anchor.diff:          </div>
         </div>
       </li>
  -
  +    <li id="oil_palm_wood_fiber" class="source-item">
  +      <div class='source_header'>
  +        <strong class='source_title'>Plantations</strong>
  +        <i class='expand_arrow'></i>
  +      </div>
  +
  +      <div class='source_body'>
  +
  +        <div class='source_table'>
  +          <dl class='sources_row'>
  +            <dt>Function</dt>
  +            <dd>Displays boundaries of areas allocated by governments to companies for tree plantations</dd>
  +          </dl>
  +          <dl class='sources_row even'>
  +            <dt>RESOLUTION / SCALE</dt>
  +            <dd>Varies by country</dd>
  +          </dl>
  +          <dl class='sources_row'>
  +            <dt>Geographic coverage</dt>
  +            <dd>Currently available for Cameroon, Gabon, Indonesia, Liberia, and Republic of the Congo</dd>
  +          </dl>
  +          <dl class='sources_row even'>
  +            <dt>Source data</dt>
  +            <dd>Generally based on a combination of government documents, satellite imagery, and GPS data.</dd>
  +          </dl>
  +          <dl class='sources_row'>
  +            <dt>Frequency of updates</dt>
  +            <dd>Variable, depending on government agencies in each country and other data providers</dd>
  +          </dl>
  +          <dl class='sources_row even'>
  +            <dt>Date of content</dt>
  +            <dd>Varies by country</dd>
  +          </dl>
  +          <dl class='sources_row'>
  +            <dt>Cautions</dt>
  +            <dd>This layer is a compilation of concession data from various countries and sources. The quality of these data can vary depending on the source. This layer may not include all existing concessions in a country, and the location of certain concessions can be inaccurate.</dd>
  +          </dl>
  +        </div>
  +
  +        <div class='source_summary'>
  +          <h3 class='overview_title'>Overview</h3>
  +          <p>“Plantation” refers to an area allocated by a government or other body for the establishment of fast growing tree plantations for the production of oil palm, timber, or other wood products, including pulp and paper.</p>
  +
  +          <p>This data set displays plantation concessions as a single layer assembled by aggregating data for multiple countries. The data may come from government agencies, NGOs, or other organizations and varies by date and data sources. For more information on concession data for each country please visit the <a href="http://data.globalforestwatch.org/">Open Data Portal</a>.</p>
  +
  +          <p>If you are aware of plantation concession data for additional countries, please email us <a href='mailto:gfw@wri.org'>here</a>.</p>
  +
  +          <p class='credits'><strong>Suggested citation for data as displayed on GFW:</strong> “Plantations.” World Resources Institute. 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', "http://data.globalforestwatch.org/datasets/20398d4dc36e47bd92b559786670f270_0" %></em></p>
  +        </div>
  +      </div>
  +    </li>
  +    <li id='oil_palm' class='source-item'>
  +      <div class='source_header'>
  +        <strong class='source_title'>Oil palm plantations</strong>
  +        <i class='expand_arrow'></i>
  +      </div>
  +
  +      <div class='source_body'>
  +
  +        <div class='source_table'>
  +          <dl class='sources_row'>
  +            <dt>Function</dt>
  +            <dd>Displays boundaries of areas allocated by governments to companies for oil palm plantations</dd>
  +          </dl>
  +          <dl class='sources_row even'>
  +            <dt>RESOLUTION / SCALE</dt>
  +            <dd>Varies by country</dd>
  +          </dl>
  +          <dl class='sources_row'>
  +            <dt>Geographic coverage</dt>
  +            <dd>Currently available for Cameroon, Republic of the Congo, Indonesia, and Liberia</dd>
  +          </dl>
  +          <dl class='sources_row even'>
  +            <dt>Source data</dt>
  +            <dd>Generally based on a combination of government documents, satellite imagery, and GPS data.</dd>
  +          </dl>
  +          <dl class='sources_row'>
  +            <dt>Frequency of updates</dt>
  +            <dd>Variable, depending on government agencies in each country and other data providers</dd>
  +          </dl>
  +          <dl class='sources_row even'>
  +            <dt>Date of content</dt>
  +            <dd>Varies by country</dd>
  +          </dl>
  +          <dl class='sources_row'>
  +            <dt>Cautions</dt>
  +            <dd>This layer is a compilation of concession data from various countries and sources. The quality of these data can vary depending on the source. This layer may not include all existing concessions in a country, and the location of certain concessions can be inaccurate.</dd>
