{"id":6232,"date":"2024-10-28T14:00:18","date_gmt":"2024-10-28T13:00:18","guid":{"rendered":"https:\/\/ist.blogs.inrae.fr\/afs\/?p=6232"},"modified":"2024-10-31T15:24:48","modified_gmt":"2024-10-31T14:24:48","slug":"mapping-stem-volume-in-fast-growing-eucalypt-plantations-integrating-spectral-textural-and-temporal-remote-sensing-information-with-forest-inventories-and-spatial-models","status":"publish","type":"post","link":"https:\/\/ist.blogs.inrae.fr\/afs\/2024\/10\/28\/mapping-stem-volume-in-fast-growing-eucalypt-plantations-integrating-spectral-textural-and-temporal-remote-sensing-information-with-forest-inventories-and-spatial-models\/","title":{"rendered":"Mapping stem volume in fast-growing eucalypt plantations: integrating spectral, textural, and temporal remote sensing information with forest inventories and spatial models"},"content":{"rendered":"<script type='text\/javascript' src='https:\/\/d1bxh8uas1mnw7.cloudfront.net\/assets\/embed.js'><\/script><p><a href=\"https:\/\/ist.blogs.inrae.fr\/afs\/wp-content\/uploads\/sites\/5\/2024\/10\/Alo-AFS-e1730120294177.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"size-medium wp-image-6234 alignleft\" src=\"https:\/\/ist.blogs.inrae.fr\/afs\/wp-content\/uploads\/sites\/5\/2024\/10\/Alo-AFS-e1730120294177-300x202.jpg\" alt=\"\" width=\"300\" height=\"202\" srcset=\"https:\/\/ist.blogs.inrae.fr\/afs\/wp-content\/uploads\/sites\/5\/2024\/10\/Alo-AFS-e1730120294177-300x202.jpg 300w, https:\/\/ist.blogs.inrae.fr\/afs\/wp-content\/uploads\/sites\/5\/2024\/10\/Alo-AFS-e1730120294177-768x516.jpg 768w, https:\/\/ist.blogs.inrae.fr\/afs\/wp-content\/uploads\/sites\/5\/2024\/10\/Alo-AFS-e1730120294177-640x430.jpg 640w, https:\/\/ist.blogs.inrae.fr\/afs\/wp-content\/uploads\/sites\/5\/2024\/10\/Alo-AFS-e1730120294177.jpg 793w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/a><strong>Key message<\/strong><\/p>\n<p align=\"justify\">Accurate volume estimation in Eucalyptus plantation stands was achieved by a linear model using SPOT and Landsat multispectral imagery, specifically texture indices and pixel-scale NDVI time integrals, which reflect the local plantation growth history. Spatial modelling techniques such as Kriging with External Drift and Generalized Additive Model slightly improved predictions by accounting for spatial correlation of volume between sample points.<\/p>\n<p><strong>Keywords<\/strong><br \/>\nGeostatistics; Vegetation indices; Time series; Texture; Kriging with External Drift (KED); Generalized additive model (GAM); Fast-growing plantations<\/p>\n<div class='altmetric-embed' data-badge-type='donut' data-doi='10.1186\/s13595-024-01255-6'  style='float: right; ' ><\/div>\n<p><strong>Publication<\/strong><br \/>\nAl\u00f3, L.L., le Maire, G., Thiersch, C.R. et al. Mapping stem volume in fast-growing eucalypt plantations: integrating spectral, textural, and temporal remote sensing information with forest inventories and spatial models. Annals of Forest Science 81, 43 (2024). <a href=\"https:\/\/doi.org\/10.1186\/s13595-024-01255-6\">https:\/\/doi.org\/10.1186\/s13595-024-01255-6<\/a><\/p>\n<p><strong>Data and\/or Code availability<\/strong><br \/>\nThe data cannot be made available in a public repository due to proprietary issues. Data sharing agreement can be set up upon request.<br \/>\nThe custom code and\/or software application generated during and\/or analyzed during the current study are available from the corresponding author on reasonable request.<\/p>\n<p><strong>Handling Editor<\/strong><br \/>\nMatteo Vizzari<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Key message Accurate volume estimation in Eucalyptus plantation stands was achieved by a linear model using SPOT and Landsat multispectral imagery, specifically texture indices and pixel-scale NDVI time integrals, which reflect the local plantation growth history. Spatial modelling techniques such as Kriging with External Drift and Generalized Additive Model slightly improved predictions by accounting for [&hellip;]<\/p>\n","protected":false},"author":109,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[14,109,15],"tags":[],"class_list":["post-6232","post","type-post","status-publish","format-standard","hentry","category-article-type","category-open-access","category-research-paper","cat-14-id","cat-109-id","cat-15-id"],"_links":{"self":[{"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/posts\/6232","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\/109"}],"replies":[{"embeddable":true,"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/comments?post=6232"}],"version-history":[{"count":3,"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/posts\/6232\/revisions"}],"predecessor-version":[{"id":6241,"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/posts\/6232\/revisions\/6241"}],"wp:attachment":[{"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/media?parent=6232"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/categories?post=6232"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/tags?post=6232"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}