<p>Planet imagery — including all new and historical mosaics — are no longer available on GFW as of April 1, 2025. For more information on this change and an overview of the other satellite imagery already available on GFW, please <a href="https://gfw.global/3RlGb6f">read our blog</a>. We would also love to know more about how you use imagery &#8211; <a href="https://gfw.global/3G0z9BL">please complete our short survey</a>.</p>


Planet Imagery is No Longer Available on GFW

<p>The Spatial Database of Planted Trees (SDPT) is a global, living database of planted forest and tree crop boundaries aimed at differentiating planted trees from natural forests. The next version is in development, and we are seeking recommendations for planted forest or tree crop data sets that could strengthen the database &#8211; <a href="https://gfw.global/4ijTAb1">fill out this form</a> to share your input. Your feedback will help enhance the database on GFW and ensure it evolves with the best available data.</p>


We are looking for data recommendations for SDPT

<p>We&#8217;ve improved your My GFW profile settings, including adding the ability to subscribe for relevant news and event updates. <a href="https://www.globalforestwatch.org/my-gfw/?profile=true">Log in to your account</a> to update your preferences and make sure your information is correct. </p>


Update Your  My GFW Account

Data &amp; Tools

Data &amp; Tools | Global Forest Watch Blog

forest change

forest change | Global Forest Watch Blog

mapping

mapping | Global Forest Watch Blog

Michelle Sims

Liz Goldman

Elise Mazur

<p>It’s well established that forests are important for people, nature and climate, but not all forests are created equal. Natural forests tend to <a href="https://zenodo.org/records/3553579#.ZFU8GnbMJwI" target="_blank" rel="noreferrer noopener">harbor more biodiversity</a> and offer a wider array of ecosystem services than planted forests, and therefore keeping natural forests standing is particularly critical.</p>



<p>The tree cover data available on Global Forest Watch (GFW) includes all types of tree cover, including natural forests and planted trees such tree crops and wood fiber plantations. Although data on primary forests are available for the humid tropics, distinguishing natural forests globally from other types of tree cover previously required overlaying multiple data sets to exclude areas that are not natural forests.</p>



<p>Now, new <a href="https://gfw.global/4fQfl03">natural forest data on GFW</a> from the <a href="https://sciencebasedtargetsnetwork.org/" target="_blank" rel="noreferrer noopener">Science Based Target Network (SBTN)</a> Natural Lands Map can help shed light on where the world’s natural forests are located and provide a baseline for monitoring loss within them since 2020.</p>



<h2 class="wp-block-heading">What is the Science Based Target Network Natural Lands Map?</h2>



<p>Land & Carbon Lab collaborated with WWF and Systemiq to develop the <a href="https://landcarbonlab.org/insights/natural-lands-map-companies-no-conversion-targets/" target="_blank" rel="noreferrer noopener">Natural Lands Map</a> to support companies who have committed to eliminate conversion of natural lands in their supply chains through targets set with the SBTN land sector framework. The map provides a 2020 baseline of natural lands that companies can use to see where production activities have caused conversion since 2020, as well as identify and prevent future risk of conversion.</p>



<p>The Natural Lands Map includes several classes of natural land cover. The natural forest layer on GFW is a subset of the SBTN Natural Lands Map that includes the natural forest class and relevant subclasses, including wetland forests, mangroves and peat forests.</p>



<p>The <a href="https://sciencebasedtargetsnetwork.org/wp-content/uploads/2023/05/Technical-Guidance-2023-Step3-Land-v0.3-Natural-Lands-Map.pdf" target="_blank" rel="noreferrer noopener">Natural Lands Map</a> was created by combining the best available global and local land cover and land use data sets into a single harmonized map at 30-meter resolution circa the year 2020. This includes data sets such as the University of Maryland GLAD Lab’s 2020 <a href="https://www.frontiersin.org/journals/remote-sensing/articles/10.3389/frsen.2022.856903/full" target="_blank" rel="noreferrer noopener">land cover data set</a>, various data sets on cropland and <a href="https://www.wri.org/research/spatial-database-planted-trees-sdpt-version-2" target="_blank" rel="noreferrer noopener">planted trees</a>, and local data sets such as <a href="https://brasil.mapbiomas.org/en/" target="_blank" rel="noreferrer noopener">MapBiomas</a> in South America and Indonesia, among others. The various input data sets were selected based on accuracies reported from the data producers when available and alignment with the definitions used by SBTN. Input data sets were combined to create the final Map.</p>



<h2 class="wp-block-heading">How does the Map define natural forests?</h2>



<p>SBTN uses the Accountability Framework Initiative (AFi) <a href="https://accountability-framework.org/use-the-accountability-framework/definitions/" target="_blank" rel="noreferrer noopener">definitions</a> of natural ecosystems and natural forests to align with other standard setting initiatives. AFi adopts the Food and Agriculture Organization (FAO) definition of forests: land spanning more than 0.5 hectares with trees higher than 5 meters and a canopy cover of more than 10%, or trees able to reach these thresholds in situ, not including land that is predominantly under agricultural or other land use. AFi then differentiates <em>natural</em> forests as those where the species composition, structure and ecological function do not show effects of major human impacts.</p>



