{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,3]],"date-time":"2025-12-03T18:05:20Z","timestamp":1764785120485,"version":"build-2065373602"},"reference-count":116,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2023,4,8]],"date-time":"2023-04-08T00:00:00Z","timestamp":1680912000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100007352","name":"National Science Foundation","doi-asserted-by":"publisher","award":["0856516","0856628","1432277","1433330","1504224","1504345","1836839","1836861"],"award-info":[{"award-number":["0856516","0856628","1432277","1433330","1504224","1504345","1836839","1836861"]}],"id":[{"id":"10.13039\/100007352","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Plot-level photography is an attractive time-saving alternative to field measurements for vegetation monitoring. However, widespread adoption of this technique relies on efficient workflows for post-processing images and the accuracy of the resulting products. Here, we estimated relative vegetation cover using both traditional field sampling methods (point frame) and semi-automated classification of photographs (plot-level photography) across thirty 1 m2 plots near Utqia\u0121vik, Alaska, from 2012 to 2021. Geographic object-based image analysis (GEOBIA) was applied to generate objects based on the three spectral bands (red, green, and blue) of the images. Five machine learning algorithms were then applied to classify the objects into vegetation groups, and random forest performed best (60.5% overall accuracy). Objects were reliably classified into the following classes: bryophytes, forbs, graminoids, litter, shadows, and standing dead. Deciduous shrubs and lichens were not reliably classified. Multinomial regression models were used to gauge if the cover estimates from plot-level photography could accurately predict the cover estimates from the point frame across space or time. Plot-level photography yielded useful estimates of vegetation cover for graminoids. However, the predictive performance varied both by vegetation class and whether it was being used to predict cover in new locations or change over time in previously sampled plots. These results suggest that plot-level photography may maximize the efficient use of time, funding, and available technology to monitor vegetation cover in the Arctic, but the accuracy of current semi-automated image analysis is not sufficient to detect small changes in cover.<\/jats:p>","DOI":"10.3390\/rs15081972","type":"journal-article","created":{"date-parts":[[2023,4,10]],"date-time":"2023-04-10T03:19:54Z","timestamp":1681096794000},"page":"1972","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Can Plot-Level Photographs Accurately Estimate Tundra Vegetation Cover in Northern Alaska?"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5067-5960","authenticated-orcid":false,"given":"Hana L.","family":"Sellers","sequence":"first","affiliation":[{"name":"Department of Biological Sciences, Grand Valley State University, 1 Campus Dr., Allendale, MI 49401, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0052-8580","authenticated-orcid":false,"given":"Sergio A.","family":"Vargas Zesati","sequence":"additional","affiliation":[{"name":"Department of Biological Sciences and the Environmental Science and Engineering Program, The University of Texas at El Paso, 500 W University Ave., El Paso, TX 79968, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1085-8521","authenticated-orcid":false,"given":"Sarah C.","family":"Elmendorf","sequence":"additional","affiliation":[{"name":"Institute of Arctic and Alpine Research, University of Colorado, Boulder, CO 80309, USA"}]},{"given":"Alexandra","family":"Locher","sequence":"additional","affiliation":[{"name":"Department of Biological Sciences, Grand Valley State University, 1 Campus Dr., Allendale, MI 49401, USA"}]},{"given":"Steven F.","family":"Oberbauer","sequence":"additional","affiliation":[{"name":"Department of Biological Sciences and Institute of Environment, Florida International University, 11200 SW 8th St., Miami, FL 33199, USA"}]},{"given":"Craig E.","family":"Tweedie","sequence":"additional","affiliation":[{"name":"Department of Biological Sciences and the Environmental Science and Engineering Program, The University of Texas at El Paso, 500 W University Ave., El Paso, TX 79968, USA"}]},{"given":"Chandi","family":"Witharana","sequence":"additional","affiliation":[{"name":"Department of Natural Resources and the Environment, University of Connecticut, Storrs, CT 06269, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4764-7691","authenticated-orcid":false,"given":"Robert D.","family":"Hollister","sequence":"additional","affiliation":[{"name":"Department of Biological Sciences, Grand Valley State University, 1 Campus Dr., Allendale, MI 49401, USA"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,8]]},"reference":[{"key":"ref_1","unstructured":"P\u00f6rtner, H.O., Roberts, D.C., Tignor, M., Poloczanska, E.S., Mintenbeck, K., Alegr\u00eda, A., Craig, M., Langsdorf, S., L\u00f6schke, S., and M\u00f6ller, V. 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