{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,22]],"date-time":"2026-01-22T02:23:47Z","timestamp":1769048627581,"version":"3.49.0"},"reference-count":44,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2023,10,24]],"date-time":"2023-10-24T00:00:00Z","timestamp":1698105600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100014051","name":"Broad Agency Announcement Program","doi-asserted-by":"publisher","award":["W913E518C0005"],"award-info":[{"award-number":["W913E518C0005"]}],"id":[{"id":"10.13039\/100014051","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100014051","name":"Broad Agency Announcement Program","doi-asserted-by":"publisher","award":["W913E521C0006"],"award-info":[{"award-number":["W913E521C0006"]}],"id":[{"id":"10.13039\/100014051","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100014051","name":"Cold Regions Research and Engineering Laboratory (ERDC-CRREL)","doi-asserted-by":"publisher","award":["W913E518C0005"],"award-info":[{"award-number":["W913E518C0005"]}],"id":[{"id":"10.13039\/100014051","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100014051","name":"Cold Regions Research and Engineering Laboratory (ERDC-CRREL)","doi-asserted-by":"publisher","award":["W913E521C0006"],"award-info":[{"award-number":["W913E521C0006"]}],"id":[{"id":"10.13039\/100014051","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Recently, sensors deployed on unpiloted aerial systems (UAS) have provided snow depth estimates with high spatial resolution over watershed scales. While light detection and ranging (LiDAR) produces precise snow depth estimates for areas without vegetation cover, there has generally been poorer precision in forested areas. At a constant flight speed, the poorest precision within forests is observed beneath tree canopies that retain foliage into or through winter. The precision of lidar-derived elevation products is improved by increasing the sample size of ground returns but doing so reduces the spatial coverage of a mission due to limitations of battery power. We address the influence of flight speed on ground return density for baseline and snow-covered conditions and the subsequent effect on precision of snow depth estimates across a mixed landscape, while evaluating trade-offs between precision and bias. Prior to and following a snow event in December 2020, UAS flights were conducted at four different flight speeds over a region consisting of three contrasting land types: (1) open field, (2) deciduous forest, (3) conifer forest. For all cover types, we observed significant improvements in precision as flight speeds were reduced to 2 m s\u22121, as well as increases in the area over which a 2 cm snow depth precision was achieved. On the other hand, snow depth estimate differences were minimized at baseline flight speeds of 2 m s\u22121 and 4 m s\u22121 and snow-on flight speeds of 6 m s\u22121 over open fields and between 2 and 4 m s\u22121 over forest areas. Here, with consideration to precision and estimate bias within each cover type, we make recommendations for ideal flight speeds based on survey ground conditions and vegetation cover.<\/jats:p>","DOI":"10.3390\/rs15215091","type":"journal-article","created":{"date-parts":[[2023,10,24]],"date-time":"2023-10-24T11:34:47Z","timestamp":1698147287000},"page":"5091","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Evaluating the Effects of UAS Flight Speed on Lidar Snow Depth Estimation in a Heterogeneous Landscape"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2499-8245","authenticated-orcid":false,"given":"Franklin B.","family":"Sullivan","sequence":"first","affiliation":[{"name":"Earth Systems Research Center, Institute for Earth, Oceans, and Space, University of New Hampshire, Durham, NH 03824, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Adam G.","family":"Hunsaker","sequence":"additional","affiliation":[{"name":"Earth Systems Research Center, Institute for Earth, Oceans, and Space, University of New Hampshire, Durham, NH 03824, USA"},{"name":"Department of Civil and Environmental Engineering, University of New Hampshire, Durham, NH 03824, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael W.","family":"Palace","sequence":"additional","affiliation":[{"name":"Earth Systems Research Center, Institute for Earth, Oceans, and Space, University of New Hampshire, Durham, NH 03824, USA"},{"name":"Department of Earth Sciences, University of New Hampshire, Durham, NH 03824, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jennifer M.","family":"Jacobs","sequence":"additional","affiliation":[{"name":"Earth Systems Research Center, Institute for Earth, Oceans, and Space, University of New Hampshire, Durham, NH 03824, USA"},{"name":"Department of Civil and Environmental Engineering, University of New Hampshire, Durham, NH 03824, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,24]]},"reference":[{"key":"ref_1","first-page":"C32B-01","article-title":"A New Global Climatology of Ephemeral and Seasonal Snow","volume":"2022","author":"Johnston","year":"2022","journal-title":"AGU Fall Meet. 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