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    <titleInfo>
      <title>Analysis of vegetation behavior in a North African semi-arid region, using SPOT-VEGETATION NDVI Data</title>
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    <name type="personnal">
      <namePart type="family">Zribi</namePart>
      <namePart type="given">Mehrez</namePart>
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    <name type="personnal">
      <namePart type="family">Lili-Chabaane</namePart>
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    <name type="personnal">
      <namePart type="family">Duchemin</namePart>
      <namePart type="given">Benoît</namePart>
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    <name type="personnal">
      <namePart type="family">Chehbouni</namePart>
      <namePart type="given">Abdelghani</namePart>
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    <abstract>The analysis of vegetation dynamics is essential in semi-arid regions, in particular because of the frequent occurrence of long periods of drought. In this paper, multi-temporal series of the Normalized Difference of Vegetation Index (NDVI), derived from SPOT-VEGETATION satellite data between September 1998 and June 2010, were used to analyze the vegetation dynamics over the semi-arid central region of Tunisia. A study of the persistence of three types of vegetation (pastures, annual agriculture and olive trees) is proposed using fractal analysis, in order to gain insight into the stability/instability of vegetation dynamics. In order to estimate the state of vegetation cover stress, we propose evaluating the properties of an index referred to as the Vegetation Anomaly Index (VAI). A positive VAI indicates high vegetation dynamics, whereas a negative VAI indicates the presence of vegetation stress. The VAI is tested for the above three types of vegetation, during the study period from 1998 to 2010, and is compared with other drought indices. The VAI is found to be strongly correlated with precipitation.</abstract>
    <targetAudience authority="marctarget">specialized</targetAudience>
    <subject>
      <topic>vegetation</topic>
      <topic>SPOT-VEGETATION</topic>
      <topic>NDVI index</topic>
      <topic>drought</topic>
      <topic>persistence</topic>
      <topic>Vegetation Drought Index</topic>
    </subject>
    <subject authority="local">
      <geographic>TUNISIE</geographic>
      <geographic>ZONE ARIDE</geographic>
    </subject>
    <classification authority="local">082</classification>
    <classification authority="local">126</classification>
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      <titleInfo>
        <title>Remote Sensing</title>
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      <part>
        <detail type="volume">
          <number>3</number>
        </detail>
        <detail type="volume">
          <number>12</number>
        </detail>
        <extent unit="pages">
          <list> 2568-2590</list>
        </extent>
      </part>
      <originInfo>
        <dateIssued>2011</dateIssued>
      </originInfo>
      <identifier type="issn">2072-4292</identifier>
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    <identifier type="uri">https://www.documentation.ird.fr/hor/fdi:010057126</identifier>
    <identifier type="doi">10.3390/rs3122568</identifier>
    <identifier type="issn">2072-4292</identifier>
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      <url access="row object">https://horizon.documentation.ird.fr/exl-doc/pleins_textes/divers17-09/010057126.pdf</url>
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        <languageTerm authority="iso639-2b">fre</languageTerm>
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