Forest canopy mortality during the 2018-2020 summer drought years in Central Europe: The application of a deep learning approach on aerial images across Luxembourg

Global field observations of tree die-off reveal hotter-drought fingerprint for Earth’s forests

(2022) William M. Hammond et al.   Nature Communications

The 2018–2020 Multi‐Year Drought Sets a New Benchmark in Europe

(2022) Oldrich Rakovec et al.   Earths Future

Wildland Fire Tree Mortality Mapping from Hyperspatial Imagery Using Machine Learning

(2021) Dale A. Hamilton et al.   Remote Sensing

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

(2021) Teja Kattenborn et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Tree species classification from airborne hyperspectral and LiDAR data using 3D convolutional neural networks

(2021) Janne Mäyrä et al.   REMOTE SENSING OF ENVIRONMENT

Tree mortality of European beech and Norway spruce induced by 2018-2019 hot droughts in central Germany

(2021) Nora Obladen et al.   AGRICULTURAL AND FOREST METEOROLOGY

Predicting into unknown space? Estimating the area of applicability of spatial prediction models

(2021) Hanna Meyer et al.   Methods in Ecology and Evolution

A first assessment of the impact of the extreme 2018 summer drought on Central European forests

(2020) Bernhard Schuldt et al.   BASIC AND APPLIED ECOLOGY

Deep learning in environmental remote sensing: Achievements and challenges

(2020) Qiangqiang Yuan et al.   REMOTE SENSING OF ENVIRONMENT

Object Detection and Image Segmentation with Deep Learning on Earth Observation Data: A Review-Part I: Evolution and Recent Trends

(2020) Thorsten Hoeser et al.   Remote Sensing

Deep learning-based dead pine tree detection from unmanned aerial vehicle images

(2020) Huan Tao et al.   INTERNATIONAL JOURNAL OF REMOTE SENSING

Increased future occurrences of the exceptional 2018–2019 Central European drought under global warming

(2020) Vittal Hari et al.   Scientific Reports

An unexpectedly large count of trees in the West African Sahara and Sahel

(2020) Martin Brandt et al.   NATURE

Spatial validation reveals poor predictive performance of large-scale ecological mapping models

(2020) Pierre Ploton et al.   Nature Communications

Mapping the forest disturbance regimes of Europe

(2020) Cornelius Senf et al.   Nature Sustainability

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

(2020) Felix Schiefer et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Boundary loss for highly unbalanced segmentation

(2020) Hoel Kervadec et al.   MEDICAL IMAGE ANALYSIS

Chimera: A Multi-Task Recurrent Convolutional Neural Network for Forest Classification and Structural Estimation

(2019) Tony Chang et al.   Remote Sensing

Detection of Fir Trees (Abies sibirica) Damaged by the Bark Beetle in Unmanned Aerial Vehicle Images with Deep Learning

(2019) Anastasiia Safonova et al.   Remote Sensing

Role of forest regrowth in global carbon sink dynamics

(2019) Thomas A. M. Pugh et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Deep learning and process understanding for data-driven Earth system science

(2019) Markus Reichstein et al.   NATURE

Developing forest monitoring capacity – Progress achieved and gaps remaining after ten years

(2019) Till Neeff et al.   FOREST POLICY AND ECONOMICS

Uncovering Ecological Patterns with Convolutional Neural Networks

(2019) Philip G. Brodrick et al.   TRENDS IN ECOLOGY & EVOLUTION

Deep learning in remote sensing applications: A meta-analysis and review

(2019) Lei Ma et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

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

(2019) Teja Kattenborn et al.   REMOTE SENSING OF ENVIRONMENT

Drought-Mediated Changes in Tree Physiological Processes Weaken Tree Defenses to Bark Beetle Attack

(2019) Thomas Kolb et al.   JOURNAL OF CHEMICAL ECOLOGY

Forest Damage Assessment Using Deep Learning on High Resolution Remote Sensing Data

(2019) Zayd Mahmoud Hamdi et al.   Remote Sensing

Mapping dead forest cover using a deep convolutional neural network and digital aerial photography

(2019) Jean-Daniel Sylvain et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

A Convolutional Neural Network Classifier Identifies Tree Species in Mixed-Conifer Forest from Hyperspectral Imagery

(2019) Geoffrey A. Fricker et al.   Remote Sensing

Monitoring global tree mortality patterns and trends. Report from the VW symposium ‘Crossing scales and disciplines to identify global trends of tree mortality as indicators of forest health’

(2018) Henrik Hartmann et al.   NEW PHYTOLOGIST

Deep Learning for Computer Vision: A Brief Review

(2018) Athanasios Voulodimos et al.   Computational Intelligence and Neuroscience

Species classification using Unmanned Aerial Vehicle (UAV)-acquired high spatial resolution imagery in a heterogeneous grassland

(2017) Bing Lu et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review

(2017) Waseem Rawat et al.   NEURAL COMPUTATION

Forest disturbances under climate change

(2017) Rupert Seidl et al.   Nature Climate Change

A multi-species synthesis of physiological mechanisms in drought-induced tree mortality

(2017) Henry D. Adams et al.   Nature Ecology & Evolution

Characterizing spectral–temporal patterns of defoliator and bark beetle disturbances using Landsat time series

(2015) Cornelius Senf et al.   REMOTE SENSING OF ENVIRONMENT

Assessing the potential of hyperspectral imagery to map bark beetle-induced tree mortality

(2013) Fabian Ewald Fassnacht et al.   REMOTE SENSING OF ENVIRONMENT

High-Resolution Global Maps of 21st-Century Forest Cover Change

(2013) M. C. Hansen et al.   SCIENCE

A Large and Persistent Carbon Sink in the World's Forests

(2011) Y. Pan et al.   SCIENCE

Climate change impacts, adaptive capacity, and vulnerability of European forest ecosystems

(2009) Marcus Lindner et al.   FOREST ECOLOGY AND MANAGEMENT