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ORIGINAL RESEARCH article

Front. Earth Sci.
Sec. Cryospheric Sciences
Volume 13 - 2025 | doi: 10.3389/feart.2025.1487776
This article is part of the Research Topic Remote Sensing of the Cryosphere View all 8 articles

Modeling snow optical properties from single wavelength airborne lidar in steep forested terrain

Provisionally accepted
Brenton A Wilder Brenton A Wilder 1Josh Enterkine Josh Enterkine 1Zachary Hoppinen Zachary Hoppinen 1,2Naheem Adebisi Naheem Adebisi 1Hans-Peter Marshall Hans-Peter Marshall 1Shad O'Neel Shad O'Neel 1,2Thomas Van Der Weide Thomas Van Der Weide 1Alicia M Kinoshita Alicia M Kinoshita 3Nancy F. Glenn Nancy F. Glenn 1*
  • 1 Boise State University, Boise, United States
  • 2 Cold Regions Research and Engineering Laboratory, Hanover, New Hampshire, United States
  • 3 San Diego State University, San Diego, California, United States

The final, formatted version of the article will be published soon.

    Airborne lidar is a powerful tool used by water resource managers to map snow depth and aid in producing spatially distributed snow water equivalent (SWE) when combined with modeled density. However, limited research so far has focused on retrieving optical snow properties from lidar. Optical snow surface properties directly impact albedo, which has a major control on snowmelt timing, which is especially useful for water management applications. Airborne lidar instruments typically emit energy at a wavelength of 1064 nm, which can be informative in mapping optical snow surface properties due tosince the grain size modulating modulates the reflectance at this wavelength.In this paper we present and validate an approach using airborne lidar for estimating snow reflectance and optical grain size at high spatial resolution. We utilize three lidar flights over the Boise National Forest, USA, during a winter season from December 2022 to March 2023. We discuss sensitivities to beam incidence angles, compare results to in situ measurements snow grain size, and perform spatial analyses to ensure reflectance and optical grain size varies across space and time in a manner that matches the literatureas anticipated. Modeled optical grain size from lidar performed well (Root mean squared difference = 49 μm; percent mean absolute difference=31%; n=28), suggesting that aerial lidar surveys with more research maycan be useful in mapping snow reflectance and optical grain size for dry snow, and may support development of other remote sensing technologies and aid water resources management.

    Keywords: lidar, Optical Grain Size, reflectance, cryosphere, remote sensing

    Received: 28 Aug 2024; Accepted: 27 Jan 2025.

    Copyright: © 2025 Wilder, Enterkine, Hoppinen, Adebisi, Marshall, O'Neel, Van Der Weide, Kinoshita and Glenn. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Nancy F. Glenn, Boise State University, Boise, United States

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.