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    <article id="forest_change" class="selected">
      <h2 class="forest_change source_title">Forest change</h2>
      <p class="description">Forest change data measure tree cover loss, tree cover gain, or forest disturbance.</p>

      <ul class="sources">
        <li id="forest_loss" data-slug="forest_loss" class="first">
          <div class="source_header">
            <strong>UMD tree cover loss &amp; gain</strong>
            <i class="expand_arrow"></i>
            <em>(annual, 30m, global)</em>
          </div>

          <div class="source_body">
            <div class="source_download">
              <a href="#" class="disabled">Download coming soon<i class="arrow_down"></i></a>
            </div>
          </div>
        </li>

        <li id="semi_monthly" data-slug="semi_monthly">
          <div class="source_header">
            <strong>Forma alerts</strong>
            <i class="expand_arrow"></i>
            <em>(monthly, 500m, humid tropics)</em>
          </div>

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            <div class="source_table">
              <dl class="sources_row">
                <dt>Function</dt>
                <dd>Detects probability of forest clearing in near-real-time</dd>
              </dl>
              <dl class="sources_row even">
                <dt>Resolution/scale</dt>
                <dd>500 x 500 meters</dd>
              </dl>
              <dl class="sources_row">
                <dt>Geographical coverage</dt>
                <dd>Humid tropical forest biome</dd>
              </dl>
              <dl class="sources_row even">
                <dt>Source data</dt>
                <dd><a href="http://modis.gsfc.nasa.gov/about/" target="_blank">MODIS</a></dd>
              </dl>
              <dl class="sources_row">
                <dt>Frequency of updates</dt>
                <dd>Displayed on the GFW site as monthly alerts. Available for download in 16 day increments</dd>
              </dl>
              <dl class="sources_row even">
                <dt>Date of content</dt>
                <dd>January 2006 - present</dd>
              </dl>
              <dl class="sources_row">
                <dt>Cautions</dt>
                <dd>
                  <p>Viewing data for the first period available via the time slider may include alerts that reflect detections from the February 2000 to December 2005 training period as the algorithm "catches up" post-training. </p>
                  <p>The GFW team has clipped out some data in regions where data quality is suspected to be low because of persistent cloud cover over identified ecoregions. This covers parts of Liberia, Venezuela, Guyana, Vietnam, Laos, and Burma/Myanmar. The current extent of the FORMA alerts is available for viewing here—<a href="http://wri-01.cartodb.com/viz/3cc0f4c2-56d3-11e3-80bb-c8600054c0d1/embed_map?title=true&description=true&search=false&shareable=false&cartodb_logo=false&layer_selector=false&legends=false&scrollwheel=true&sublayer_options=1&sql=&zoom=3&center_lat=-1.845383988573187&center_lon=16.34765625" target="_blank">FORMA geographic extent</a>.</p>
                  <p>The <a href="https://github.com/reddmetrics/forma-clj" target="_blank">algorithm</a> behind the FORMA alerts is constantly evolving to fix bugs and improve accuracy. As a result, what appears on the site and the results of analyses conducted on the site may change over time. It is important to always include the access date when citing FORMA. For questions, please contact <a href="mailto:<EMAIL>"><EMAIL></a>.
                </dd>
              </dl>
            </div>

            <div class="source_summary">
              <h3 class="overview_title">Overview</h3>
              <p>The FORMA alerts data set uses an <a href="https://github.com/reddmetrics/forma-clj" target="_blank">algorithm</a> to analyze freely available satellite imagery products and other ancillary data to identify new areas of forest clearing in near real-time across the world’s <a href="http://wolfweb.unr.edu/~ldyer/classes/396/olsonetal.pdf" target="_blank">humid tropical forest biome</a>. The system analyzes data gathered daily by the <a href="http://modis.gsfc.nasa.gov/about/" target="_blank">MODIS</a> sensor, which operates on NASA’s Terra and Aqua satellites. The FORMA alerts system then detects pronounced changes in vegetation cover over time, as measured by the <a href="http://earthobservatory.nasa.gov/Features/MeasuringVegetation/measuring_vegetation_2.php" target="_blank">Normalized Difference Vegetation Index (NDVI)</a>, a measure of vegetation greenness. These pronounced changes in vegetation cover are likely to be indicative of forest being cleared, burned, or defoliated.</p>

