{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,23]],"date-time":"2026-02-23T23:47:54Z","timestamp":1771890474534,"version":"3.50.1"},"reference-count":89,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2020,5,9]],"date-time":"2020-05-09T00:00:00Z","timestamp":1588982400000},"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>Forest plantations are globally important for the economy and are significant for carbon sequestration. Properly managing plantations requires accurate information about stand timber stocks. In this study, we used the area (ABA) and individual tree (ITD) based approaches for estimating stem volume in fast-growing Eucalyptus spp forest plantations. Herein, we propose a new method to improve individual tree detection (ITD) in dense canopy homogeneous forests and assess the effects of stand age, slope and scan angle on ITD accuracy. Field and Light Detection and Ranging (LiDAR) data were collected in Eucalyptus urophylla x Eucalyptus grandis even-aged forest stands located in the mountainous region of the Rio Doce Valley, southeastern Brazil. We tested five methods to estimate volume from LiDAR-derived metrics using ABA: Artificial Neural Network (ANN), Random Forest (RF), Support Vector Machine (SVM), and linear and Gompertz models. LiDAR-derived canopy metrics were selected using the Recursive Feature Elimination algorithm and Spearman\u2019s correlation, for nonparametric and parametric methods, respectively. For the ITD, we tested three ITD methods: two local maxima filters and the watershed method. All methods were tested adding our proposed procedure of Tree Buffer Exclusion (TBE), resulting in 35 possibilities for treetop detection. Stem volume for this approach was estimated using the Schumacher and Hall model. Estimated volumes in both ABA and ITD approaches were compared to the field observed values using the F-test. Overall, the ABA with ANN was found to be better for stand volume estimation (     r  y  y ^        = 0.95 and RMSE = 14.4%). Although the ITD results showed similar precision (     r  y  y ^        = 0.94 and RMSE = 16.4%) to the ABA, the results underestimated stem volume in younger stands and in gently sloping terrain (&lt;25%). Stem volume maps also differed between the approaches; ITD represented the stand variability better. In addition, we discuss the importance of LiDAR metrics as input variables for stem volume estimation methods and the possible issues related to the ABA and ITD performance.<\/jats:p>","DOI":"10.3390\/rs12091513","type":"journal-article","created":{"date-parts":[[2020,5,11]],"date-time":"2020-05-11T12:26:30Z","timestamp":1589199990000},"page":"1513","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":38,"title":["Estimating Stem Volume in Eucalyptus Plantations Using Airborne LiDAR: A Comparison of Area- and Individual Tree-Based Approaches"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7840-3905","authenticated-orcid":false,"given":"Rodrigo Vieira","family":"Leite","sequence":"first","affiliation":[{"name":"Department of Forest Engineering, Federal University of Vi\u00e7osa, Vi\u00e7osa 36570-900, MG, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7597-2427","authenticated-orcid":false,"given":"Cibele Hummel do","family":"Amaral","sequence":"additional","affiliation":[{"name":"Department of Forest Engineering, Federal University of Vi\u00e7osa, Vi\u00e7osa 36570-900, MG, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6500-4289","authenticated-orcid":false,"given":"Raul de Paula","family":"Pires","sequence":"additional","affiliation":[{"name":"School of Agrifood and Forestry Science and Engineering, University of Lleida, 25198 Lleida, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7844-3560","authenticated-orcid":false,"given":"Carlos Alberto","family":"Silva","sequence":"additional","affiliation":[{"name":"School of Forest Resources and Conservation, University of Florida, Gainesville, FL 32611, USA"},{"name":"Department of Geographical Sciences, University of Maryland, College Park, MD 20740, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6475-3376","authenticated-orcid":false,"given":"Carlos Pedro Boechat","family":"Soares","sequence":"additional","affiliation":[{"name":"Department of Forest Engineering, Federal University of Vi\u00e7osa, Vi\u00e7osa 36570-900, MG, Brazil"}]},{"given":"Renata Paulo","family":"Macedo","sequence":"additional","affiliation":[{"name":"Klabin S\/A, Tel\u00eamaco borba 84275-000, PR, Brazil"}]},{"given":"Antonilmar Ara\u00fajo Lopes da","family":"Silva","sequence":"additional","affiliation":[{"name":"Celulose Nipo-Brasileira S.A. (CENIBRA), Belo Oriente 35196-000, MG, Brazil"}]},{"given":"Eben North","family":"Broadbent","sequence":"additional","affiliation":[{"name":"Spatial Ecology and Conservation (SPEC) Lab, School of Forest Resources and Conservation, University of Florida, Gainesville, FL 32611, USA"}]},{"given":"Midhun","family":"Mohan","sequence":"additional","affiliation":[{"name":"Department of Geography, University of California\u2013Berkeley, Berkeley, CA 94709, USA"}]},{"given":"H\u00e9lio Garcia","family":"Leite","sequence":"additional","affiliation":[{"name":"Department of Forest Engineering, Federal University of Vi\u00e7osa, Vi\u00e7osa 36570-900, MG, Brazil"}]}],"member":"1968","published-online":{"date-parts":[[2020,5,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"969","DOI":"10.1109\/36.921414","article-title":"A segmentation-based method to retrieve stem volume estimates from 3-D tree height models produced by laser scanners","volume":"39","author":"Kelle","year":"2001","journal-title":"IEEE Trans. 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