anchor.diff:          </div>
         </div>
       </li>
  -    <li id='ifl_2013_deg' class='source-item'>
  -      <div class='source_header'>
  -        <strong class='source_title'>Intact Forest Landscapes 2000/2013</strong>
  -        <i class='expand_arrow'></i>
  -        <em class='source_description'>(2000/2013)</em>
  -      </div>
  -
  -      <div class='source_body'>
  -        <div class='source_table'>
  -          <dl class='sources_row'>
  -            <dt>Function</dt>
  -            <dd>Identifies the world’s last remaining unfragmented forest landscapes, large enough to retain all native biodiversity andshowing no signs of human alteration as of the year 2013. This layer also shows the reduction in the extent of Intact Forest Lanscapes from 2000 to 2013.</dd>
  -          </dl>
  -          <dl class='sources_row even'>
  -            <dt>RESOLUTION / SCALE</dt>
  -            <dd>Approximately 1:1,000,000</dd>
  -          </dl>
  -          <dl class='sources_row'>
  -            <dt>Geographic coverage</dt>
  -            <dd>Global</dd>
  -          </dl>
  -          <dl class='sources_row even'>
  -            <dt>Source data</dt>
  -            <dd><a href='http://landsat.usgs.gov/' target='_blank'>Landsat TM/ETM+/OLI</a></dd>
  -          </dl>
  -          <dl class='sources_row'>
  -            <dt>Frequency of updates</dt>
  -            <dd>2015 update; 2008 original publication</dd>
  -          </dl>
  -          <dl class='sources_row even'>
  -            <dt>Date of content</dt>
  -            <dd>2013</dd>
  -          </dl>
  -          <dl class='sources_row'>
  -            <dt>Cautions</dt>
  -            <dd>The world IFL map was created through visual interpretation of Landsat images by experts. The map may contain inaccuracies due to limitations in the spatial resolution of the imagery and lack of ancillary information about local land-use practices in some regions. In addition, the methodology assumes that fires in proximity to roads or other infrastructure may have been caused by humans, and therefore constitute a form of anthropogenic disturbance. This assumption could result in an underestimation of IFL extent in the boreal biome.</dd>
  -          </dl>
  -        </div>
  -
  -        <div class='source_summary'>
  -          <h3 class='overview_title'>Overview</h3>
  -          <p>The <a href='http://intactforests.org/' target='_blank'>Intact Forest Landscapes</a> (IFL) data set identifies unbroken expanses of natural ecosystems within the zone of forest extent that show no signs of significant human activity and are large enough that all native biodiversity, including viable populations of wide-ranging species, could be maintained. To map IFL areas, a set of criteria was developed and designed to be globally applicable and easily replicable, the latter to allow for repeated assessments over time as well as verification. IFL areas were defined as unfragmented landscapes, at least 50,000 hectares in size, and with a minimum width of 10 kilometers. IFL areas were defined as unfragmented landscapes, at least 50,000 hectares in size, and with a minimum width of 10 kilometers. These were then mapped from Landsat imagery for the years 2000 and 2013.</p>
  -
  -          <p>Changes in the extent of IFLs were identified within year 2000 IFL boundary using the global wall-to-wall Landsat image composite for year 2013 and the global forest cover loss dataset (Hansen et al., 2013). Areas identified as “reduction in extent” met the IFL criteria in 2000, but no longer met the criteria in 2013. The main causes of change were clearing for agriculture and tree plantations, industrial activity such as logging and mining, fragmentation due to infrastructure and new roads, and fires assumed to be caused by humans.</p>
  -
  -          <p>This data can be used to assess forest intactness, alteration, and degradation at global and regional scales. More information about the data set and methodology is available on  <a href="http://www.intactforests.org">www.intactforests.org</a></p>
  -
  -          <p class='credits'><strong>Citation:</strong> Potapov, P., A. Yaroshenko, S. Turubanova, M. Dubinin, L. Laestadius, C. Thies, D. Aksenov, A. Egorov, Y. Yesipova, I. Glushkov, M. Karpachevski, A. Kostickova, A. Manisha, E. Tsybikova, and I. Zhuravleva. 2008. “Mapping the World’s Intact Forest Landscapes by Remote Sensing.” Ecology and Society 13, no. 2: Art. 51. www.ecologyandsociety.org/vol13/iss2/art51.</p>
  -
  -          <p class='credits'><strong>Suggested citation for users:</strong> Greenpeace, University of Maryland, World Resources Institute and Transparent World. “Intact Forest Landscapes. 2000/2013” Accessed through Global Forest Watch on [date]. www.globalforestwatch.org</p>
  -
  -          <p class='read_more hidden'><em><a href="http://data.globalforestwatch.org/datasets?q=intact+forest+landscapes&sort_by=relevance" target="_blank">Learn more or download data</a></em></p>
  -        </div>
  -      </div>
  -    </li>
  -    <li id='plantations' class='source-item'>
  -      <div class='source_header'>
  -        <strong class='source_title'>Tree Plantations</strong>
  -        <i class='expand_arrow'></i>
  -      </div>
  -
  -      <div class='source_body'>