  +          </dl>
  +        </div>
  +
  +        <div class='source_summary'>
  +          <h3 class='overview_title'>Overview</h3>
  +          <p>“Oil palm concession” refers to an area allocated by a government or other body for industrial-scale oil palm plantations.</p>
  +
  +          <p>This data set displays oil palm concessions as a single layer assembled by aggregating concession data for multiple countries. The data may come from government agencies, NGOs, or other organizations and varies by date and data sources. For more information on concession data for each country please visit the <a href="http://data.globalforestwatch.org/datasets?q=oil+palm&sort_by=relevance">Open Data Portal</a>.</p>
  +
  +          <p>If you are aware of concession data for additional countries, please email us <a href='mailto:gfw@wri.org'>here</a>.</p>
  +
  +          <p class='credits'><strong>Suggested citation for data as displayed on GFW:</strong> “Oil Palm.” World Resources Institute. 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', "http://data.globalforestwatch.org/datasets/20398d4dc36e47bd92b559786670f270_0", :class => "download-mobile-link" %></em></p>
  +        </div>
  +
  +      </div>
  +    </li>
  +    <li id='wood_fiber_plantations' class='source-item last'>
  +      <div class='source_header'>
  +        <strong class='source_title'>Wood Fiber Plantations</strong>
  +        <i class='expand_arrow'></i>
  +      </div>
  +
  +      <div class='source_body'>
  +        <div class='source_download'>
  +          <a href='http://wri-public-data.s3.amazonaws.com/gfw2/GFW_woodfiber_20130402.zip' target='_blank' title='Download'>Download<i class='arrow_down'></i></a>
  +        </div>
  +
  +        <div class='source_table'>
  +          <dl class='sources_row'>
  +            <dt>Function</dt>
  +            <dd>Displays boundaries of areas allocated by governments to private companies for tree plantations for production of timber and wood pulp for paper and paper products</dd>
  +          </dl>
  +          <dl class='sources_row even'>
  +            <dt>RESOLUTION / SCALE</dt>
  +            <dd>Varies by country</dd>
  +          </dl>
  +          <dl class='sources_row'>
  +            <dt>Geographic coverage</dt>
  +            <dd>Currently available for Republic of the Congo, Gabon, and Indonesia</dd>
  +          </dl>
  +          <dl class='sources_row even'>
  +            <dt>Source data</dt>
  +            <dd>Generally based on a combination of government documents, satellite imagery, and GPS data.</dd>
  +          </dl>
  +          <dl class='sources_row'>
  +            <dt>Frequency of updates</dt>
  +            <dd>Variable, depending on government agencies in each country and other data providers</dd>
  +          </dl>
  +          <dl class='sources_row even'>
  +            <dt>Date of content</dt>
  +            <dd>Varies by country</dd>
  +          </dl>
  +          <dl class='sources_row'>
  +            <dt>Cautions</dt>
  +            <dd>This layer is a compilation of concession data from various countries and sources. The quality of these data can vary depending on the source. This layer may not include all existing concessions in a country, and the location of certain concessions can be inaccurate.</dd>
  +          </dl>
  +        </div>
  +
  +        <div class='source_summary'>
  +          <h3 class='overview_title'>Overview</h3>
  +          <p>“Wood fiber concession” refers to an area allocated by a government or other body for establishment of fast-growing tree plantations for the production of timber and wood pulp for paper and paper products.</p>
  +
  +          <p>This data set displays wood fiber concessions as a single layer assembled by aggregating concession data for multiple countries. The data may come from government agencies, NGOs, or other organizations and varies by date and data sources. For more information on concession data for each country please visit the <a href="http://data.globalforestwatch.org/datasets?q=wood+fiber&sort_by=relevance">Open Data Portal</a>.</p>
  +
  +          <p>If you are aware of concession data for additional countries, please email us <a href='mailto:gfw@wri.org'>here</a>.</p>
  +
  +          <p class='credits'><strong>Suggested citation for data as displayed on GFW:</strong> “Wood Fiber.” World Resources Institute. 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', "http://data.globalforestwatch.org/datasets/eca9f0db800a4d5c83bbf7f231c67949_0", :class => "download-mobile-link" %></em></p>
  +        </div>
  +      </div>
  +    </li>
