The Standardized Vegetation Optical Depth Index SVODI

<p><strong>Related paper with detailed description: </strong><a href="https://doi.org/10.5194/bg-19-5107-2022">https://doi.org/10.5194/bg-19-5107-2022</a></p> <p><strong>Short summary:</strong> The Standardized Vegetation Optical Depth index (SVODI) can be used to monitor the vegetation condition, such as whether the vegetation is unusually dry or wet. SVODI has global coverage and spans the past three decades and is derived from multiple space-borne passive microwave sensors of that period. SVODI is based on a new probabilistic merging method that allows the merging of normally distributed data, even if the data is not gap-free.</p> <p><strong>Files: </strong></p> <ul> <li>&quot;SVODI_v01.zip&quot; <ul> <li>Contains the bulk SVODI data, globally, from 1987-07-10 to&nbsp; 2019-12-31. Files are daily global netcdf images, with a 0.25 degree spatial resolution. Is unzipped roughly the same size.</li> </ul> </li> <li>&quot;svodi_v01_0_2006-06-26.nc&quot; <ul> <li>An arbitrary file from SVODI_V01.zip. For your convenience in case you want to see an example first without downloading the whole thing.</li> </ul> </li> <li>&quot;ESA-CCI-SOILMOISTURE-LAND_AND_RAINFOREST_MASK-fv04.2.nc&quot; <ul> <li>Grid of SVODI, Source: https://github.com/TUW-GEO/smecv-grid</li> </ul> </li> </ul> <p><strong>Data fields:</strong></p> <ul> <li>&quot;svodi&quot; <ul> <li>The standardized vegetation optical depth index</li> <li>unitless</li> <li>range: -inf, inf</li> </ul> </li> <li>&quot;flag&quot; <ul> <li>Bit-flag indicating which &lt;sensor&gt;-&lt;band&gt; combination contributed to each observation <ul> <li>1: AMSRE-C</li> <li>2:&nbsp;AMSR2-C</li> <li>3: WindSat-C</li> <li>4: AMSRE-X</li> <li>5: AMSR2-X</li> <li>6: WindSat-X</li> <li>7: TMI-X</li> <li>8: AMSRE-Ku</li> <li>9: AMSR2-Ku</li> <li>10: WindSat-Ku</li> <li>11: TMI-Ku</li> <li>12: SSMI-Ku</li> </ul> </li> </ul> </li> </ul>