              <p>This algorithm produces alerts that indicate where forest clearing is statistically likely to have occurred within a 500 meter × 500 meter area. FORMA alerts only appear in areas where the probability of forest clearing is greater than or equal to 50.</p>

              <p>Upcoming upgrades to FORMA include improving the resolution to 250 meters × 250 meters, and expanding coverage to tropical dry forest and eventually to other biomes across the global scale.</p>

              <p class="credits">Citation: Hammer, Dan, <NAME>, and <NAME>. 2013. “FORMA Alerts.” World Resources Institute and Center for Global Development. Accessed through Global Forest Watch on [date]. <a href="http://www.globalforestwatch.org" target="_blank">www.globalforestwatch.org</a>.</p>
            </div>

            <div class="source_description">
              <h3>Methodology</h3>
              <p>This dataset uses freely available satellite imagery, collected by the <a href="http://modis.gsfc.nasa.gov/about/" target="_blank">Moderate Resolution Imaging Spectroradiometer (MODIS)</a>, which operates on NASA's Terra and Aqua (EOS PM) satellite platforms and views the entire Earth’s surface every 1 to 2 days. The images help to reveal notable changes in vegetation cover over time using an indicator that measures vegetation intensity called the <a href="http://earthobservatory.nasa.gov/Features/MeasuringVegetation/measuring_vegetation_2.php" target="_blank">Normalized Difference Vegetation Index (NDVI)</a>. By applying an automated algorithm to this input and in combination with complementary data inputs for fire hotspots and global precipitation averages, areas where forest clearing is likely to have occurred are therefore identified. The algorithm also employs parallel processing in a remote server system the cloud that enables the rapid analysis of these very large data sets.</p>

              <h3>Explanation</h3>
              <p>Forest clearing alerts appear when and where new, large-scale clearing is likely to have occurred after 2005. Thus, the alerts should not be interpreted as an analysis of total forest cover loss area, but rather as an indication of an area that has a high probability of having experienced forest cover loss or disturbance over time. The system employs advanced statistical techniques to achieve the best fit to scientifically validate information on clearing, measured as a probability. On the GFW website, alerts appear only for 50 percent or higher probability. That is, alerts appear for a particular period when there has been significant clearing in the area during or before that period.</p>

              <h3>Temporal and spatial resolution</h3>
              <p>FORMA alerts are displayed on the GFW site as monthly data, and the site is updated each month. Users who download data for analysis will find that the underlying dataset is actually available at 16-day intervals, intervals that do not line up perfectly with calendar months. Data is displayed at a monthly resolution on GFW due to the monthly availability of precipitation data input. Users can manipulate the GFW time slider to view trends in clearing alerts from December 2005 to present.</p>

              <p>The alert system currently identifies 500 x 500 meter areas where clearing is statistically likely to have occurred. Alerts for a 250-meter resolution version are currently being developed on Google’s Earth Engine platform and will be available in 2014.</p>

              <h3>Geographic extent</h3>
              <p>FORMA alerts are currently available only for humid tropical forests (as defined by <a href="http://www.pnas.org/content/105/27/9439.full#ref-1" target="_blank">Hansen et al. (2008)</a>, based on <a href="http://wolfweb.unr.edu/~ldyer/classes/396/olsonetal.pdf" target="_blank">WWF’s terrestrial ecoregions</a>) spanning portions of 89 countries. The development team is working to incorporate additional data to extend the geographic coverage beyond the current extent. Currently FORMA data spans across portions of 89 countries. To visualize the geographic extent of the alerts on the map, switch on the “Humid Tropical Forest Biome” layer.</p>

              <h3>Data applications</h3>
              <p>The forest clearing alerts have been designed for quick identification of forest clearing as it emerges. This allows for rapid response and prioritization of scarce financial and human resources dedicated to forest conservation or sustainable forest management. Armed with this information, stakeholders can use preemptive methods such as on-the-ground visits or aerial inspection with high-resolution satellite imagery (less than 5 meter pixel resolution) to investigate suspected forest clearing areas.</p>

              <p>In addition, the alerts may be of value to a variety of researchers who study both temporal and spatial patterns related to forest clearing areas.</p>

              <p>Using the GFW platform, the alerts can be compared against other relevant data layers, such as protected areas and concessions boundaries, to evaluate the effectiveness of forest management practices across time and spatial extent.</p>

