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Beyond Ice: NASA’s ICESat-2 spaceborne lidar mission for land and vegetation applications

delete2026-03-10
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OA
AI
C
Carlos Alberto Silva
A
Amy Neuenschwander
C
Caio Hamamura
S
Sérgio Godinho
K
Kody M. Brock
L
Lonesome Malambo
L
Lana L. Narine
J
Jeff W. Atkins
J
Jordan S. Borak
S
Sorin Popescu
I
Inácio Thomaz Bueno
L
Lucas Bielak Rezende
G
Giulio Brossi Santoro
A
Ana Paula Dalla Côrte
C
Cesar Alvites
N
Nooshin Mashhadi
A
Adrián Cardíl
A
Andrew T. Hudak
L
Lauri Korhonen
A
Ajay Sharma
J
Jeffery B. Cannon
M
Midhun Mohan
W
Wan Shafrina Wan Mohd Jaafar
V
Veraldo Liesenberg
C
Carine Klauberg
DOI:10.1109/mgrs.2026.3666794delete
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Abstract

Abstract

En 中文
The extension of NASA’s Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) mission beyond the cryosphere to include the study of vegetation and the land surface has significantly advanced global Earth observation. This review synthesizes findings from 293 peer-reviewed articles and provides a comprehensive assessment of the mission’s contributions to terrestrial ecosystem science. We begin by outlining the mission’s objectives, instrumentation, and core data products—particularly ATL03 (geolocated photons) and ATL08 (terrain and canopy heights)—which have supported a wide array of applications in forestry, terrain analysis, and environmental monitoring. Our analysis shows that most studies focus on temperate and tropical broadleaf forests, with a strong emphasis on estimating canopy height, terrain elevation, and forest structure. Terrain metrics derived from <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ICESat-2</i> products typically achieve high accuracy, while vegetation variables, such as canopy height, cover, leaf area index (LAI), and aboveground biomass, demonstrate moderate to strong accuracies across biomes. While parametric models remain the most used approach, machine learning methods are expanding, and more than one third of the reviewed literature incorporates synergistic analyses with other satellite missions. Despite its versatility, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ICESat-2</i> remains underutilized in several key domains—including nonforest vegetation, fire ecology, wildlife habitat assessment, urban monitoring, and disturbance detection—mainly due to the scarcity of standardized algorithms and validated reference datasets. However, the growing availability of open source processing tools presents a significant opportunity for expanding the user base and fostering innovation in these emerging areas. Future advancements, such as the forthcoming ATL18 gridded canopy height and terrain products, alongside synergies with missions like the European Space Agency (ESA)’s BIOMASS and the NASA–Indian Space Research Organisation (ISRO) Synthetic Aperture Radar (NISAR), promise to enhance multisensor integration and ecosystem monitoring. Overall, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ICESat-2</i> continues to evolve as a powerful resource for characterizing vegetation structure, ecosystem dynamics, and land surface processes on a global scale.
Keywords:
Vegetation mapping
Sea surface
Photonics
Land surface
Sea ice
NASA
Ecosystems
Sea measurements
Earth Observing System

Journal

IEEE Geoscience and Remote Sensing Magazine cover
IEEE Geoscience and Remote Sensing Magazine
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16.4
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