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      <source-app name="Horizon">Horizon</source-app>
      <rec-number>1</rec-number>
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        <key app="Horizon" db-id="fdi:010074140">1</key>
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      <ref-type name="Journal Article">17</ref-type>
      <work-type>ACL : Articles dans des revues avec comité de lecture répertoriées par l'AERES</work-type>
      <contributors>
        <authors>
          <author>
            <style face="normal" font="default" size="100%">Aires, F.</style>
          </author>
          <author>
            <style face="normal" font="default" size="100%">Prigent, C.</style>
          </author>
          <author>
            <style face="normal" font="default" size="100%">Fluet-Chouinard, E.</style>
          </author>
          <author>
            <style face="normal" font="default" size="100%">Yamazaki, D.</style>
          </author>
          <author>
            <style face="bold" font="default" size="100%">Papa, Fabrice</style>
          </author>
          <author>
            <style face="normal" font="default" size="100%">Lehner, B.</style>
          </author>
        </authors>
      </contributors>
      <titles>
        <title>Comparison of visible and multi-satellite global inundation datasets at high-spatial resolution</title>
        <secondary-title>Remote Sensing of Environment</secondary-title>
      </titles>
      <pages>427-441</pages>
      <keywords>
        <keyword>Wetlands and Inundation</keyword>
        <keyword>Remote sensing</keyword>
        <keyword>Landsat</keyword>
        <keyword>Passive microwaves</keyword>
      </keywords>
      <dates>
        <year>2018</year>
      </dates>
      <call-num>fdi:010074140</call-num>
      <language>ENG</language>
      <periodical>
        <full-title>Remote Sensing of Environment</full-title>
      </periodical>
      <isbn>0034-4257</isbn>
      <accession-num>ISI:000445990100030</accession-num>
      <electronic-resource-num>10.1016/j.rse.2018.06.015</electronic-resource-num>
      <urls>
        <related-urls>
          <url>https://www.documentation.ird.fr/hor/fdi:010074140</url>
        </related-urls>
        <pdf-urls>
          <url>https://www.documentation.ird.fr/intranet/publi/2018/10/010074140.pdf</url>
        </pdf-urls>
      </urls>
      <volume>216</volume>
      <remote-database-provider>Horizon (IRD)</remote-database-provider>
      <abstract>Several new satellite-derived and long-term surface water datasets at high-spatial resolution have recently become available at the global scale, showing different characteristics and abilities. They are either based on visible imagery from Landsat - the Global 3-second Water Body Map (G3WBM) and the Global Surface Water Explorer (GSWE) - or on the merging of passive/active microwave and visible observations - Global Inundation Extent from Multi-Satellite (GIEMS-D3) - that has been downscaled from a native resolution of 25 km x 25 km to the 90 m x 90 m resolution. The objective of this paper is to perform a thorough comparison of the different water surface estimates in order to identify the advantages and disadvantages of the two approaches and propose a strategy for future developments of high-resolution surface water databases. Results show that due to their very high spatial resolution (30 m) the Landsat-based datasets are well suited to retrieve open water surfaces, even at very small size. GIEMS-D3 has a better ability to detect water under vegetation and during the cloudy season, and it shows larger seasonal dynamics. However, its current version overestimates surface water extent on water-saturated soils, and due to its low original (i.e. before downscaling) spatial resolution, it is under-performing at detecting small water bodies. The permanent waters for G3WBM, GSWE, GIEMS-D3 and GLWD represent respectively: 2.76, 2.05, 3.28, and 3.04 million km(2). The transitory waters shows larger discrepancies: 0.48, 3.72, 10.39 and 8.81 million km(2). Synthetic Aperture Radar (SAR) data (from ENVIronment SATellite (ENVISAT), Sentinel and soon the Surface Water Ocean Topography (SWOT)) would be a good complementary information because they have a high nominal spatial resolution and are less sensitive to clouds than visible measurements. However, global SAR datasets are still not available due to difficulties in developing a retrieval scheme adequate at the global scale. In order to improve our estimates of global wetland extents at high resolution and over long-term records, three interim lines of action are proposed: (1) extend the temporal record of GIEMS-D3 to exploit the full time series of microwave observations (from 1978 to present), (2) develop an approach to fuse the GSWE and GIEMS-D3 datasets leveraging the strengths of both, and (3) prepare for the release of SAR global datasets.</abstract>
      <custom6>126 ; 062</custom6>
      <custom1>UR065</custom1>
      <custom7>Inde</custom7>
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