              <h3>Accuracy and validation</h3>
              <p>Inaccuracies are an inherent part of remote sensing analysis. FORMA Alerts appear in areas with a greater than 50% probability of deforestation, based on the algorithm described under methodology. However, persistent cloud cover is a continuous issue in the tropics, and extreme flooding can also produce unreliable remotely-sensed data that will result in forest clearing “false positives” (alerts where no actual tree cover loss has occurred). Furthermore, the alerting system cannot detect all forest cover loss, whether due to the small size of clearings, persistent cloud cover, or other explanations still being identified through GFW validation efforts.</p>

              <p>The major instances of false positives may occur as the following:</p>

              <ol>
                <li><strong>A random, "speckled" distribution of alerts across an ecoregion, or complete filling of a small ecoregion.</strong> Caused by limited or sparse training data, particularly in small ecoregions, which makes it difficult to tune the model there. As a result, alerts cannot be reliably detected. In a normal ecoregion, alerts are usually clustered.</li>

                <li><strong>A rapid explosion of alerts over 1-3 months covering a relatively large area.</strong> Caused by a significant, persistent drop in detected vegetation levels due to persistent cloud cover along coastlines, in mountains, or elsewhere.</li>

                <li><strong>Alerts in water.</strong> Caused by shifting water bodies. These alerts should not necessarily be considered false positives, but rather ambiguous alerts requiring additional data for corroboration.</li>
              </ol>

              <p>The GFW team is working aggressively to address potential inaccuracies in the data through rigorous validation methods. Specifically, the GFW team is comparing the growing data set of historical alerts to other validated data sets, which are being used for similar applications.</p>

              <p>This paper demonstrates the spatial correlation of the alerts with the PRODES and DETER data sets, produced by the Brazilian Space Agency for the Amazon. The conclusions from the paper help to illustrate the potential pitfalls of the algorithm, along with its strengths. Through future refinement and proposed crowdsourcing efforts, the GFW team expects the data quality of the FORMA Alerts will continue to improve.</p>

              <h3>Additional Resources on FORMA</h3>
              <strong>Working Papers:</strong>
              <ul>
                <li>FORMA: Forest Monitoring for Action – Rapid Identification of Pan-tropical Deforestation Using Moderate-Resolution Remotely Sensed Data (CGD Working Paper 192, November 2009) [<a href="http://www.cgdev.org/sites/default/files/1423248_file_Hammer_Kraft_Wheeler_FORMA_FINAL.pdf" target="_blank">pdf</a>]</li>
                <li>From REDD to Green: A Global Incentive System to Stop Tropical Forest Clearing (CGD Working Paper 282, December 2011) [<a href="http://www.cgdev.org/sites/default/files/1425830_file_Wheeler_et_al_REDD_to_Green.pdf" target="_blank">pdf</a>]</li>
                <li>Forest Clearing in the Pantropics: December 2005-2011 (CGD Working Paper 283, December 2011) [<a href="http://www.cgdev.org/publication/forest-clearing-pantropics-december-2005%E2%80%93august-2011-working-paper-283" target="_blank">pdf</a>] Data Set for Working Paper 283</li>
                <li>FORMA and fCPR: Accelerating a Performance-Based Payment System for REDD+ (CGD Policy Paper 006, June 2012) [<a href="http://www.cgdev.org/publication/forma-and-fcpr-accelerating-performance-based-payment-system-redd" target="_blank">pdf</a>]</li>
                <li>FORMA: Comparative Analysis in the Brazilian Amazon (forthcoming WRI Working Paper, expected publication date January 2014)</li>
              </ul>

              <strong>GitHub Repositories:</strong>
              <ul>
                <li><a href="https://github.com/reddmetrics/forma-clj" target="_blank">REDD Metrics FORMA page</a></li>
              </ul>
            </div>
          </div>
        </li>

        <li id="geographic_coverage_forma" data-slug="geographic_coverage_forma">
          <div class="source_header">
            <strong>Geographic coverage of forma alerts</strong>
            <i class="expand_arrow"></i>
          </div>

          <div class="source_body">
            <div class="source_download">
              <a href="https://wri-01.cartodb.com/tables/ecoregions/map" target="_blank" title="Download at project website">Download<i class="arrow_down"></i></a>
            </div>

