{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T18:52:02Z","timestamp":1778007122001,"version":"3.51.4"},"reference-count":46,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2017,12,3]],"date-time":"2017-12-03T00:00:00Z","timestamp":1512259200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Monitoring vegetation recovery typically requires ground measurements of vegetation height, which is labor-intensive and time-consuming. Recently, unmanned aerial vehicles (UAVs) have shown great promise for characterizing vegetation in a cost-efficient way, but the literature on specific methods and cost savings is scant. In this study, we surveyed vegetation height on seismic lines in Alberta\u2019s Boreal Forest using a point-intercept sampling strategy, and compared them to height estimates derived from UAV-based photogrammetric point clouds. In order to derive UAV-based vegetation height, we tested three different approaches to estimate terrain elevation: (1) UAV_RTK, where photogrammetric point clouds were normalized using terrain measurements obtained from a real-time kinematic global navigation satellite system (RTK GNSS) surveys; (2) UAV_LiDAR, where photogrammetric data were normalized using pre-existing LiDAR (Light Detection and Ranging) data; and (3) UAV_UAV, where UAV photogrammetry data were used alone. Comparisons were done at two scales: point level (n = 1743) and site level (n = 30). The point-level root-mean-square errors (RMSEs) of UAV_RTK, UAV_LiDAR, and UAV_UAV were 28 cm, 31 cm, and 30 cm, respectively. The site-level RMSEs were 11 cm, 15 cm, and 8 cm, respectively. At the aggregated site level, we found that UAV photogrammetry could replace traditional field-based vegetation surveys of mean vegetation height across the range of conditions assessed in this study, with an RMSE less than 10 cm. Cost analysis indicates that using UAV-based point clouds is more cost-effective than traditional field vegetation surveys.<\/jats:p>","DOI":"10.3390\/rs9121257","type":"journal-article","created":{"date-parts":[[2017,12,4]],"date-time":"2017-12-04T11:16:38Z","timestamp":1512386198000},"page":"1257","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":67,"title":["Measuring Vegetation Height in Linear Disturbances in the Boreal Forest with UAV Photogrammetry"],"prefix":"10.3390","volume":"9","author":[{"given":"Shijuan","family":"Chen","sequence":"first","affiliation":[{"name":"Department of Geography, University of Calgary, Calgary, AB T2N 1N4, Canada"},{"name":"Department of Earth and Environment, Boston University, 685 Commonwealth Avenue, Boston, MA 02215, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8079-3730","authenticated-orcid":false,"given":"Gregory","family":"McDermid","sequence":"additional","affiliation":[{"name":"Department of Geography, University of Calgary, Calgary, AB T2N 1N4, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guillermo","family":"Castilla","sequence":"additional","affiliation":[{"name":"Northern Forestry Centre, 5320 122 Street Northwest, Edmonton, AB T6H 3S5, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Julia","family":"Linke","sequence":"additional","affiliation":[{"name":"Department of Geography, University of Calgary, Calgary, AB T2N 1N4, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2017,12,3]]},"reference":[{"key":"ref_1","first-page":"419","article-title":"Conservation of caribou (Rangifer tarandus) in Canada: An uncertain future","volume":"89","author":"Ray","year":"2011","journal-title":"Can. 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