Poster Open Access

Semi-supervised Sentinel-2 tree species detection

Vermeer, Martijn; Sørensen, Tord K.; Völgyes, David; Fantin, Daniele; Miller, Heidrun

MARC21 XML Export

<?xml version='1.0' encoding='UTF-8'?>
<record xmlns="">
  <datafield tag="041" ind1=" " ind2=" ">
    <subfield code="a">eng</subfield>
  <controlfield tag="005">20220520014929.0</controlfield>
  <controlfield tag="001">6563721</controlfield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="u">Science and Technology AS</subfield>
    <subfield code="0">(orcid)0000-0002-5879-3969</subfield>
    <subfield code="a">Sørensen, Tord K.</subfield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="u">Science and Technology AS</subfield>
    <subfield code="0">(orcid)0000-0001-9723-5532</subfield>
    <subfield code="a">Völgyes, David</subfield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="u">Science and Technology AS</subfield>
    <subfield code="0">(orcid)0000-0002-5339-0239</subfield>
    <subfield code="a">Fantin, Daniele</subfield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="u">Allskog SA</subfield>
    <subfield code="0">(orcid)0000-0002-1637-9719</subfield>
    <subfield code="a">Miller, Heidrun</subfield>
  <datafield tag="856" ind1="4" ind2=" ">
    <subfield code="s">13362140</subfield>
    <subfield code="z">md5:4ecfd680f20216fca4497962ac501462</subfield>
    <subfield code="u"></subfield>
  <datafield tag="542" ind1=" " ind2=" ">
    <subfield code="l">open</subfield>
  <datafield tag="260" ind1=" " ind2=" ">
    <subfield code="c">2022-05-19</subfield>
  <datafield tag="909" ind1="C" ind2="O">
    <subfield code="p">openaire</subfield>
    <subfield code="o"></subfield>
  <datafield tag="100" ind1=" " ind2=" ">
    <subfield code="u">Science and Technology AS</subfield>
    <subfield code="0">(orcid)0000-0002-2777-6584</subfield>
    <subfield code="a">Vermeer, Martijn</subfield>
  <datafield tag="245" ind1=" " ind2=" ">
    <subfield code="a">Semi-supervised Sentinel-2 tree species detection</subfield>
  <datafield tag="540" ind1=" " ind2=" ">
    <subfield code="u"></subfield>
    <subfield code="a">Creative Commons Attribution 4.0 International</subfield>
  <datafield tag="650" ind1="1" ind2="7">
    <subfield code="a">cc-by</subfield>
    <subfield code="2"></subfield>
  <datafield tag="520" ind1=" " ind2=" ">
    <subfield code="a">&lt;p&gt;For forest management the availability of complete and up-to-date forest inventories is essential, with one of the most important parameters&amp;nbsp;being the volumetric tree species distribution. Unfortunately, tree species mapping in Norwegian&amp;nbsp;production forests is a time-consuming and largely&amp;nbsp;manual process, leading to forest inventories that&amp;nbsp;are often incomplete and/or outdated. Indeed, the&amp;nbsp;determination of the tree species distribution is&amp;nbsp;currently performed by a forestry expert, mainly&lt;br&gt;
by visual interpretation of aerial imagery and in&amp;nbsp;some cases lidar data. High resolution aerial imagery is available, however&amp;nbsp; campaigns are expensive and therefore infrequent. Satellite imagery, on&amp;nbsp;the other hand, provides dense time series, but has&amp;nbsp;a much lower resolution. The primary goal of the&amp;nbsp;SENTREE project is to automate the classification&amp;nbsp;of Norwegian main production tree species (Norway spruce, Scots pine and Birch) using semantic&amp;nbsp;segmentation networks on a fusion of aerial and&amp;nbsp;satellite data sources.&lt;/p&gt;</subfield>
  <datafield tag="773" ind1=" " ind2=" ">
    <subfield code="n">doi</subfield>
    <subfield code="i">isVersionOf</subfield>
    <subfield code="a">10.5281/zenodo.6563720</subfield>
  <datafield tag="024" ind1=" " ind2=" ">
    <subfield code="a">10.5281/zenodo.6563721</subfield>
    <subfield code="2">doi</subfield>
  <datafield tag="980" ind1=" " ind2=" ">
    <subfield code="a">poster</subfield>
All versions This version
Views 5252
Downloads 5151
Data volume 681.5 MB681.5 MB
Unique views 4848
Unique downloads 4141


Cite as