  +    <li id='dam_hotspots' class='source-item last'>
  +      <div class='source_header'>
  +        <strong class='source_title'>Major dams</strong>
  +        <i class='expand_arrow'></i>
  +      </div>
  +
  +      <div class='source_body'>
  +        <div class='source_table'>
  +          <dl class='sources_row'>
  +            <dt>Function</dt>
  +            <dd>Identifies dam locations for the world’s 50 major river basins.</dd>
  +          </dl>
  +          <dl class='sources_row even'>
  +            <dt>RESOLUTION / SCALE</dt>
  +            <dd>Varies by country</dd>
  +          </dl>
  +          <dl class='sources_row even'>
  +            <dt>Geographic coverage</dt>
  +            <dd>This data set is not global. The data is confined to the world’s 50 major river basins.</dd>
  +          </dl>
  +          <dl class='sources_row'>
  +            <dt>Source data</dt>
  +            <dd>Dams data are compiled from various sources, including: the <a href="http://atlas.gwsp.org/index.php?option=com_content&task=view&id=207&Itemid=68">Global Reservoir and Dam (GRanD) Database</a>, the <a href="http://waterandfood.org/">Consultative Group on International Agricultural Research (CGIAR) Challenge Program on Water and Food - Mekong</a> (for Mekong basin dams only), the <a href="http://geo.usace.army.mil/pgis/f?p=397:101:32175502090367::NO:::">United States National Inventory of Dams (NID)</a>, other government dam inventories, and original data collection by International Rivers.</dd>
  +          </dl>
  +          <dl class='sources_row'>
  +            <dt>Frequency of updates</dt>
  +            <dd>As new data becomes available</dd>
  +          </dl>
  +          <dl class='sources_row even'>
  +            <dt>Date of content</dt>
  +            <dd>2014</dd>
  +          </dl>
  +          <dl class='sources_row'>
  +            <dt>Cautions</dt>
  +            <dd>
  +              <p>Data results are biased towards public available data, so gaps may exist.</p>
  +            </dd>
  +          </dl>
  +        </div>
  +
  +        <div class='source_summary'>
  +        <h3 class='overview_title'>Overview</h3>
  +          <p>The <a href="http://www.v-c-s.org">State of the World's Rivers</a> is an interactive web database that illustrates data on ecological health in the world’s 50 major river basins. Indicators of ecosystem health are grouped into the categories of river fragmentation, biodiversity, and water quality. The database was created and published by International Rivers in 2014.</p>
  +          <p>The Dam Hotspots data contains over 5,000 dam locations determined by latitude and longitude coordinates. These locations were confined to the world’s 50 major river basins. The data set comes from multiple sources, and was corrected for location errors by International Rivers. The “project status”—a moving target—was determined by acquiring official government data, as well as through primary research from Berkeley and five International Rivers’ regional offices.</p>
  +          <div class="layer-details layer-details-dam_hotspots">
  +            <ul class="layer-colors">
  +              <li><i class="circle" style='color:#F78300;'></i>Operational: Already existing dams.</li>
  +              <li><i class="circle" style='color:#D5CB12;'></i>Under construction: Dams which are currently being constructed.</li>
  +              <li><i class="circle" style='color:#1F78B4;'></i>Planned: Dams whose studies or licensing have been completed, but construction has yet to begin.</li>
  +              <li><i class="circle" style='color:#85AB63;'></i>Inventoried: Dams whose potential site has been selected, but neither studies nor licensing have occurred.</li>
  +              <li><i class="circle" style='color:#E31A1C;'></i>Suspended: Dams which have been temporarily or permanently suspended, deactivated, cancelled, or revoked.</li>
  +              <li><i class="circle" style='color:#746969;'></i>Unknown: No data are currently available.</li>
  +            </ul>
  +          </div>
  +          <p class='credits'><strong>Citation:</strong>International Rivers, The State of the World’s Rivers, August 2014 available at <a href="http://tryse.net/googleearth/irivers-dev3/">http://tryse.net/googleearth/irivers-dev3/</a>.</p>
  +          <p class='read_more hidden'><em><a href='http://data.globalforestwatch.org/datasets/537361e2df59486e898cd4e024af57ea_0' class="download-mobile-link" target='_blank'>Learn more or download data.</a></em></p>
  +        </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>
  
positive.code:         </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>
  
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>
  