            <div class="source_table">
              <dl class="sources_row">
                <dt>Function</dt>
                <dd>Displays the geographic coverage of FORMA alerts</dd>
              </dl>
              <dl class="sources_row even">
                <dt>Resolution/scale</dt>
                <dd>Regional</dd>
              </dl>
              <dl class="sources_row">
                <dt>Geographic coverage</dt>
                <dd>This data layer shows the geographic coverage of FORMA alerts, which largely corresponds to the extent of the humid tropic forest biome, as defined by <a href="http://www.pnas.org/content/105/27/9439.full#ref-1" target="_blank">Hansen et al. (2008)</a></dd>
              </dl>
              <dl class="sources_row even">
                <dt>Source data</dt>
                <dd><a href="http://wolfweb.unr.edu/~ldyer/classes/396/olsonetal.pdf" target="_blank">WWF's terrestrial ecoregions</a></dd>
              </dl>
              <dl class="sources_row">
                <dt>Frequency of Updates</dt>
                <dd>TBD</dd>
              </dl>
              <dl class="sources_row even">
                <dt>Date of Content</dt>
                <dd>2001</dd>
              </dl>
            </div>
          </div>
          <p class="credits">Citation: <NAME>., <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, and <NAME>. 2001. “Terrestrial Ecoregions of the World: A New Map of Life on Earth.” BioScience 51, no. 11 (November): 933–38.</p>
            </div>
        </li>

        <li id="brazilian_amazon" data-slug="brazilian_amazon">
          <div class="source_header">
            <strong>Imazon SAD alerts</strong>
            <i class="expand_arrow"></i>
            <em>(monthly, 250m, Brazilian Amazon)</em>
          </div>

          <div class="source_body"><commit_msg>Fixes incorrectly closed tags that prevented showing the loging page<commit_after><div class="narrow_column">
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    <ul>
      <li class="item_title"><i class="caret_down"></i></li>
      <li><a href="#forest_change" class="selected forest_change" data-slug="forest_change">Forest Change</a></li>
      <li><a href="#forest_cover" class="forest_cover" data-slug="forest_cover">Forest cover</a></li>
      <li><a href="#forest_use" class="forest_use" data-slug="forest_use">Forest use</a></li>
      <li><a href="#conservation" class="conservation" data-slug="conservation">Conservation</a></li>
      <li><a href="#people" class="people" data-slug="people">People</a></li>
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      <li><a href="#data_policy" class="data_policy" data-slug="data_policy">Data policy</a></li>
    </ul>
  </div>

  <div class="content_right">
    <article id="forest_change" class="selected">
      <h2 class="forest_change source_title">Forest change</h2>
      <p class="description">Forest change data measure tree cover loss, tree cover gain, or forest disturbance.</p>

      <ul class="sources">
        <li id="forest_loss" data-slug="forest_loss" class="first">
          <div class="source_header">
            <strong>UMD tree cover loss &amp; gain</strong>
            <i class="expand_arrow"></i>
            <em>(annual, 30m, global)</em>
          </div>

          <div class="source_body">
            <div class="source_download">
              <a href="#" class="disabled">Download coming soon<i class="arrow_down"></i></a>
            </div>
          </div>
        </li>

        <li id="semi_monthly" data-slug="semi_monthly">
          <div class="source_header">
            <strong>Forma alerts</strong>
            <i class="expand_arrow"></i>
            <em>(monthly, 500m, humid tropics)</em>
          </div>

          <div class="source_body">
            <div class="source_download">
              <a href="#" class="disabled">Download coming soon<i class="arrow_down"></i></a>
            </div>

