anchor.diff:          <div class='source_table'>
             <dl class='sources_row'>
               <dt>Function</dt>
  -            <dd>Identifies areas of tree cover loss and gain</dd>
  +            <dd>Identifies areas of tree cover loss</dd>
             </dl>
             <dl class='sources_row even'>
               <dt>Resolution/scale</dt>
  
positive.code: 
      <li id='umd_tree_loss_gain' class='source-item first'>
        <div class='source_header'>
          <strong class='source_title'>University of Maryland/Google tree cover loss &amp; gain</strong>
          <i class='expand_arrow'></i>
          <em class='source_description'>(annual &amp; 12 years, 30m, global)</em>
        </div>
  
negative.code:           </dl>
            <dl class='sources_row'>
              <dt>Frequency of updates</dt>
              <dd>Annual</dd>
            </dl>
            <dl class='sources_row even'>
              <dt>Date of content</dt>
              <dd>January 2000–2012</dd>
            </dl>
            <dl class='sources_row'>
              <dt>Tree cover canopy density</dt>
              <dd>VARIES ACCORDING TO SELECTION (CLICK THE GEAR ICON ON THE MAP TO CHANGE THE MINIMUM TREE COVER CANOPY DENSITY THRESHOLD)</dd>
            </dl>
            <dl class='sources_row even'>
              <dt>Cautions</dt>
              <dd>
                <p>For the purpose of this study, “tree cover” was defined as all vegetation taller than 5 meters in height. “Tree cover” is the biophysical presence of trees and may take the form of natural forests or plantations existing over a range of canopy densities. “Loss” indicates the removal or mortality of tree canopy cover and can be due to a variety of factors, including mechanical harvesting, fire, disease, or storm damage. As such, “loss” does not equate to deforestation.</p>
  
                <p>When zoomed out (< zoom level 13), pixels of loss are shaded according to the density of loss at the 30 x 30 meter scale. Pixels with darker shading represent areas with a higher concentration of tree cover loss, whereas pixels with lighter shading indicate a lower concentration of tree cover loss. There is no variation in pixel shading when the data is at full resolution (≥ zoom level 13).</p>
              </dd>
            </dl>
          </div>
  
          <div class='source_summary'>
            <h3 class='overview_title'>Overview</h3>
            <p>This data set measures areas of tree cover loss across all global land (except Antarctica and other Arctic islands) annually at 30 × 30 meter resolution. The data were generated using multispectral satellite imagery from the <a href='http://landsat.usgs.gov/science_L7_cpf.php' target='_blank'>Landsat 7 thematic mapper plus (ETM+)</a> sensor. Over 600,000 Landsat 7 images were compiled and analyzed using Google Earth Engine, a cloud platform for earth observation and data analysis. The clear land surface observations (30 × 30 meter pixels) in the satellite images were assembled chronologically and a supervised learning algorithm was then applied to identify per pixel tree cover loss or gain.</p>
  
  
  
            <p>Tree cover loss is defined as “stand replacement disturbance,” or the complete removal of tree cover canopy at the Landsat pixel scale. Tree cover loss may indicate a number of potential activities, such as timber harvesting, fires or disease, the conversion of natural forest to other land uses, or the crop rotations cycle of tree plantations. </p>
  
            <p class='credits'><strong>Citation:</strong> Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, and J. R. G. Townshend. 2013. “High-Resolution Global Maps of 21st-Century Forest Cover Change.” Science 342 (15 November): 850–53.</p>
  
            <p class='credits'><strong>Suggested citations for data as displayed on GFW:</strong> Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, and J. R. G. Townshend. 2013. “Hansen/UMD/Google/USGS/NASA Tree Cover Loss and Gain Area.” University of Maryland, Google, USGS, and NASA. Accessed through Global Forest Watch on  [date]. <a href='http://www.globalforestwatch.org' target='_blank'>www.globalforestwatch.org</a>.</p>
  
            <p class='read_more hidden'><em><%= link_to 'Learn more or download data', sources_path %></em></p>
          </div>
        </div>
      </li>
      
      
      
