English
Related papers

Related papers: Scalable deep fusion of spaceborne lidar and synth…

200 papers

The Global Ecosystem Dynamics Investigation (GEDI) is a spaceborne lidar instrument that collects near-global measurements of forest structure. While expansive in scope, GEDI samples are spatially sparse and cover a small fraction of the…

Applications · Statistics 2024-01-04 Paul B. May , Andrew O. Finley , Ralph O. Dubayah

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

Spaceborne Light Detection and Ranging (LiDAR) systems, such as NASA's Global Ecosystem Dynamics Investigation (GEDI), provide forest structure for global carbon assessments. However, geolocation uncertainties (typically 5-15 m) propagate…

Image and Video Processing · Electrical Eng. & Systems 2025-11-25 Narumasa Tsutsumida , Rei Mitsuhashi , Yoshito Sawada , Akira Kato

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

The integration of multisource remote sensing data and deep learning models offers new possibilities for accurately mapping high spatial resolution forest height. We found that GEDI relative heights (RH) metrics exhibited strong correlation…

Computer Vision and Pattern Recognition · Computer Science 2023-11-21 Man Chen , Wenquan Dong , Hao Yu , Iain Woodhouse , Casey M. Ryan , Haoyu Liu , Selena Georgiou , Edward T. A. Mitchard

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

Monitoring and managing Earth's forests in an informed manner is an important requirement for addressing challenges like biodiversity loss and climate change. While traditional in situ or aerial campaigns for forest assessments provide…

Computer Vision and Pattern Recognition · Computer Science 2022-12-13 Alexander Becker , Stefania Russo , Stefano Puliti , Nico Lang , Konrad Schindler , Jan Dirk Wegner

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…

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

Large-scale high spatial resolution aboveground biomass (AGB) maps play a crucial role in determining forest carbon stocks and how they are changing, which is instrumental in understanding the global carbon cycle, and implementing policy to…

Computer Vision and Pattern Recognition · Computer Science 2024-05-27 Wenquan Dong , Edward T. A. Mitchard , Yuwei Chen , Man Chen , Congfeng Cao , Peilun Hu , Cong Xu , Steven Hancock

Characterizing urban environments with broad coverages and high precision is more important than ever for achieving the UN's Sustainable Development Goals (SDGs) as half of the world's populations are living in cities. Urban building height…

Estimating forest AGB at large scales and fine spatial resolutions has become increasingly important for greenhouse gas accounting, monitoring, and verification efforts to mitigate climate change. Airborne LiDAR is highly valuable for…

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

Accurate tree segmentation is a key step in extracting individual tree metrics from forest laser scans, and is essential to understanding ecosystem functions in carbon cycling and beyond. Over the past decade, tree segmentation algorithms…

Computer Vision and Pattern Recognition · Computer Science 2025-09-16 Yihang She , Andrew Blake , David Coomes , Srinivasan Keshav

Monitoring and understanding forest dynamics is essential for environmental conservation and management. This is why the Swiss National Forest Inventory (NFI) provides countrywide vegetation height maps at a spatial resolution of 0.5 m. Its…

Computer Vision and Pattern Recognition · Computer Science 2023-09-06 Yuchang Jiang , Marius Rüetschi , Vivien Sainte Fare Garnot , Mauro Marty , Konrad Schindler , Christian Ginzler , Jan D. Wegner

The analysis of the multi-layer structure of wild forests is an important challenge of automated large-scale forestry. While modern aerial LiDARs offer geometric information across all vegetation layers, most datasets and methods focus only…

Computer Vision and Pattern Recognition · Computer Science 2022-04-26 Ekaterina Kalinicheva , Loic Landrieu , Clément Mallet , Nesrine Chehata

Access to below-canopy volumetric vegetation data is crucial for understanding ecosystem dynamics. We address the long-standing limitation of remote sensing to penetrate deep into dense canopy layers. LiDAR and radar are currently…

Computer Vision and Pattern Recognition · Computer Science 2025-08-28 Mohamed Youssef , Jian Peng , Oliver Bimber

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

The ability to map challenging subarctic environments opens new horizons for robotic deployments in industries such as forestry, surveillance, and open-pit mining. In this paper, we explore possibilities of large-scale lidar mapping in a…

Accurate geolocation is essential for the reliable use of GEDI LiDAR data in footprint-scale applications such as aboveground biomass modeling, data fusion, and ecosystem monitoring. However, residual geolocation errors arising from both…

Computational Engineering, Finance, and Science · Computer Science 2025-11-04 Leonel Corado , Sérgio Godinho , Carlos Alberto Silva , Juan Guerra-Hernández , Francesco Valérioa , Teresa Gonçalves , Pedro Salgueiro
‹ Prev 1 2 3 10 Next ›