Articles | Volume 15, issue 3
Research article
24 Mar 2021
Research article |  | 24 Mar 2021

Snow depth mapping with unpiloted aerial system lidar observations: a case study in Durham, New Hampshire, United States

Jennifer M. Jacobs, Adam G. Hunsaker, Franklin B. Sullivan, Michael Palace, Elizabeth A. Burakowski, Christina Herrick, and Eunsang Cho


Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Publish subject to revisions (further review by editor and referees) (30 Jun 2020) by Philip Marsh
AR by Svenja Lange on behalf of the Authors (13 Aug 2020)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (28 Sep 2020) by Philip Marsh
RR by Anonymous Referee #1 (09 Oct 2020)
RR by Anonymous Referee #3 (26 Nov 2020)
RR by Anonymous Referee #2 (05 Dec 2020)
RR by Anonymous Referee #4 (04 Jan 2021)
ED: Publish subject to minor revisions (review by editor) (14 Jan 2021) by Philip Marsh
AR by Jennifer Jacobs on behalf of the Authors (25 Jan 2021)  Author's response    Author's tracked changes    Manuscript
ED: Publish as is (25 Jan 2021) by Philip Marsh
Short summary
This pilot study describes a proof of concept for using lidar on an unpiloted aerial vehicle to map shallow snowpack (< 20 cm) depth in open terrain and forests. The 1 m2 resolution snow depth map, generated by subtracting snow-off from snow-on lidar-derived digital terrain models, consistently had 0.5 to 1 cm precision in the field, with a considerable reduction in accuracy in the forest. Performance depends on the point cloud density and the ground surface variability and vegetation.