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    <identifier>10.57760/sciencedb.06122</identifier>
    <datestamp>2022-11-02T09:19:32Z</datestamp>
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  <dc:date>2022-11-02</dc:date>
  <dc:title>Unmanned aerial vehicle imagery on desert grassland</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.06122</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>We acquired an aerial image dataset for April 2021. The quadrotor M300 RTK UAV (DJI-Innovations, Shenzhen, China) was selected as the data acquisition platform. To satisfy the aerial photography requirement, the forward and side overlaps were set to 70% and 80%, respectively. Each image was 5280 &amp;times; 3956 pixels in size and comprised three bands in the RGB domains, with a radiometric resolution of 24 bits.Features exported from eCognition Developer 64&amp;nbsp;and python code for features selection are provided.</dc:description>
  <dc:subject>Effective gerbil holes; Object-based classification; UAV imagery</dc:subject>
  <dc:creator>Guimei Qi</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
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  <dc:type>dataset</dc:type>
  <dc:publisher>Science Data Bank</dc:publisher>
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