August 19, 2022 Software Open Access

Scarth, Peter; Denham, Robert; Watson, Fiona

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  <dc:creator>Scarth,  Peter</dc:creator>
  <dc:creator>Denham, Robert</dc:creator>
  <dc:creator>Watson, Fiona</dc:creator>
  <dc:date>2022-08-19</dc:date>
  <dc:description>The fractional cover v3.0 model is a Multi Layer Perceptron (neural network) model architecture that uses surface reflectance to estimate the three cover fractions of bare ground, photosynthetic vegetation (PV) and non-photosynthetic vegetation (NPV). The MLP model was trained with Tensorflow using Landsat TM, ETM+ and OLI surface reflectance and a collection of 4000 field observations of overstorey and ground cover. The field observations covered a wide variety of vegetation, soil and climate types across Australia, collected between 1997 and 2018.</dc:description>
  <dc:identifier>https://zenodo.org/record/7008343</dc:identifier>
  <dc:identifier>10.5281/zenodo.7008343</dc:identifier>
  <dc:identifier>oai:zenodo.org:7008343</dc:identifier>
  <dc:language>eng</dc:language>
  <dc:relation>doi:10.5281/zenodo.7008342</dc:relation>
  <dc:relation>url:https://zenodo.org/communities/remote-sensing</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>https://opensource.org/licenses/MIT</dc:rights>
  <dc:subject>remote sensing</dc:subject>
  <dc:title>JRSRP Fractional cover v3</dc:title>
  <dc:type>info:eu-repo/semantics/other</dc:type>
  <dc:type>software</dc:type>
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