Review article: using spaceborne lidar for snow depth retrievals: recent findings and utility for hydrologic applications

Abstract. Lidar is an effective tool to measure snow depth over key watersheds across the United States. Lidar-derived snow depth observations from airborne platforms have demonstrated centimeter-level accuracy at high spatial resolution. However, ground-based and airborne lidar surveys are costly and limited in space and time. In recent years, there has been an emerging interest in using spaceborne lidar to estimate snow depth. Preliminary results from spaceborne lidar altimeters such as the NASA Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) can provide routine snow depth retrievals over watersheds, though further research on accuracy, coverage, and operational potential is needed. In this review, we outline the current status of research using spaceborne lidar to derive snow depth. We focus on the currently operational ICESat-2 mission, with a summary of snow observations gathered from previous studies. An example snow depth retrieval using ICESat-2 is also given over the Alaskan tundra. We also outline best practices for spaceborne lidar snow depth retrieval, based on findings from recent studies. We conclude with a discussion of ongoing challenges for spaceborne lidar, with suggestions for future studies and requirements for future mission concepts.

Authors

Institutions

Publication Details

Journal
˜The œcryosphere
Published
2025-11-13
DOI
https://doi.org/10.5194/tc-19-5671-2025
Citations
1
Primary Topic
Cryospheric studies and observations
Type
article
Field-Weighted Citation Impact
1.30

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Review article: using spaceborne lidar for snow depth retrievals: recent findings and utility for hydrologic applications

César Deschamps‐Berger, Zachary Fair, Justin M. Pflug, Karina Zikan et al.
1 citations
˜The œcryosphere
Cryospheric studies and observations
1.30
article

Review article: using spaceborne lidar for snow depth retrievals: recent findings and utility for hydrologic applications

César Deschamps‐Berger, Zachary Fair, Justin M. Pflug, Karina Zikan, Hannah Besso, Désirée Treichler, Jessica D. Lundquist, Carrie Vuyovich, David Shean, Ellyn M. Enderlin, T. Neumann
article en
1 citations

Abstract

Abstract. Lidar is an effective tool to measure snow depth over key watersheds across the United States. Lidar-derived snow depth observations from airborne platforms have demonstrated centimeter-level accuracy at high spatial resolution. However, ground-based and airborne lidar surveys are costly and limited in space and time. In recent years, there has been an emerging interest in using spaceborne lidar to estimate snow depth. Preliminary results from spaceborne lidar altimeters such as the NASA Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) can provide routine snow depth retrievals over watersheds, though further research on accuracy, coverage, and operational potential is needed. In this review, we outline the current status of research using spaceborne lidar to derive snow depth. We focus on the currently operational ICESat-2 mission, with a summary of snow observations gathered from previous studies. An example snow depth retrieval using ICESat-2 is also given over the Alaskan tundra. We also outline best practices for spaceborne lidar snow depth retrieval, based on findings from recent studies. We conclude with a discussion of ongoing challenges for spaceborne lidar, with suggestions for future studies and requirements for future mission concepts.

˜The œcryosphereVol. 19(11)
Boise State University (US), Goddard Space Flight Center (US), University of Oslo (NO), University of Washington (US), Instituto Pirenaico de Ecología (ES), Earth System Science Interdisciplinary Center (US), University of Maryland, College Park (US)
Nuclear Safety and Security Commission, Goddard Space Flight Center
Openalex Percentile: Top 16%
Cryospheric studies and observations
1.30
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.