      
       <li id='forestgain' class='source-item '>
        <div class='source_header'>
          <strong class='source_title'>University of Maryland/Google tree cover gain</strong>
          <i class='expand_arrow'></i>
          <em class='source_description'>(annual &amp; 12 years, 30m, global)</em>
        </div>
  
        <div class='source_body'>
          <div class='source_download'>
            <a href='http://www.earthenginepartners.appspot.com/science-2013-global-forest/download.html' target='_blank' title='Download at project website'>Download at project website<i class='arrow_down'></i></a>
          </div>
  
          <div class='source_table'>
            <dl class='sources_row'>
              <dt>Function</dt>
              <dd>Identifies areas of tree cover gain</dd>
            </dl>
            <dl class='sources_row even'>
              <dt>Resolution/scale</dt>
              <dd>30 × 30 meters</dd>
            </dl>
            <dl class='sources_row'>
              <dt>Geographic coverage</dt>
              <dd>Global land area (excluding Antarctica and other Arctic islands)</dd>
            </dl>
            <dl class='sources_row even'>
              <dt>Source data</dt>
              <dd><a href='http://landsat.usgs.gov/' target='_blank'>Landsat 7 ETM+</a></dd>
            </dl>
            <dl class='sources_row'>
              <dt>Frequency of updates</dt>
              <dd>12-year cumulative, updated annually</dd>
            </dl>
            <dl class='sources_row even'>
              <dt>Date of content</dt>
              <dd>January 2000–2012</dd>
            </dl>
            <dl class='sources_row'>
              <dt>Tree cover canopy density</dt>
              <dd>>50%</dd>
            </dl>
            <dl class='sources_row even'>
              <dt>Cautions</dt>
              <dd>
                <p>For the purpose of this study, “tree cover” was defined as all vegetation taller than 5 meters in height. “Tree cover” is the biophysical presence of trees and may take the form of natural forests or plantations existing over a range of canopy densities. “Loss” indicates the removal or mortality of tree canopy cover and can be due to a variety of factors, including mechanical harvesting, fire, disease, or storm damage. As such, “loss” does not equate to deforestation.</p>
  
                <p>When zoomed out (< zoom level 13), pixels of gain are shaded according to the density of gain at the 30 x 30 meter scale. Pixels with darker shading represent areas with a higher concentration of tree cover gain, whereas pixels with lighter shading indicate a lower concentration of tree cover gain. There is no variation in pixel shading when the data is at full resolution (≥ zoom level 13).</p>
              </dd>
            </dl>
          </div>
  
          <div class='source_summary'>
            <h3 class='overview_title'>Overview</h3>
            <p>This data set measures areas of tree cover gain across all global land (except Antarctica and other Arctic islands) at 30 × 30 meter resolution, displayed as a 12-year cumulative layer. The data were generated using multispectral satellite imagery from the <a href='http://landsat.usgs.gov/science_L7_cpf.php' target='_blank'>Landsat 7 thematic mapper plus (ETM+)</a> sensor. Over 600,000 Landsat 7 images were compiled and analyzed using Google Earth Engine, a cloud platform for earth observation and data analysis. The clear land surface observations (30 × 30 meter pixels) in the satellite images were assembled and a supervised learning algorithm was then applied to identify per pixel tree cover gain..</p>
            
  
  
            <p>Tree cover gain was defined as the establishment of tree canopy at the Landsat pixel scale in an area that previously had no tree cover. Tree cover gain may indicate a number of potential activities, including natural forest growth or the crop rotation cycle of tree plantations. </p>
  
            <p class='credits'><strong>Citation:</strong> Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, and J. R. G. Townshend. 2013. “High-Resolution Global Maps of 21st-Century Forest Cover Change.” Science 342 (15 November): 850–53.</p>
  
            <p class='credits'><strong>Suggested citations for data as displayed on GFW:</strong> Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, and J. R. G. Townshend. 2013. “Hansen/UMD/Google/USGS/NASA Tree Cover Loss and Gain Area.” University of Maryland, Google, USGS, and NASA. Accessed through Global Forest Watch on  [date]. <a href='http://www.globalforestwatch.org' target='_blank'>www.globalforestwatch.org</a>.</p>
  
            <p class='read_more hidden'><em><%= link_to 'Learn more or download data', sources_path %></em></p>
          </div>
  