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    <titleInfo>
      <title>Assessing the SMOS soil moisture retrieval parameters with high-resolution NAFE'06 data</title>
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      <namePart type="family">Merlin</namePart>
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    <name type="personnal">
      <namePart type="family">Escorihuela</namePart>
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    <name type="personnal">
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    <abstract>The spatial and temporal invariance of Soil Moisture and Ocean Salinity (SMOS) forward model parameters for soil moisture retrieval was assessed at 1-km resolution on a diurnal basis with data from the National Airborne Field Experiment 2006. The approach used was to apply the SMOS default parameters uniformly over 27 1-km validation pixels, retrieve soil moisture from the airborne observations, and then to interpret the differences between airborne and ground estimates in terms of land use, parameter variability, and sensing depth. For pastures ( 17 pixels) and nonirrigated crops ( 5 pixels), the root mean square error (rmse) was 0.03 volumetric (vol./vol.) soil moisture with a bias of 0.004 vol./vol. For pixels dominated by irrigated crops ( 5 pixels), the rmse was 0.10 vol./vol., and the bias was -0.09 vol./vol. The correlation coefficient between bias in irrigated areas and the 1-km field soil moisture variability was found to be 0.73, which suggests either 1) an increase of the soil dielectric roughness ( up to about one) associated with small-scale heterogeneity of soil moisture or/and 2) a difference in sensing depth between an L-band radiometer and the in situ measurements, combined with a strong vertical gradient of soil moisture in the top 6 cm of the soil.</abstract>
    <targetAudience authority="marctarget">specialized</targetAudience>
    <subject>
      <topic>Airborne experiment</topic>
      <topic>calibration</topic>
      <topic>L-band radiometry</topic>
      <topic>National Airborne</topic>
      <topic>Field Experiment (NAFE)</topic>
      <topic>retrieval algorithm</topic>
      <topic>soil moisture</topic>
      <topic>Soil</topic>
      <topic>Moisture and Ocean Salinity (SMOS)</topic>
    </subject>
    <classification authority="local">126</classification>
    <classification authority="local">032</classification>
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      <titleInfo>
        <title>IEEE Geoscience and Remote Sensing Letters</title>
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      <part>
        <detail type="volume">
          <number>6</number>
        </detail>
        <detail type="volume">
          <number>4</number>
        </detail>
        <extent unit="pages">
          <list> 635-639</list>
        </extent>
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      <originInfo>
        <dateIssued>2009</dateIssued>
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      <identifier type="issn">1545-598X</identifier>
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    <identifier type="uri">https://www.documentation.ird.fr/hor/PAR00004279</identifier>
    <identifier type="doi">10.1109/lgrs.2009.2012727</identifier>
    <identifier type="issn">1545-598X</identifier>
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      <recordCreationDate encoding="w3cdtf">2009-12-03</recordCreationDate>
      <recordChangeDate encoding="w3cdtf">2017-08-23</recordChangeDate>
      <recordIdentifier>PAR00004279</recordIdentifier>
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