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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

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

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

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

Forest structural complexity metrics integrate multiple canopy attributes into a single value that reflects habitat quality and ecosystem function. Spaceborne lidar from the Global Ecosystem Dynamics Investigation (GEDI) has enabled mapping…

Computer Vision and Pattern Recognition · Computer Science 2025-10-09 Tiago de Conto , John Armston , Ralph Dubayah

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

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 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

Modern unmanned aerial vehicles (UAVs) are irreplaceable in search and rescue (SAR) missions to obtain a situational overview or provide closeups without endangering personnel. However, UAVs heavily rely on global navigation satellite…

Robotics · Computer Science 2024-12-04 Jan Quenzel , Linus T. Mallwitz , Benedikt T. Arnold , Sven Behnke

Reliable wall-to-wall biomass density estimation from NASA's GEDI mission requires interpolating sparse LIDAR observations across heterogeneous landscapes. While machine learning approaches like Random Forest and XGBoost are widely used,…

Machine Learning · Computer Science 2026-02-05 Robin Young , Srinivasan Keshav

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

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 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…

This work presents the first quantitative study of alignment errors between small uncrewed aerial systems (sUAS) georectified imagery and a priori building polygons and finds that alignment errors are non-uniform and irregular, which…

Computer Vision and Pattern Recognition · Computer Science 2025-06-23 Thomas Manzini , Priyankari Perali , Raisa Karnik , Mihir Godbole , Hasnat Abdullah , Robin Murphy

Simultaneous localization and mapping (SLAM) approaches for mobile robots remains challenging in forest or arboreal fruit farming environments, where tree canopies obstruct Global Navigation Satellite Systems (GNSS) signals. Unlike indoor…

Mountainous terrain is increasingly being measured and mapped by airplane-based LiDAR (Light Detection and Ranging) techniques, but the accuracy of these measurements in such topographically variable terrain is not well understood. For this…

The collection of ecological data in the field is essential to diagnose, monitor and manage ecosystems in a sustainable way. Since acquisition of this information through traditional methods are generally time-consuming, due to the…

Computer Vision and Pattern Recognition · Computer Science 2024-01-12 Ion Ciobotari , Adriana Príncipe , Maria Alexandra Oliveira , João Nuno Silva

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
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