            <div class="source_table">
              <dl class="sources_row">
                <dt>Function</dt>
                <dd>Detects probability of forest clearing in near-real-time</dd>
              </dl>
              <dl class="sources_row even">
                <dt>Resolution/scale</dt>
                <dd>500 x 500 meters</dd>
              </dl>
              <dl class="sources_row">
                <dt>Geographical coverage</dt>
                <dd>Humid tropical forest biome</dd>
              </dl>
              <dl class="sources_row even">
                <dt>Source data</dt>
                <dd><a href="http://modis.gsfc.nasa.gov/about/" target="_blank">MODIS</a></dd>
              </dl>
              <dl class="sources_row">
                <dt>Frequency of updates</dt>
                <dd>Displayed on the GFW site as monthly alerts. Available for download in 16 day increments</dd>
              </dl>
              <dl class="sources_row even">
                <dt>Date of content</dt>
                <dd>January 2006 - present</dd>
              </dl>
              <dl class="sources_row">
                <dt>Cautions</dt>
                <dd>
                  <p>Viewing data for the first period available via the time slider may include alerts that reflect detections from the February 2000 to December 2005 training period as the algorithm "catches up" post-training. </p>
                  <p>The GFW team has clipped out some data in regions where data quality is suspected to be low because of persistent cloud cover over identified ecoregions. This covers parts of Liberia, Venezuela, Guyana, Vietnam, Laos, and Burma/Myanmar. The current extent of the FORMA alerts is available for viewing here—<a href="http://wri-01.cartodb.com/viz/3cc0f4c2-56d3-11e3-80bb-c8600054c0d1/embed_map?title=true&description=true&search=false&shareable=false&cartodb_logo=false&layer_selector=false&legends=false&scrollwheel=true&sublayer_options=1&sql=&zoom=3&center_lat=-1.845383988573187&center_lon=16.34765625" target="_blank">FORMA geographic extent</a>.</p>
                  <p>The <a href="https://github.com/reddmetrics/forma-clj" target="_blank">algorithm</a> behind the FORMA alerts is constantly evolving to fix bugs and improve accuracy. As a result, what appears on the site and the results of analyses conducted on the site may change over time. It is important to always include the access date when citing FORMA. For questions, please contact <a href="mailto:<EMAIL>"><EMAIL></a>.</p>
                </dd>
              </dl>
            </div>

            <div class="source_summary">
              <h3 class="overview_title">Overview</h3>
              <p>The FORMA alerts data set uses an <a href="https://github.com/reddmetrics/forma-clj" target="_blank">algorithm</a> to analyze freely available satellite imagery products and other ancillary data to identify new areas of forest clearing in near real-time across the world’s <a href="http://wolfweb.unr.edu/~ldyer/classes/396/olsonetal.pdf" target="_blank">humid tropical forest biome</a>. The system analyzes data gathered daily by the <a href="http://modis.gsfc.nasa.gov/about/" target="_blank">MODIS</a> sensor, which operates on NASA’s Terra and Aqua satellites. The FORMA alerts system then detects pronounced changes in vegetation cover over time, as measured by the <a href="http://earthobservatory.nasa.gov/Features/MeasuringVegetation/measuring_vegetation_2.php" target="_blank">Normalized Difference Vegetation Index (NDVI)</a>, a measure of vegetation greenness. These pronounced changes in vegetation cover are likely to be indicative of forest being cleared, burned, or defoliated.</p>

              <p>This algorithm produces alerts that indicate where forest clearing is statistically likely to have occurred within a 500 meter × 500 meter area. FORMA alerts only appear in areas where the probability of forest clearing is greater than or equal to 50.</p>

              <p>Upcoming upgrades to FORMA include improving the resolution to 250 meters × 250 meters, and expanding coverage to tropical dry forest and eventually to other biomes across the global scale.</p>

              <p class="credits">Citation: Hammer, Dan, <NAME>, and <NAME>. 2013. “FORMA Alerts.” World Resources Institute and Center for Global Development. Accessed through Global Forest Watch on [date]. <a href="http://www.globalforestwatch.org" target="_blank">www.globalforestwatch.org</a>.</p>
            </div>

            <div class="source_description">
              <h3>Methodology</h3>
              <p>This dataset uses freely available satellite imagery, collected by the <a href="http://modis.gsfc.nasa.gov/about/" target="_blank">Moderate Resolution Imaging Spectroradiometer (MODIS)</a>, which operates on NASA's Terra and Aqua (EOS PM) satellite platforms and views the entire Earth’s surface every 1 to 2 days. The images help to reveal notable changes in vegetation cover over time using an indicator that measures vegetation intensity called the <a href="http://earthobservatory.nasa.gov/Features/MeasuringVegetation/measuring_vegetation_2.php" target="_blank">Normalized Difference Vegetation Index (NDVI)</a>. By applying an automated algorithm to this input and in combination with complementary data inputs for fire hotspots and global precipitation averages, areas where forest clearing is likely to have occurred are therefore identified. The algorithm also employs parallel processing in a remote server system the cloud that enables the rapid analysis of these very large data sets.</p>

