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    <title>SyndicateMizzou Video Podcast</title>
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    <pubDate>Thu, 24 May 2012 07:02:32 GMT</pubDate>
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      <title>SyndicateMizzou Podcast:  Hong S.   He - Hong S. He’s research into landscape ecology</title>
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      <description>Hong S. He’s research projects in landscape ecology include Geographic Information Systems (GIS) and remote sensing applications (such as satellite imagery and aerial photography), both of which are put to work in making important forestry management decisions.</description>
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      <pubDate>Tue, 18 Sep 2007 20:04:15 GMT</pubDate>
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      <title>SyndicateMizzou Podcast:  Hong S.   He - The innovation of computerized landscape modeling work</title>
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      <description>A computer model called LANDIS addresses the larger spatial and temporal dimensions involved in effective forestry management, whether that means looking at the long-term effects of fire management or at tree harvesting practices.  In lieu of an ecological crystal ball, this computer model is becoming a crucial tool that employs current science “to simulate the long-term effects of various management decisions.” With LANDIS, it becomes possible to estimate how frequently a fire needs to occur in order to maintain the forest’s ecological health.</description>
      <duration>3</duration>
      <pubDate>Tue, 18 Sep 2007 20:04:37 GMT</pubDate>
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      <title>SyndicateMizzou Podcast:  Hong S.   He - Landscape modeling, continued </title>
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      <description>Computer modeling is an important tool used by landscape ecologists when they need to answer large-scale questions and consider several management scenarios such as suppressing fire or using prescribed fires, as well as the future impact of climate warming on certain species of trees.  LANDIS shows the predicted results of various management policies 50-100 years from now.  “Using some active management alternatives, hopefully we’ll end up with different, more desirable ecosystems,” says He.  </description>
      <duration>3</duration>
      <pubDate>Wed, 19 Sep 2007 13:57:40 GMT</pubDate>
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