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Tree canopy height is one of the most important indicators of forest biomass, productivity, and species diversity, but it is challenging to measure accurately from the ground and from space. Here, we used a U-Net model adapted for…

Computer Vision and Pattern Recognition · Computer Science 2023-06-06 Fabien H Wagner , Sophia Roberts , Alison L Ritz , Griffin Carter , Ricardo Dalagnol , Samuel Favrichon , Mayumi CM Hirye , Martin Brandt , Philipe Ciais , Sassan Saatchi

The worldwide variation in vegetation height is fundamental to the global carbon cycle and central to the functioning of ecosystems and their biodiversity. Geospatially explicit and, ideally, highly resolved information is required to…

Computer Vision and Pattern Recognition · Computer Science 2022-04-19 Nico Lang , Walter Jetz , Konrad Schindler , Jan Dirk Wegner

Vegetation structure mapping is critical for understanding the global carbon cycle and monitoring nature-based approaches to climate adaptation and mitigation. Repeated measurements of these data allow for the observation of deforestation…

With the rise in global greenhouse gas emissions, accurate large-scale tree canopy height maps are essential for understanding forest structure, estimating above-ground biomass, and monitoring ecological disruptions. To this end, we present…

Machine Learning · Computer Science 2026-03-13 Jan Pauls , Max Zimmer , Berkant Turan , Sassan Saatchi , Philippe Ciais , Sebastian Pokutta , Fabian Gieseke

In intensively managed forests in Europe, where forests are divided into stands of small size and may show heterogeneity within stands, a high spatial resolution (10 - 20 meters) is arguably needed to capture the differences in canopy…

Forest monitoring is critical for climate change mitigation. However, existing global tree height maps provide only static snapshots and do not capture temporal forest dynamics, which are essential for accurate carbon accounting. We…

Computer Vision and Pattern Recognition · Computer Science 2026-03-13 Jan Pauls , Karsten Schrödter , Sven Ligensa , Martin Schwartz , Berkant Turan , Max Zimmer , Sassan Saatchi , Sebastian Pokutta , Philippe Ciais , Fabian Gieseke

Accurate tree height estimation is vital for ecological monitoring and biomass assessment. We apply quantile regression to existing tree height estimation models based on satellite data to incorporate uncertainty quantification. Most…

Computer Vision and Pattern Recognition · Computer Science 2026-04-09 Karsten Schrödter , Jan Pauls , Fabian Gieseke

We have developed the world's first canopy height map of the distribution area of world-level giant trees. This mapping is crucial for discovering more individual and community world-level giant trees, and for analyzing and quantifying the…

Computer Vision and Pattern Recognition · Computer Science 2024-04-24 Guangpeng Fan , Fei Yan , Xiangquan Zeng , Qingtao Xu , Ruoyoulan Wang , Binghong Zhang , Jialing Zhou , Liangliang Nan , Jinhu Wang , Zhiwei Zhang , Jia Wang

Estimating canopy height and its changes at meter resolution from satellite imagery is a significant challenge in computer vision with critical environmental applications. However, the lack of open-access datasets at this resolution hinders…

NASA's Global Ecosystem Dynamics Investigation (GEDI) is a key climate mission whose goal is to advance our understanding of the role of forests in the global carbon cycle. While GEDI is the first space-based LIDAR explicitly optimized to…

Machine Learning · Computer Science 2021-11-05 Nico Lang , Nikolai Kalischek , John Armston , Konrad Schindler , Ralph Dubayah , Jan Dirk Wegner

Mapping forest resources and carbon is important for improving forest management and meeting the objectives of storing carbon and preserving the environment. Spaceborne remote sensing approaches have considerable potential to support forest…

Machine Learning · Statistics 2023-11-10 David Morin , Milena Planells , Stéphane Mermoz , Florian Mouret

We propose a framework for global-scale canopy height estimation based on satellite data. Our model leverages advanced data preprocessing techniques, resorts to a novel loss function designed to counter geolocation inaccuracies inherent in…

Computer Vision and Pattern Recognition · Computer Science 2026-03-13 Jan Pauls , Max Zimmer , Una M. Kelly , Martin Schwartz , Sassan Saatchi , Philippe Ciais , Sebastian Pokutta , Martin Brandt , Fabian Gieseke

Information on urban tree canopies is fundamental to mitigating climate change [1] as well as improving quality of life [2]. Urban tree planting initiatives face a lack of up-to-date data about the horizontal and vertical dimensions of the…

Image and Video Processing · Electrical Eng. & Systems 2022-12-13 John Francis , Stephen Law

Accurate forest canopy height estimation is essential for evaluating aboveground biomass and carbon stock dynamics, supporting ecosystem monitoring services like timber provisioning, climate change mitigation, and biodiversity conservation.…

Computer Vision and Pattern Recognition · Computer Science 2024-10-25 Jose B. Castro , Cheryl Rogers , Camile Sothe , Dominic Cyr , Alemu Gonsamo

Scattered trees outside of dense, closed-canopy forests are very important for carbon sequestration, supporting livelihoods, maintaining ecosystem integrity, and climate change adaptation and mitigation. In contrast to trees inside of…

Computer Vision and Pattern Recognition · Computer Science 2021-02-03 John Brandt , Fred Stolle

We present PrediTree, the first comprehensive open-source dataset designed for training and evaluating tree height prediction models at sub-meter resolution. This dataset combines very high-resolution (0.5m) LiDAR-derived canopy height…

Computer Vision and Pattern Recognition · Computer Science 2025-09-11 Hiyam Debary , Mustansar Fiaz , Levente Klein

Regular measurement of carbon stock in the world's forests is critical for carbon accounting and reporting under national and international climate initiatives, and for scientific research, but has been largely limited in scalability and…

Computer Vision and Pattern Recognition · Computer Science 2025-01-03 Manuel Weber , Carly Beneke , Clyde Wheeler

Estimating global tree canopy height is crucial for forest conservation and climate change applications. However, capturing high-resolution ground truth canopy height using LiDAR is expensive and not available globally. An efficient…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Daniele Rege Cambrin , Isaac Corley , Paolo Garza

Accurate estimation of forest biomass, a major carbon sink, relies heavily on tree-level traits such as height and species. Unoccupied Aerial Vehicles (UAVs) capturing high-resolution imagery from a single RGB camera offer a cost-effective…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Jannik Endres , Etienne Laliberté , David Rolnick , Arthur Ouaknine

With the recent increase in deforestation, forest fires, and regional temperatures, the concerns around the rapid and complete collapse of the Amazon rainforest ecosystem have heightened. The thresholds of deforestation and the temperature…

Atmospheric and Oceanic Physics · Physics 2025-07-04 Adam Giammarese , Jacob Brown , Nishant Malik
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