    Article • Scientific Reports, November 2019, Springer Science + Business Media

    Dr Teja Kattenborn

  37. Advantages of retrieving pigment content [μg/cm2] versus concentration [%] from canopy reflectance

    Article • Remote Sensing of Environment, September 2019, Elsevier

    Dr Teja Kattenborn

  38. Using aboveground vegetation attributes as proxies for mapping peatland belowground carbon stocks

    Article • Remote Sensing of Environment, September 2019, Elsevier

    Dr Teja Kattenborn

  39. UAV data as alternative to field sampling to map woody invasive species based on combined Sentinel-1 and Sentinel-2 data

    Article • Remote Sensing of Environment, June 2019, Elsevier

    Dr Teja Kattenborn

  40. A Landsat-based vegetation trend product of the Tibetan Plateau for the time-period 1990–2018

    Article • Scientific Data, May 2019, Springer Science + Business Media

    Dr Teja Kattenborn

  41. The functioning of plants determines how they reflect light

    Article • Scientific Reports, April 2019, Springer Science + Business Media

    Dr Teja Kattenborn

  42. Chlorophyll content estimation in an open-canopy conifer forest with Sentinel-2A and hyperspectral imagery in the context of forest decline

    Article • Remote Sensing of Environment, March 2019, Elsevier

    Dr Teja Kattenborn

  43. Proximal VIS-NIR spectrometry to retrieve substance concentrations in surface waters using partial least squares modelling

    Article • Water Science & Technology Water Supply, October 2018, IWA Publishing

    Dr Teja Kattenborn

  44. PILOT STUDY ON THE RETRIEVAL OF DBH AND DIAMETER DISTRIBUTION OF DECIDUOUS FOREST STANDS USING CAST SHADOWS IN UAV-BASED ORTHOMOSAICS

    Article • ISPRS Annals of the Photogrammetry Remote Sensing and Spatial Information Sciences, September 2018, Copernicus GmbH

    Dr Teja Kattenborn

  45. Differentiating plant functional types using reflectance: which traits make the difference?

    Article • Remote Sensing in Ecology and Conservation, July 2018, Wiley

    Dr Teja Kattenborn

  46. Modis-Based Grassland Trends Within and Around the Kekexili Core Protection Zone of the Sanjiangyuan Nature Reserve

    Article • July 2018, Institute of Electrical & Electronics Engineers (IEEE)

    Dr Teja Kattenborn

  47. Previsual symptoms of Xylella fastidiosa infection revealed in spectral plant-trait alterations

    Article • Nature Plants, June 2018, Springer Science + Business Media

    Dr Teja Kattenborn

  48. Mapping plant species in mixed grassland communities using close range imaging spectroscopy

    Article • Remote Sensing of Environment, November 2017, Elsevier

    Dr Teja Kattenborn

  49. Detecting the spread of invasive species in central Chile with a Sentinel-2 time-series

    Article • June 2017, Institute of Electrical & Electronics Engineers (IEEE)

    Dr Teja Kattenborn

  50. Linking plant strategies and plant traits derived by radiative transfer modelling

    Article • Journal of Vegetation Science, April 2017, Wiley

    Dr Simon Pierce, Dr Teja Kattenborn

  51. Estimating stand density, biomass and tree species from very high resolution stereo-imagery – towards an all-in-one sensor for forestry applications?

    Article • Forestry An International Journal of Forest Research, March 2017, Oxford University Press (OUP)

    Dr Teja Kattenborn

  52. Linking plant strategies (CSR) and remotely sensed plant traits

    Article • August 2016, Institute of Electrical & Electronics Engineers (IEEE)

    Dr Teja Kattenborn

  53. Corrigendum to “Mapping forest biomass from space – Fusion of hyperspectralEO1-hyperion data and Tandem-X and WorldView-2 canopy heightmodels” [Int. J. Appl. Earth Obs. Geoinf. Issue no. 35 (2015) 359-367]

    Article • International Journal of Applied Earth Observation and Geoinformation, September 2015, Elsevier

    Dr Teja Kattenborn

  54. Building a hybrid land cover map with crowdsourcing and geographically weighted regression

    Article • ISPRS Journal of Photogrammetry and Remote Sensing, May 2015, Elsevier

    Dr Teja Kattenborn

  55. Mapping forest biomass from space – Fusion of hyperspectral EO1-hyperion data and Tandem-X and WorldView-2 canopy height models

    Article • International Journal of Applied Earth Observation and Geoinformation, March 2015, Elsevier

    Dr Teja Kattenborn

  56. Modeling forest biomass using Very-High-Resolution data—Combining textural, spectral and photogrammetric predictors derived from spaceborne stereo images

    Article • European Journal of Remote Sensing, January 2015, Taylor & Francis

    Dr Teja Kattenborn

  57. Automatic Single Tree Detection in Plantations using UAV-based Photogrammetric Point clouds

    Article • August 2014, Copernicus GmbH

    Dr Teja Kattenborn

  58. Segmentation of Forest to Tree Objects

    Article • March 2013, Springer Science + Business Media

    Dr Teja Kattenborn