List of works - Teja Kattenborn

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

scientific article published on 31 May 2019

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

scientific article published on 24 May 2019

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

conference paper presented at EGU23

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

scientific article published on 6 October 2022

Assessment of camera focal length influence on canopy reconstruction quality

Automated mapping of <i>Portulacaria afra</i> canopies for restoration monitoring with convolutional neural networks and heterogeneous unmanned aerial vehicle imagery

scientific article published in 2022

Biodiversity and Climate Extremes: Known Interactions and Research Gaps

scientific article published in June 2024

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

article by Linda See et al published May 2015 in ISPRS Journal of Photogrammetry and Remote Sensing

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

scientific article published on 01 March 2019

Citizen science plant observations encode global trait patterns

scientific article published in 2022

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

scientific article published on 05 February 2020

Convolutional Neural Networks enable efficient, accurate and fine-grained segmentation of plant species and communities from high-resolution UAV imagery

scientific article published on 27 November 2019

Deep learning and citizen science enable automated plant trait predictions from photographs

scientific article published on 12 August 2021

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

scientific article published on 09 July 2018

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

article

Evaluating different methods for retrieving intraspecific leaf trait variation from hyperspectral leaf reflectance

scientific article published on 27 August 2021

Explaining Sentinel 2-based dNBR and RdNBR variability with reference data from the bird’s eye (UAS) perspective

scientific article published on 10 November 2020

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

conference paper presented at EGU23

How canopy shadow affects invasive plant species classification in high spatial resolution remote sensing

scientific article published on 13 February 2019

Linking plant strategies and plant traits derived by radiative transfer modelling

article

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

scientific article published on 05 September 2017

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

scientific article published on 26 August 2023

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

scientific article published on 25 June 2018

Radiative transfer modelling reveals why canopy reflectance follows function

scientific article published on 25 April 2019

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

scientific article published in August 2022

TRY plant trait database - enhanced coverage and open access

scientific article published on 31 December 2019

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

scientific article published on 23 October 2020

Transfer learning from citizen science photographs enables plant species identification in UAV imagery

scientific article published in 2022

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

conference paper presented at EGU23

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

scientific article published on 12 April 2019

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

scientific article published in 2023

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

scientific article published in 2019

List of works by Teja Kattenborn

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

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

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

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

Assessment of camera focal length influence on canopy reconstruction quality

Automated mapping of <i>Portulacaria afra</i> canopies for restoration monitoring with convolutional neural networks and heterogeneous unmanned aerial vehicle imagery

Biodiversity and Climate Extremes: Known Interactions and Research Gaps

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

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

Citizen science plant observations encode global trait patterns

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

Convolutional Neural Networks enable efficient, accurate and fine-grained segmentation of plant species and communities from high-resolution UAV imagery

Deep learning and citizen science enable automated plant trait predictions from photographs

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

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

Evaluating different methods for retrieving intraspecific leaf trait variation from hyperspectral leaf reflectance

Explaining Sentinel 2-based dNBR and RdNBR variability with reference data from the bird’s eye (UAS) perspective

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

How canopy shadow affects invasive plant species classification in high spatial resolution remote sensing

Linking plant strategies and plant traits derived by radiative transfer modelling

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

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

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

Radiative transfer modelling reveals why canopy reflectance follows function

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

TRY plant trait database - enhanced coverage and open access

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

Transfer learning from citizen science photographs enables plant species identification in UAV imagery

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

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

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

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