{"id":6973,"date":"2026-07-03T12:37:13","date_gmt":"2026-07-03T10:37:13","guid":{"rendered":"https:\/\/ist.blogs.inrae.fr\/afs\/?p=6973"},"modified":"2026-07-03T12:37:13","modified_gmt":"2026-07-03T10:37:13","slug":"estimating-the-age-of-eucalyptus-plantations-using-monthly-harmonized-landsat-sentinel-imagery-and-a-landtrendr-based-workflow","status":"publish","type":"post","link":"https:\/\/ist.blogs.inrae.fr\/afs\/2026\/07\/03\/estimating-the-age-of-eucalyptus-plantations-using-monthly-harmonized-landsat-sentinel-imagery-and-a-landtrendr-based-workflow\/","title":{"rendered":"Estimating the age of Eucalyptus plantations using monthly Harmonized Landsat\u2013Sentinel imagery and a LandTrendr-based workflow"},"content":{"rendered":"<script type='text\/javascript' src='https:\/\/d1bxh8uas1mnw7.cloudfront.net\/assets\/embed.js'><\/script><p><span style=\"color: #0d5c06;font-size: 10pt\"><strong>Research paper<\/strong><\/span><\/p>\n<p><strong><a href=\"https:\/\/ist.blogs.inrae.fr\/afs\/wp-content\/uploads\/sites\/5\/2026\/07\/26-07-03_Huang-J.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-6974 alignright\" src=\"https:\/\/ist.blogs.inrae.fr\/afs\/wp-content\/uploads\/sites\/5\/2026\/07\/26-07-03_Huang-J-277x300.jpg\" alt=\"\" width=\"292\" height=\"316\" srcset=\"https:\/\/ist.blogs.inrae.fr\/afs\/wp-content\/uploads\/sites\/5\/2026\/07\/26-07-03_Huang-J-277x300.jpg 277w, https:\/\/ist.blogs.inrae.fr\/afs\/wp-content\/uploads\/sites\/5\/2026\/07\/26-07-03_Huang-J-640x693.jpg 640w, https:\/\/ist.blogs.inrae.fr\/afs\/wp-content\/uploads\/sites\/5\/2026\/07\/26-07-03_Huang-J.jpg 685w\" sizes=\"auto, (max-width: 292px) 100vw, 292px\" \/><\/a>Key message<\/strong><\/p>\n<p align=\"justify\">Using monthly Harmonized Landsat\u2013Sentinel imagery and an adapted LandTrendr-based workflow, we achieved reliable month-resolved estimation of coppiced-stand age for\u00a0<i>Eucalyptus<\/i>\u00a0spp. plantations in Luzhai County, Guangxi, China. The workflow achieved 83.2% overall accuracy and a mean absolute timing error of 1.58\u00a0months, enabling reliable month-scale harvest dating for short-rotation plantations.<\/p>\n<p><strong>Keywords<\/strong><br \/>\nForest age estimation; Harvest detection; Spectral index fusion; Monthly time series; Harvest scheduling<\/p>\n<div class='altmetric-embed' data-badge-type='donut' data-doi='10.1186\/s13595-026-01339-5'  style='float: right; ' ><\/div>\n<p><strong>Publication<\/strong><br \/>\nHuang, J., Wei, H., Ding, J.\u00a0<i>et al.<\/i>\u00a0Estimating the age of\u00a0<i>Eucalyptus<\/i>\u00a0plantations using monthly Harmonized Landsat\u2013Sentinel imagery and a LandTrendr-based workflow.\u00a0<i>Annals of Forest Science<\/i>\u00a083, 23 (2026). <a href=\"https:\/\/doi.org\/10.1186\/s13595-026-01339-5\">https:\/\/doi.org\/10.1186\/s13595-026-01339-5<\/a><\/p>\n<p><strong>Data availability<\/strong><br \/>\nThe data supporting the findings of this study are publicly available in Zenodo at\u00a0<a href=\"https:\/\/doi.org\/10.5281\/zenodo.19045044\">https:\/\/doi.org\/10.5281\/zenodo.19045044<\/a>. The repository contains the HLS fused image, the Eucalyptus plantation classification result, the study-area boundary, training and validation samples, the harvest-date output, a README file describing the file organisation, and the core Google Earth Engine workflow files in text format. All files are openly accessible under the CC BY 4.0 licence.<\/p>\n<p><strong>Handling editor<\/strong><br \/>\nShengli Tao<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Research paper Key message Using monthly Harmonized Landsat\u2013Sentinel imagery and an adapted LandTrendr-based workflow, we achieved reliable month-resolved estimation of coppiced-stand age for\u00a0Eucalyptus\u00a0spp. plantations in Luzhai County, Guangxi, China. The workflow achieved 83.2% overall accuracy and a mean absolute timing error of 1.58\u00a0months, enabling reliable month-scale harvest dating for short-rotation plantations. Keywords Forest age estimation; [&hellip;]<\/p>\n","protected":false},"author":240,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[14,1,109,15],"tags":[],"class_list":["post-6973","post","type-post","status-publish","format-standard","hentry","category-article-type","category-non-classe","category-open-access","category-research-paper","cat-14-id","cat-1-id","cat-109-id","cat-15-id"],"_links":{"self":[{"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/posts\/6973","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/users\/240"}],"replies":[{"embeddable":true,"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/comments?post=6973"}],"version-history":[{"count":2,"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/posts\/6973\/revisions"}],"predecessor-version":[{"id":6976,"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/posts\/6973\/revisions\/6976"}],"wp:attachment":[{"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/media?parent=6973"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/categories?post=6973"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/tags?post=6973"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}