  -        <div class='source_table'>
  -          <dl class='sources_row'>
  -            <dt>Function</dt>
  -            <dd>Shows the coverage of plantations in select countries</dd>
  -          </dl>
  -          <dl class='sources_row even'>
  -            <dt>RESOLUTION / SCALE</dt>
  -            <dd>Based on 30 × 30 meter data. Scale varies by country.</dd>
  -          </dl>
  -          <dl class='sources_row'>
  -            <dt>Geographic coverage</dt>
  -            <dd>Currently available for Brazil, Cambodia, Colombia, Indonesia, Liberia, Malaysia, and Peru</dd>
  -          </dl>
  -          <dl class='sources_row even'>
  -            <dt>Source data</dt>
  -            <dd><a href="http://www.transparentworld.ru/en/" target="_blank">Transparent World</a></dd>
  -          </dl>
  -          <dl class='sources_row'>
  -            <dt>Date of content</dt>
  -            <dd>2013–2014</dd>
  -          </dl>
  -          <dl class='sources_row even'>
  -            <dt>Cautions</dt>
  -            <dd>
  -            An accuracy assessment found 40% false positives and 18% false negatives for the presence of plantations, with an overall accuracy of 79%. Overall accuracies were lowest in Indonesia at 68%.
  -            The accuracies of the species and type labels were not assessed. These fields represent the best guess of the analysts and should not be used for official purposes.
  -            Polygons labeled as clearings were bare or had very young vegetation as of 2013 or 2014, but contextual clues suggest that these areas will eventually become tree plantations.
  -            A subset of this data set more appropriate for supply chain monitoring can be found on <a href="http://commodities.globalforestwatch.org/" target="_blank">GFW Commodities.</a>
  -
  -            </dd>
  -          </dl>
  -          <dl class='sources_row'>
  -            <dt>License</dt>
  -            <dd><a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">CC BY 4.0</a></dd>
  -          </dl>
  -        </div>
  -
  -        <div class='source_summary'>
  -          <h3 class='overview_title'>Overview</h3>
  -          <p>This data set was created by Transparent World, with the support of Global Forest Watch. Many studies depicting forest cover and forest change cannot distinguish between natural forests and plantations. This data set attempts to distinguish tree plantations from natural forest for seven key countries: Brazil, Cambodia, Colombia, Indonesia, Liberia, Malaysia, and Peru.</p>
  -
  -          <p>Given the variability of plantations and their spectral similarity to natural forests, this study used visual interpretations of satellite imagery, primarily <a href="http://landsat.usgs.gov/" target="_blank">Landsat</a>, supplemented by high resolution imagery (Google Maps, Bing Maps, or Digital Globe), where available, to locate plantations. Analysts hand-digitized plantation boundaries based on several key visual criteria, including texture, shape, color, and size.</p>
  -
  -          <p>Each polygon is labelled with the plantation type and when possible, the species. A “gr” in front of the species name indicates a group of species, such as pines or fruit, where the individual species was not identifiable. The percentage of plantation coverage indicates a rough estimate of the prevalence of plantation within apolygon (as in the case of a mosaic). Types are defined as follows:</p>
  -          <p><ul class="bullets">
  -            <li><strong>Large industrial plantation:</strong> single plantation units larger than 100 hectares</li>
  -            <li><strong>Mosaic of medium-sized plantations:</strong> mosaic of plantation units < 100 hectares embedded within patches of other land use</li>
  -            <li><strong>Mosaic of small-sized plantations:</strong> mosaic of plantation units < 10 hectares embedded within patches of other land use.</li>
  -            <li><strong>Clearing/ very young plantation:</strong> bare ground with contextual clues suggesting it will become a plantations (shape or pattern of clearing, proximity to other plantations, distinctive road network, etc)</li>
  -          </ul></p>
  -          <p>For more information on this data set and how it was produced, see the forthcoming WRI Technical Note associated with this project.</p>
  -
  -          <p class='credits'><strong>Citation:</strong> Transparent World. “Tree Plantations.” 2015. 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'><a href='http://data.globalforestwatch.org/' target='_blank'>Learn more or download data</a></p>
  -        </div>
  -      </div>
  -    </li>
       <li id='cod_primary_forest_wgs' class='source-item'>
         <div class='source_header'>
           <strong class='source_title'>Democratic Republic of the Congo primary forests</strong>
  
positive.code:         </div>
        </div>
      </li>
  
      <li id='plantations' class='source-item'>
        <div class='source_header'>
          <strong class='source_title'>Tree Plantations</strong>
  
negative.code: 
              </dd>
            </dl>
            <dl class='sources_row'>
              <dt>License</dt>
              <dd><a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">CC BY 4.0</a></dd>
            </dl>
  