Hannes Feilhauer

Professor

Leipzig University

Germany

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About

Hannes Feilhauer is a Professor at Leipzig University in Germany. His research focuses on ecophylogenetics, biodiversity assessments, and the use of remote sensing data to study plant species composition and dynamics. Recent articles authored by Professor Feilhauer explore topics such as the relationship between spectral data and grassland biodiversity, as well as the impacts of climate extremes on biodiversity patterns.

Articles (15)

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2025

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2025

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2025

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2025

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2024

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2024

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2024

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2024

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2023

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2022

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2022

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2022

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2022

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2022

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2022

Collaborators (17)

Markus Reichstein

Max Planck Institute for Biogeochemistry

GERMANY

Hannes Feilhauer

Research Interests

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Articles (15)

Plant trait retrieval from hyperspectral data: Collective efforts in scientific data curation outperform simulated data derived from the PROSAIL model

Predicting woody species assemblages using ecophylogenetics and Earth observation data

Exploring Sentinel‐2‐Based Spectral Variability for Enhancing Grassland Diversity Assessments Across Germany

Patterns of plant species composition of a temperate floodplain meadow in response to fine-scale topography

Biodiversity and Climate Extremes: Known Interactions and Research Gaps

Macrophenological dynamics from citizen science plant occurrence data

Is spectral pixel-to-pixel variation a reliable indicator of grassland biodiversity? A systematic assessment of the spectral variation hypothesis using spatial simulation experiments

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

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

Remote sensing for vegetation science: A virtual special issue on its power and challenges

Estimating heavy metal concentrations in Technosols with reflectance spectroscopy

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

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

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

Sampling Robustness in Gradient Analysis of Urban Material Mixtures

Collaborators (17)

Markus Reichstein

Sophie Wolf

Matthias Tesche

Karin Mora

Jana Mullerova

Miguel Mahecha

Ana Bastos

Phuong D. Dao

Carsten F. Dormann

Sabine Chabrillat

Philip Townsend

Michael Ewald

Ingolf Kühn

Teja Kattenborn

Sebastian Schmidtlein

Djamil Al-Halbouni

Chaonan Ji

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