Beyond Ice: NASA’s ICESat-2 spaceborne lidar mission for land and vegetation applications
| Authors: | Carlos Alberto Silva, Amy Neuenschwander, Caio Hamamura, Sérgio Godinho, Kody M. Brock, Lonesome Malambo, Lana Narine, Jeff W. Atkins, Jordan S. Borak, Sorin Popescu, Inacio T. Bueno, Lucas Bielak Rezende, Giulio Brossi Santoro, Ana Paula Dalla Corte, Cesar Ivan Alvites Diaz, Nooshin Mashhadi, Adrián Cardil, Andrew T. Hudak, Lauri Korhonen, Ajay Sharma, Jeffery B. Cannon, Midhun Mohan, Wan Shafrina Wan Mohd Jaafar, Veraldo Liesenberg, Carine Klauberg |
| Year: | 2026 |
| Type: | Scientific Journal |
| Station: | Rocky Mountain Research Station |
| DOI: | https://doi.org/10.1109/MGRS.2026.3666794 |
| Source: | IEEE Geoscience and Remote Sensing Magazine |
Abstract
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 ICESat-2 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, ICESat-2 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, ICESat-2 continues to evolve as a powerful resource for characterizing vegetation structure, ecosystem dynamics, and land surface processes on a global scale.