              <h3>Explanation</h3>
              <p>Forest clearing alerts appear when and where new, large-scale clearing is likely to have occurred after 2005. Thus, the alerts should not be interpreted as an analysis of total forest cover loss area, but rather as an indication of an area that has a high probability of having experienced forest cover loss or disturbance over time. The system employs advanced statistical techniques to achieve the best fit to scientifically validate information on clearing, measured as a probability. On the GFW website, alerts appear only for 50 percent or higher probability. That is, alerts appear for a particular period when there has been significant clearing in the area during or before that period.</p>

              <h3>Temporal and spatial resolution</h3>
              <p>FORMA alerts are displayed on the GFW site as monthly data, and the site is updated each month. Users who download data for analysis will find that the underlying dataset is actually available at 16-day intervals, intervals that do not line up perfectly with calendar months. Data is displayed at a monthly resolution on GFW due to the monthly availability of precipitation data input. Users can manipulate the GFW time slider to view trends in clearing alerts from December 2005 to present.</p>

              <p>The alert system currently identifies 500 x 500 meter areas where clearing is statistically likely to have occurred. Alerts for a 250-meter resolution version are currently being developed on Google’s Earth Engine platform and will be available in 2014.</p>

              <h3>Geographic extent</h3>
              <p>FORMA alerts are currently available only for humid tropical forests (as defined by <a href="http://www.pnas.org/content/105/27/9439.full#ref-1" target="_blank">Hansen et al. (2008)</a>, based on <a href="http://wolfweb.unr.edu/~ldyer/classes/396/olsonetal.pdf" target="_blank">WWF’s terrestrial ecoregions</a>) spanning portions of 89 countries. The development team is working to incorporate additional data to extend the geographic coverage beyond the current extent. Currently FORMA data spans across portions of 89 countries. To visualize the geographic extent of the alerts on the map, switch on the “Humid Tropical Forest Biome” layer.</p>

              <h3>Data applications</h3>
              <p>The forest clearing alerts have been designed for quick identification of forest clearing as it emerges. This allows for rapid response and prioritization of scarce financial and human resources dedicated to forest conservation or sustainable forest management. Armed with this information, stakeholders can use preemptive methods such as on-the-ground visits or aerial inspection with high-resolution satellite imagery (less than 5 meter pixel resolution) to investigate suspected forest clearing areas.</p>

              <p>In addition, the alerts may be of value to a variety of researchers who study both temporal and spatial patterns related to forest clearing areas.</p>

              <p>Using the GFW platform, the alerts can be compared against other relevant data layers, such as protected areas and concessions boundaries, to evaluate the effectiveness of forest management practices across time and spatial extent.</p>

              <h3>Accuracy and validation</h3>
              <p>Inaccuracies are an inherent part of remote sensing analysis. FORMA Alerts appear in areas with a greater than 50% probability of deforestation, based on the algorithm described under methodology. However, persistent cloud cover is a continuous issue in the tropics, and extreme flooding can also produce unreliable remotely-sensed data that will result in forest clearing “false positives” (alerts where no actual tree cover loss has occurred). Furthermore, the alerting system cannot detect all forest cover loss, whether due to the small size of clearings, persistent cloud cover, or other explanations still being identified through GFW validation efforts.</p>

              <p>The major instances of false positives may occur as the following:</p>

              <ol>
                <li><strong>A random, "speckled" distribution of alerts across an ecoregion, or complete filling of a small ecoregion.</strong> Caused by limited or sparse training data, particularly in small ecoregions, which makes it difficult to tune the model there. As a result, alerts cannot be reliably detected. In a normal ecoregion, alerts are usually clustered.</li>

                <li><strong>A rapid explosion of alerts over 1-3 months covering a relatively large area.</strong> Caused by a significant, persistent drop in detected vegetation levels due to persistent cloud cover along coastlines, in mountains, or elsewhere.</li>

                <li><strong>Alerts in water.</strong> Caused by shifting water bodies. These alerts should not necessarily be considered false positives, but rather ambiguous alerts requiring additional data for corroboration.</li>
              </ol>

              <p>The GFW team is working aggressively to address potential inaccuracies in the data through rigorous validation methods. Specifically, the GFW team is comparing the growing data set of historical alerts to other validated data sets, which are being used for similar applications.</p>

