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Related papers: Forest canopy height estimation from satellite RGB…

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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 canopy height information is essential for quantifying forest carbon, monitoring restoration and degradation, and assessing habitat structure, yet high-fidelity measurements from airborne laser scanning (ALS) remain unevenly…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 John Brandt , Seungeun Yi , Jamie Tolan , Xinyuan Li , Peter Potapov , Jessica Ertel , Justine Spore , Huy V. Vo , Michaël Ramamonjisoa , Patrick Labatut , Piotr Bojanowski , Camille Couprie

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

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…

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

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

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

Our study introduces a novel, low-cost, and reproducible framework for real-time, object-level structural assessment and geolocation of roadside vegetation and infrastructure with commonly available but underutilized dashboard camera…

Computer Vision and Pattern Recognition · Computer Science 2025-08-18 Durga Joshi , Chandi Witharana , Robert Fahey , Thomas Worthley , Zhe Zhu , Diego Cerrai

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

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

Monocular height estimation (MHE) from very-high-resolution (VHR) optical imagery remains challenging due to limited structural cues and the high cost and geographic constraints of conventional elevation data such as airborne LiDAR and…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Jian Song , Hongruixuan Chen , Naoto Yokoya

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

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

Geolocation error in spaceborne sampling light detection and ranging (LiDAR) measurements of forest structure can compromise forest attribute estimates and degrade integration with georeferenced field measurements or other remotely sensed…

Forest inventories rely on accurate measurements of the diameter at breast height (DBH) for ecological monitoring, resource management, and carbon accounting. While LiDAR-based techniques can achieve centimeter-level precision, they are…

Computer Vision and Pattern Recognition · Computer Science 2026-04-17 Siming He , Zachary Osman , Fernando Cladera , Dexter Ong , Nitant Rai , Patrick Corey Green , Vijay Kumar , Pratik Chaudhari

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…

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

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

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
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