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    <responseDate>2026-10-14T15:22:01Z</responseDate>
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    <identifier>10.57760/sciencedb.13287</identifier>
    <datestamp>2024-01-12T10:45:40Z</datestamp>
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  <dc:date>2024-01-12</dc:date>
  <dc:title>A global estimate of monthly vegetation and soil fractions from spatio-temporally adaptive spectral mixture analysis during 2001-2022</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.13287</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>This dataset is a&amp;nbsp;global estimate&amp;nbsp;of monthly vegetation and soil fractions using&amp;nbsp;spatio-temporally adaptive spectral mixture analysis from 2001-2011. The file is a compressed month-by-month GeoTIFF data for each year, according to the grid of longitude 60&amp;deg; and Latitude 50&amp;deg;. Since the dataset for each year includes 216 files, named as &amp;ldquo;SMA_year_(month-1)_gridid.tif&amp;rdquo;, like &amp;ldquo;SMA_2001_0_0.tif&amp;rdquo;.Bands (1-5) represent 'PV', 'NPV', 'BS', 'IS', and 'DA' respectively.The&amp;nbsp;dataset&amp;nbsp;can be also exported from GEE by our code or achieved by request from authors.Here is a schematic of global girds and id65N 2 5 8 11 14 1715N 1 4 7 10 13 1635S 0 3 6 9 12 15&amp;nbsp; 150W 90W 30W 30E 90E 150E</dc:description>
  <dc:subject>fractions; spectral mixture analysis; globe</dc:subject>
  <dc:creator>Qiangqiang Sun</dc:creator>
  <dc:creator>Danfeng Sun</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:relation>http://www.doi.org/https://doi.org/10.5194/essd-16-1333-2024</dc:relation>
  <dc:publisher>Science Data Bank</dc:publisher>
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