anchor.diff:  
                 <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>
  -              <p>A validation assessment of the 2000 – 2012 UMD change data was carried out independently from the mapping exercise at the global and biome (tropical, subtropical, temperate, and boreal) scale. A stratified random sample (for no change, loss, and gain) of 1500 blocks, each 120 × 120 meters, was used as validation data.  The amount of tree cover loss within each block was estimated using Landsat, MODIS, and Google Earth high-resolution imagery and compared to the map. Overall accuracies for loss were over 99% globally and for all biomes. However, since the overall accuracy calculations are positively skewed due to the high percentage of no change pixels, it is also important to assess the accuracy of the change predictions. The user’s accuracy (i.e. the percentage of pixels labelled as tree cover loss that actually lost tree cover) was 87.0% at the global level. At the biome level, user’s accuracies were 87.0%, 79.3%, 88.2%, and 88.0% for the tropical, subtropical, temperate, and boreal biomes, respectively. A separate test was conducted to determine the temporal accuracy of the tree cover loss data. Within the 1500 blocks, the year of the largest drop in annual MODIS NDVI was compared to the year of tree cover loss from the map. The year of disturbance matched for 75.2% of tree cover loss events, and was within one year for 96.7% of tree cover loss events.</p>
  +              <p>A validation assessment of the 2000 – 2012 Hansen/UMD/Google/USGS/NASA change data was carried out independently from the mapping exercise at the global and biome (tropical, subtropical, temperate, and boreal) scale. A stratified random sample (for no change, loss, and gain) of 1500 blocks, each 120 × 120 meters, was used as validation data.  The amount of tree cover loss within each block was estimated using Landsat, MODIS, and Google Earth high-resolution imagery and compared to the map. Overall accuracies for loss were over 99% globally and for all biomes. However, since the overall accuracy calculations are positively skewed due to the high percentage of no change pixels, it is also important to assess the accuracy of the change predictions. The user’s accuracy (i.e. the percentage of pixels labelled as tree cover loss that actually lost tree cover) was 87.0% at the global level. At the biome level, user’s accuracies were 87.0%, 79.3%, 88.2%, and 88.0% for the tropical, subtropical, temperate, and boreal biomes, respectively. A separate test was conducted to determine the temporal accuracy of the tree cover loss data. Within the 1500 blocks, the year of the largest drop in annual MODIS NDVI was compared to the year of tree cover loss from the map. The year of disturbance matched for 75.2% of tree cover loss events, and was within one year for 96.7% of tree cover loss events.</p>
               </dd>
             </dl>
           </div>
  
positive.code: 
      <p>To learn more, visit the <%= link_to 'Forest Change tab', "#{sources_path}#forest_change" %> on the Data page.</p>
  
      <p><strong>Figures:</strong> UMD/Google circle graphs, 2012 tree cover, all global overview graphs and rankings</p>
  
      <h3 class='overview_title'>European Space Agency (GlobCover)</h3>
      <p>Data from the European Space Agency’s GlobCover was used to visualize tree cover on the country pages. As stated on the <a href='http://due.esrin.esa.int/globcover/' target='_blank'>ESA website</a>, GlobCover is an initiative which began in 2005 in partnership with a number of organizations. The aim of the project was to develop a service capable of delivering global composites and land cover maps using input observations from the 300m MERIS sensor on board the ENVISAT satellite mission. ESA makes available the land cover maps, which cover 2 periods: December 2004 - June 2006 and January - December 2009. To learn more, visit the <a href='http://due.esrin.esa.int/globcover/' target='_blank'>GlobCover website</a> or <a href='http://due.esrin.esa.int/globcover/LandCover2009/Globcover2009_V2.3_Global_.zip' target='_blank'>download the 2009 GlobCover map</a>.</p>
  
negative.code: 
                <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>
  
                <p>A validation assessment of the 2000 – 2012 Hansen/UMD/Google/USGS/NASA change data was carried out independently from the mapping exercise at the global and biome (tropical, subtropical, temperate, and boreal) scale. A stratified random sample (for no change, loss, and gain) of 1500 blocks, each 120 × 120 meters, was used as validation data.  The amount of tree cover gain within each block was estimated using Landsat, MODIS, and Google Earth high-resolution imagery and compared to the map. Overall accuracies for gain were over 99.5% globally and for all biomes. However, since the overall accuracy calculations are positively skewed due to the high percentage of no change pixels, it is also important to assess the accuracy of the change predictions. The user’s accuracy (i.e. the percentage of pixels labelled as tree cover gain that actually gained tree cover) was 87.8% at the global level. At the biome level, user’s accuracies were 81.9%, 85.5%, 62.0%, and 76.7% for the tropical, subtropical, temperate, and boreal biomes, respectively.</p>
              </dd>
            </dl>
          </div>
  