{"id":5283,"date":"2022-03-31T09:43:28","date_gmt":"2022-03-31T07:43:28","guid":{"rendered":"https:\/\/ist.blogs.inrae.fr\/afs\/?p=5283"},"modified":"2022-04-04T16:49:12","modified_gmt":"2022-04-04T14:49:12","slug":"potential-of-using-surface-temperature-data-to-benchmark-sentinel-2-based-forest-phenometrics-in-boreal-finland","status":"publish","type":"post","link":"https:\/\/ist.blogs.inrae.fr\/afs\/2022\/03\/31\/potential-of-using-surface-temperature-data-to-benchmark-sentinel-2-based-forest-phenometrics-in-boreal-finland\/","title":{"rendered":"Potential of using surface temperature data to benchmark Sentinel-2-based forest phenometrics in boreal Finland"},"content":{"rendered":"<script type='text\/javascript' src='https:\/\/d1bxh8uas1mnw7.cloudfront.net\/assets\/embed.js'><\/script><p><strong><a href=\"https:\/\/ist.blogs.inrae.fr\/afs\/wp-content\/uploads\/sites\/5\/2022\/03\/Majasalmi_2022.png\"><img loading=\"lazy\" decoding=\"async\" class=\"size-medium wp-image-5286 alignright\" src=\"https:\/\/ist.blogs.inrae.fr\/afs\/wp-content\/uploads\/sites\/5\/2022\/03\/Majasalmi_2022-300x300.png\" alt=\"\" width=\"300\" height=\"300\" srcset=\"https:\/\/ist.blogs.inrae.fr\/afs\/wp-content\/uploads\/sites\/5\/2022\/03\/Majasalmi_2022-300x300.png 300w, https:\/\/ist.blogs.inrae.fr\/afs\/wp-content\/uploads\/sites\/5\/2022\/03\/Majasalmi_2022-150x150.png 150w, https:\/\/ist.blogs.inrae.fr\/afs\/wp-content\/uploads\/sites\/5\/2022\/03\/Majasalmi_2022-50x50.png 50w, https:\/\/ist.blogs.inrae.fr\/afs\/wp-content\/uploads\/sites\/5\/2022\/03\/Majasalmi_2022-640x637.png 640w, https:\/\/ist.blogs.inrae.fr\/afs\/wp-content\/uploads\/sites\/5\/2022\/03\/Majasalmi_2022.png 876w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/a>Key message<\/strong><\/p>\n<p align=\"justify\">We present a new approach to calibrate timings of phenological events from satellite data (e.g., Sentinel-2 MSI data) with readily available surface temperature data. The new approach improves the estimation of growing season length in boreal forests.<\/p>\n<p><strong>Keywords<\/strong><\/p>\n<p align=\"justify\">Land surface phenology, LSP; Enhanced vegetation index, EVI; Temperature deviation integral, TDI<\/p>\n<div class='altmetric-embed' data-badge-type='donut' data-doi='10.1186\/s13595-022-01130-2'  style='float: right; ' ><\/div>\n<p><strong>Publication<\/strong><br \/>\nMajasalmi T., Rautiainen M. Potential of using surface temperature data to benchmark Sentinel-2-based forest phenometrics in boreal Finland. Annals of Forest Science 79, 6 (2022). <a href=\"https:\/\/annforsci.biomedcentral.com\/articles\/10.1186\/s13595-022-01130-2\">https:\/\/doi.org\/10.1186\/s13595-022-01130-2<\/a><\/p>\n<p><strong>Data and\/or Code availability<\/strong><br \/>\nAll data is publicly available (See reference list). The datasets generated during the current study are available from the corresponding author on reasonable request.<\/p>\n<p><strong>Handling Editor<\/strong><br \/>\nBarry A. Gardiner<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Key message We present a new approach to calibrate timings of phenological events from satellite data (e.g., Sentinel-2 MSI data) with readily available surface temperature data. The new approach improves the estimation of growing season length in boreal forests. Keywords Land surface phenology, LSP; Enhanced vegetation index, EVI; Temperature deviation integral, TDI Publication Majasalmi T., [&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-5283","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\/5283","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=5283"}],"version-history":[{"count":5,"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/posts\/5283\/revisions"}],"predecessor-version":[{"id":5306,"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/posts\/5283\/revisions\/5306"}],"wp:attachment":[{"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/media?parent=5283"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/categories?post=5283"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/tags?post=5283"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}