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            </mdq:DQ_ConformanceResult>
          </mdq:result>
        </mdq:DQ_DomainConsistency>
      </mdq:report>
      <mdq:report>
        <mdq:DQ_DomainConsistency>
          <mdq:result>
            <mdq:DQ_ConformanceResult>
              <mdq:specification>
                <cit:CI_Citation>
                  <cit:title>
                    <gcx:Anchor xlink:href="">INSPIRE Data Specification on orthoimagery - Guidelines</gcx:Anchor>
                  </cit:title>
                  <cit:date>
                    <cit:CI_Date>
                      <cit:date>
                        <gco:Date>2010-04-26</gco:Date>
                      </cit:date>
                      <cit:dateType>
                        <cit:CI_DateTypeCode codeList="http://standards.iso.org/iso/19115/resources/Codelists/cat/codelists.xml#CI_DateTypeCode" codeListValue="publication" />
                      </cit:dateType>
                    </cit:CI_Date>
                  </cit:date>
                </cit:CI_Citation>
              </mdq:specification>
              <mdq:explanation>
                <gco:CharacterString>See the referenced specification</gco:CharacterString>
              </mdq:explanation>
              <mdq:pass>
                <gco:Boolean>true</gco:Boolean>
              </mdq:pass>
            </mdq:DQ_ConformanceResult>
          </mdq:result>
        </mdq:DQ_DomainConsistency>
      </mdq:report>
    </mdq:DQ_DataQuality>
  </mdb:dataQualityInfo>
  <mdb:resourceLineage>
    <mrl:LI_Lineage>
      <mrl:statement>
        <gco:CharacterString>The SWI algorithm, originally developed at Vienna University of Technology (TU Wien) and later improved by other research groups, uses an infiltration model describing the relation between surface soil moisture and profile soil moisture as a function of time. The algorithm is based on a two-layer water balance model to estimate profile soil moisture from SSM retrieved from scatterometer data. The remotely sensed topsoil represents the first layerand the second layer extends downwards from the bottom of the surface layer. In this model, the water content of the reservoir layer is described in terms of an Index, which is controlled only by the past soil moisture conditions in the surface layer in a way that the influence of measurements decreases by increasing the time. The SWI processing algorithm uses near-real-time ASCAT-25km SSM product as input to generate daily global SWI images. Therefore a computational adaption of SWI algorithm has been made based on a recursive formulation. In this method, a gain factor is introduced that relates the past SWI measurements to the current measurements. SWI images are calculated for eight different T values (1, 5, 10, 15, 20, 40, 60, 100) together with the respective quality flags. The SWI quality flag is a parameter related to the number of available SSM measurements used for calculation of SWIT at time t. It is calculated also by using a recursive formulation and expressed in percentage after normalization.</gco:CharacterString>
      </mrl:statement>
      <mrl:scope>
        <mcc:MD_Scope>
          <mcc:level>
            <mcc:MD_ScopeCode codeList="http://standards.iso.org/iso/19115/resources/Codelists/cat/codelists.xml#MD_ScopeCode" codeListValue="dataset" />
          </mcc:level>
        </mcc:MD_Scope>
      </mrl:scope>
    </mrl:LI_Lineage>
  </mdb:resourceLineage>
  <mdb:metadataMaintenance>
    <mmi:MD_MaintenanceInformation>
      <mmi:maintenanceAndUpdateFrequency>
        <mmi:MD_MaintenanceFrequencyCode codeList="http://standards.iso.org/iso/19115/resources/Codelists/cat/codelists.xml#MD_MaintenanceFrequencyCode" codeListValue="asNeeded" />
      </mmi:maintenanceAndUpdateFrequency>
    </mmi:MD_MaintenanceInformation>
  </mdb:metadataMaintenance>
</mdb:MD_Metadata>

