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Large-scale, high-resolution forest canopy height mapping plays a crucial role in understanding regional and global carbon and water cycles. Spaceborne LiDAR missions, including the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) and…

Computer Vision and Pattern Recognition · Computer Science 2026-02-10 Yongkang Lai , Xihan Mu , Dasheng Fan , Donghui Xie , Shanxin Guo , Wenli Huang , Tianjie Zhao , Guangjian Yan

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

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

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…

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

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

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…

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, cost-effective monitoring of plantation aboveground biomass (AGB) is crucial for supporting local livelihoods and carbon sequestration initiatives like the China Certified Emission Reduction (CCER) program. High-resolution canopy…

Computer Vision and Pattern Recognition · Computer Science 2025-06-26 Shen Tan , Xin Zhang , Liangxiu Han , Huaguo Huang , Han Wang

The recent decline of the European forest carbon sink highlights the need for spatially explicit and frequently updated forest monitoring tools. Yet, existing satellite-based disturbance products remain too coarse to detect changes at the…

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

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

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

The increasing demand for commodities is leading to changes in land use worldwide. In the tropics, deforestation, which causes high carbon emissions and threatens biodiversity, is often linked to agricultural expansion. While the need for…

Computer Vision and Pattern Recognition · Computer Science 2021-07-16 Nico Lang , Konrad Schindler , Jan Dirk Wegner

Accurate forest stand delineation is essential for forest inventory and management but remains a largely manual and subjective process. A recent study has shown that deep learning can produce stand delineations comparable to expert…

Computer Vision and Pattern Recognition · Computer Science 2026-02-26 Håkon Næss Sandum , Hans Ole Ørka , Oliver Tomic , Terje Gobakken

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

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…

Tree height estimation serves as an important proxy for biomass estimation in ecological and forestry applications. While traditional methods such as photogrammetry and Light Detection and Ranging (LiDAR) offer accurate height measurements,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-04 Grace Colverd , Jumpei Takami , Laura Schade , Karol Bot , Joseph A. Gallego-Mejia

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
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