              <p>This paper demonstrates the spatial correlation of the alerts with the PRODES and DETER data sets, produced by the Brazilian Space Agency for the Amazon. The conclusions from the paper help to illustrate the potential pitfalls of the algorithm, along with its strengths. Through future refinement and proposed crowdsourcing efforts, the GFW team expects the data quality of the FORMA Alerts will continue to improve.</p>

              <h3>Additional Resources on FORMA</h3>
              <strong>Working Papers:</strong>
              <ul>
                <li>FORMA: Forest Monitoring for Action – Rapid Identification of Pan-tropical Deforestation Using Moderate-Resolution Remotely Sensed Data (CGD Working Paper 192, November 2009) [<a href="http://www.cgdev.org/sites/default/files/1423248_file_Hammer_Kraft_Wheeler_FORMA_FINAL.pdf" target="_blank">pdf</a>]</li>
                <li>From REDD to Green: A Global Incentive System to Stop Tropical Forest Clearing (CGD Working Paper 282, December 2011) [<a href="http://www.cgdev.org/sites/default/files/1425830_file_Wheeler_et_al_REDD_to_Green.pdf" target="_blank">pdf</a>]</li>
                <li>Forest Clearing in the Pantropics: December 2005-2011 (CGD Working Paper 283, December 2011) [<a href="http://www.cgdev.org/publication/forest-clearing-pantropics-december-2005%E2%80%93august-2011-working-paper-283" target="_blank">pdf</a>] Data Set for Working Paper 283</li>
                <li>FORMA and fCPR: Accelerating a Performance-Based Payment System for REDD+ (CGD Policy Paper 006, June 2012) [<a href="http://www.cgdev.org/publication/forma-and-fcpr-accelerating-performance-based-payment-system-redd" target="_blank">pdf</a>]</li>
                <li>FORMA: Comparative Analysis in the Brazilian Amazon (forthcoming WRI Working Paper, expected publication date January 2014)</li>
              </ul>

              <strong>GitHub Repositories:</strong>
              <ul>
                <li><a href="https://github.com/reddmetrics/forma-clj" target="_blank">REDD Metrics FORMA page</a></li>
              </ul>
            </div>
          </div>
        </li>

        <li id="geographic_coverage_forma" data-slug="geographic_coverage_forma">
          <div class="source_header">
            <strong>Geographic coverage of forma alerts</strong>
            <i class="expand_arrow"></i>
          </div>

          <div class="source_body">
            <div class="source_download">
              <a href="https://wri-01.cartodb.com/tables/ecoregions/map" target="_blank" title="Download at project website">Download<i class="arrow_down"></i></a>
            </div>

            <div class="source_table">
              <dl class="sources_row">
                <dt>Function</dt>
                <dd>Displays the geographic coverage of FORMA alerts</dd>
              </dl>
              <dl class="sources_row even">
                <dt>Resolution/scale</dt>
                <dd>Regional</dd>
              </dl>
              <dl class="sources_row">
                <dt>Geographic coverage</dt>
                <dd>This data layer shows the geographic coverage of FORMA alerts, which largely corresponds to the extent of the humid tropic forest biome, as defined by <a href="http://www.pnas.org/content/105/27/9439.full#ref-1" target="_blank">Hansen et al. (2008)</a></dd>
              </dl>
              <dl class="sources_row even">
                <dt>Source data</dt>
                <dd><a href="http://wolfweb.unr.edu/~ldyer/classes/396/olsonetal.pdf" target="_blank">WWF's terrestrial ecoregions</a></dd>
              </dl>
              <dl class="sources_row">
                <dt>Frequency of Updates</dt>
                <dd>TBD</dd>
              </dl>
              <dl class="sources_row even">
                <dt>Date of Content</dt>
                <dd>2001</dd>
              </dl>
          </div>
          <p class="credits">Citation: <NAME>., <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, and <NAME>. 2001. “Terrestrial Ecoregions of the World: A New Map of Life on Earth.” BioScience 51, no. 11 (November): 933–38.</p>
            </div>
        </li>

        <li id="brazilian_amazon" data-slug="brazilian_amazon">
          <div class="source_header">
            <strong>Imazon SAD alerts</strong>
            <i class="expand_arrow"></i>
            <em>(monthly, 250m, Brazilian Amazon)</em>
          </div>

          <div class="source_body">
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