{"id":1953,"date":"2016-09-03T17:42:11","date_gmt":"2016-09-03T15:42:11","guid":{"rendered":"http:\/\/ist.blogs.inra.fr\/afs\/?p=1953"},"modified":"2016-09-03T17:42:53","modified_gmt":"2016-09-03T15:42:53","slug":"multidimensional-scaling-of-first-return-airborne-laser-echoes-for-prediction-and-model-assisted-estimation-of-a-distribution-of-tree-stem-diameters","status":"publish","type":"post","link":"https:\/\/ist.blogs.inrae.fr\/afs\/2016\/09\/03\/multidimensional-scaling-of-first-return-airborne-laser-echoes-for-prediction-and-model-assisted-estimation-of-a-distribution-of-tree-stem-diameters\/","title":{"rendered":"Multidimensional scaling of first-return airborne laser echoes for prediction and model-assisted estimation of a distribution of tree stem diameters"},"content":{"rendered":"<script type='text\/javascript' src='https:\/\/d1bxh8uas1mnw7.cloudfront.net\/assets\/embed.js'><\/script><p id=\"Par1\" class=\"Para\" style=\"text-align: justify\"><strong class=\"EmphasisTypeBold \">We demonstrate how multidimensional scaling can be used to combine forest inventory field data and airborne laser scanner data to obtain both predictions and model-assisted estimation of a tree stem diameter distribution<\/strong>.<\/p>\n<p id=\"Par2\" class=\"Para\">\u2022 <em><strong class=\"EmphasisTypeBoldItalic \">Abstract<\/strong><\/em><\/p>\n<p id=\"Par6\" class=\"Para\" style=\"text-align: justify\">The size distribution of forest trees is important both for management planning and analysis purposes. Yet field samples are rarely large enough to assuage a desired accuracy of a direct estimation in all areas of interest. Improvements in spatial coverage and accuracy are possible with a census\u2014or a very large sample of one or more cost-effective auxiliary variables that can inform one about the tree size distribution<strong><em>. <\/em><\/strong>The objective of this study is to demonstrate how a relative frequency distribution of canopy heights from airborne laser scanner data can be used to improve direct estimates of a tree size distribution. Multidimensional scaling is used to link a relative frequency distribution of canopy heights to an observed plot-level distribution of tree size. A multivariate linear model can be used for both predictions and model-assisted estimation of a tree stem diameter distribution. Multidimensional scaling can provide a multivariate linear link between two relative frequency distributions and is therefore ideally suited for both stand-level predictions and design-based inference of tree size distributions.<\/p>\n<div class='altmetric-embed' data-badge-type='donut' data-doi='10.1007\/s13595-016-0581-2'  style='float: right; ' ><\/div>\n<p><span style=\"color: #ff6600\"><a style=\"color: #ff6600\" href=\"http:\/\/link.springer.com\/article\/10.1007\/s13595-016-0581-2\"><strong>Read the full paper <\/strong><\/a><\/span><\/p>\n<hr \/>\n<p><span style=\"color: #808000\"><strong>Publication<\/strong><\/span><\/p>\n<p>Magnussen S, Renaud J-P 2016. Multidimensional scaling of first-return airborne laser echoes for prediction and model-assisted estimation of a distribution of tree stem diameters. Ann. For. Sci.: 1-10. 10.1007\/s13595-016-0581-2.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>We demonstrate how multidimensional scaling can be used to combine forest inventory field data and airborne laser scanner data to obtain both predictions and model-assisted estimation of a tree stem diameter distribution. \u2022 Abstract The size distribution of forest trees is important both for management planning and analysis purposes. Yet field samples are rarely large [&hellip;]<\/p>\n","protected":false},"author":35,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[15],"tags":[],"class_list":["post-1953","post","type-post","status-publish","format-standard","hentry","category-research-paper","cat-15-id"],"_links":{"self":[{"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/posts\/1953","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\/35"}],"replies":[{"embeddable":true,"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/comments?post=1953"}],"version-history":[{"count":0,"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/posts\/1953\/revisions"}],"wp:attachment":[{"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/media?parent=1953"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/categories?post=1953"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/tags?post=1953"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}