{"id":3325,"date":"2019-03-29T09:00:09","date_gmt":"2019-03-29T08:00:09","guid":{"rendered":"https:\/\/ist.blogs.inra.fr\/afs\/?p=3325"},"modified":"2019-03-27T11:39:42","modified_gmt":"2019-03-27T10:39:42","slug":"effect-of-permanent-plots-on-the-relative-efficiency-of-spatially-balanced-sampling-in-a-national-forest-inventory","status":"publish","type":"post","link":"https:\/\/ist.blogs.inrae.fr\/afs\/2019\/03\/29\/effect-of-permanent-plots-on-the-relative-efficiency-of-spatially-balanced-sampling-in-a-national-forest-inventory\/","title":{"rendered":"Effect of permanent plots on the relative efficiency of spatially balanced sampling in a national forest inventory"},"content":{"rendered":"<script type='text\/javascript' src='https:\/\/d1bxh8uas1mnw7.cloudfront.net\/assets\/embed.js'><\/script><p align=\"justify\"><a href=\"https:\/\/ist.blogs.inra.fr\/afs\/wp-content\/uploads\/sites\/5\/2019\/03\/Raty-Kangas.png\"><img loading=\"lazy\" decoding=\"async\" class=\" wp-image-3326 alignleft\" src=\"https:\/\/ist.blogs.inra.fr\/afs\/wp-content\/uploads\/sites\/5\/2019\/03\/Raty-Kangas-300x224.png\" alt=\"\" width=\"333\" height=\"249\" srcset=\"https:\/\/ist.blogs.inrae.fr\/afs\/wp-content\/uploads\/sites\/5\/2019\/03\/Raty-Kangas-300x224.png 300w, https:\/\/ist.blogs.inrae.fr\/afs\/wp-content\/uploads\/sites\/5\/2019\/03\/Raty-Kangas-768x573.png 768w, https:\/\/ist.blogs.inrae.fr\/afs\/wp-content\/uploads\/sites\/5\/2019\/03\/Raty-Kangas-1024x763.png 1024w, https:\/\/ist.blogs.inrae.fr\/afs\/wp-content\/uploads\/sites\/5\/2019\/03\/Raty-Kangas-640x477.png 640w, https:\/\/ist.blogs.inrae.fr\/afs\/wp-content\/uploads\/sites\/5\/2019\/03\/Raty-Kangas.png 1171w\" sizes=\"auto, (max-width: 333px) 100vw, 333px\" \/><\/a>Using spatially balanced sampling utilizing auxiliary information in the design phase can enhance the design efficiency of national forest inventory. These gains decreased with increasing proportion of permanent plots in the sample. Using semi-permanent plots, changing every <em>n<\/em>th inventory round, instead of permanent plots, reduced this phenomenon. Further studies for accounting the permanent sample when selecting temporary sample are needed.<\/p>\n<p align=\"justify\"><strong>Context<\/strong> National forest inventories (NFIs) produce national- and regional-level statistics for sustainability assessment and decision-making. Using an interpreted satellite image as auxiliary information in the design phase improved the relative efficiency (RE). Spatially balanced sampling through local pivotal method (LPM) used for selection of clusters of sample plots is designed for temporary sample; thus, the method was tested in a NFI design with both permanent and temporary clusters.<br \/>\n<strong>Aims<\/strong> We estimated LPM method and stratified sampling for a NFI designed for successive occasions, where the clusters are permanent, semi-permanent, or temporary being replaced: never, every <em>n<\/em>th, and every inventory round, respectively.<br \/>\n<strong>Methods<\/strong> REs of sampling designs against systematic sampling were studied with simulations of inventory sampling.<br \/>\n<strong>Results<\/strong> The larger the proportion of permanent clusters the smaller benefits gained with LPM. REs of stratified sampling were not depending on the proportion of permanent clusters. The semi-permanent sampling with LPM removed the previously described decrease and resulted in the largest REs.<br \/>\n<strong>Conclusion<\/strong> Sampling strategies with semi-permanent clusters were the most efficient, yet not necessarily optimal for all inventory variables. Further development of method to simultaneously take into account the distribution of permanent sample when selecting temporary or semi-temporary sample is desired since it could increase the design efficiency.<\/p>\n<p><strong>Keywords<\/strong><br \/>\nAuxiliary information, Local pivotal method, Permanent cluster, Relative efficiency, Sampling design, Semi-permanent cluster<\/p>\n<div class='altmetric-embed' data-badge-type='donut' data-doi='10.1007\/s13595-019-0802-6'  style='float: right; ' ><\/div>\n<p><strong>Open Access Publication<\/strong><br \/>\nR\u00e4ty, M. &amp; Kangas, A.S. Annals of Forest Science (2019) 76: 20. <a href=\"https:\/\/doi.org\/10.1007\/s13595-019-0802-6\">https:\/\/doi.org\/10.1007\/s13595-019-0802-6<\/a><\/p>\n<p align=\"justify\"><strong>Data availability<\/strong><br \/>\nThe datasets generated during and\/or analyzed during the current study are available from the corresponding author on reasonable request.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Using spatially balanced sampling utilizing auxiliary information in the design phase can enhance the design efficiency of national forest inventory. These gains decreased with increasing proportion of permanent plots in the sample. Using semi-permanent plots, changing every nth inventory round, instead of permanent plots, reduced this phenomenon. Further studies for accounting the permanent sample when [&hellip;]<\/p>\n","protected":false},"author":106,"featured_media":3326,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[14,109,15],"tags":[],"class_list":["post-3325","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-article-type","category-open-access","category-research-paper","cat-14-id","cat-109-id","cat-15-id","has_thumb"],"_links":{"self":[{"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/posts\/3325","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\/106"}],"replies":[{"embeddable":true,"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/comments?post=3325"}],"version-history":[{"count":0,"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/posts\/3325\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/media\/3326"}],"wp:attachment":[{"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/media?parent=3325"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/categories?post=3325"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/tags?post=3325"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}