<p>Because satellite data cannot directly map all the elements of these definitions, the data development team operationalized them using proxies based on available data to exclude tree cover that would not meet the natural forest definition. Non-natural tree cover may include tree crops (e.g., palm oil, orchards, cocoa), planted forests (e.g., eucalyptus, teak, or pine plantations), patches of trees under 0.5 hectares, or trees within areas predominantly under agricultural or urban land use (e.g., trees planted within agricultural fields or within small urban parks). Natural forests may include primary, secondary or naturally regenerating forests, and may include some forms of low-intensity management.</p>



<p>AFi guidance states that quantitative thresholds established by national and sub-national forest definitions may take precedence over the global definitions, so local maps were given priority over global data in select regions.</p>



<h4 class="wp-block-heading">The natural forest map distinguishes natural forests from other tree cover</h4>



<div class="flourish-embed flourish-photo-slider" data-src="visualisation/21139033?163031"><script src="https://public.flourish.studio/resources/embed.js"></script><noscript><img decoding="async" src="https://public.flourish.studio/visualisation/21139033/thumbnail" width="100%" alt="photo-slider visualization" /></noscript></div>



<h2 class="wp-block-heading">What data is available on Global Forest Watch?</h2>



<p>The natural forest layer now available on the GFW map includes all natural forest subclasses from the SBTN Natural Lands Map (<a href="https://sciencebasedtargetsnetwork.org/wp-content/uploads/2023/05/Technical-Guidance-2023-Step3-Land-v0.3-Natural-Lands-Map.pdf" target="_blank" rel="noreferrer noopener">version 0.3</a>). This natural forest layer has an overall accuracy of 88%.*</p>



<iframe loading="lazy" width="670" height="490" frameborder="0" src="https://www.globalforestwatch.org/embed/map/?map=eyJkYXRhc2V0cyI6W3siZGF0YXNldCI6Im5hdHVyYWwtZm9yZXN0cyIsIm9wYWNpdHkiOjEsInZpc2liaWxpdHkiOnRydWUsImxheWVycyI6WyJuYXR1cmFsLWZvcmVzdHMtMjAyMCJdfSx7ImRhdGFzZXQiOiJwb2xpdGljYWwtYm91bmRhcmllcyIsImxheWVycyI6WyJkaXNwdXRlZC1wb2xpdGljYWwtYm91bmRhcmllcyIsInBvbGl0aWNhbC1ib3VuZGFyaWVzIl0sIm9wYWNpdHkiOjEsInZpc2liaWxpdHkiOnRydWV9XX0%3D"></iframe>



<p>Previously, GFW users could analyze tree cover loss within and outside of the <a href="https://gfw.global/2Qbv7fM">Spatial Database of Planted Trees</a>, which helped identify which losses were more likely to represent plantation harvesting or tree crop rotation. Now, the GFW dashboard allows users to separate tree cover loss in natural forests and non-natural tree cover from 2021 onwards using the natural forest map, meaning users can specifically monitor loss of natural forests around the world. This provides users with a more comprehensive and improved method to estimate loss in natural forests that is more aligned with widely accepted definitions.</p>



<iframe loading="lazy" width="630" height="460" frameborder="0" src="https://www.globalforestwatch.org/embed/widget/treeLossPlantations/country/BRA"></iframe>



<p></p>



<p>Users can also now calculate the area** of natural forest, non-natural tree cover and other land cover within administrative boundaries and other land use categories, such as protected areas.</p>



<iframe loading="lazy" width="315" height="460" frameborder="0" src="https://www.globalforestwatch.org/embed/widget/naturalForest/global"></iframe>



<p></p>



<h2 class="wp-block-heading">How can this data be used?</h2>



<p>The natural forest layer can be used to assess the extent of natural forest in 2020, and can be combined with additional data, such as tree cover loss, to monitor loss of natural forests from 2021 onward in a user’s area of interest. For example, companies can use the data to assess whether their production or sourcing activities have caused deforestation since 2020, or if their future plans pose a risk of deforestation, for tracking progress under voluntary commitments or the European Union Deforestation Regulation (EUDR).</p>



<p>For any use case however, users should consider the definitions used for the natural forest layer and determine whether these definitions align with their monitoring needs. For example, there is a key difference in how AFi and EUDR define deforestation that users must consider: while AFi defines deforestation as conversion of natural forest to non-natural tree cover or another land cover, <a href="https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32023R1115&qid=1686611894470" target="_blank" rel="noreferrer noopener">EUDR defines deforestation</a> as the conversion of any type of forest — including planted forest — to agricultural use. Because the natural forest layer does not include planted forest, users may need to use additional data to include planted forests in their forest baseline to monitor conversion of natural and planted forest to agriculture for EUDR purposes.</p>



<p>For a full description of how the natural forest map relates to EUDR, see <a href="https://landcarbonlab.org/insights/natural-lands-map-companies-no-conversion-targets/" target="_blank" rel="noreferrer noopener">this blog</a>. For more information on EUDR definitions and how GFW can support EUDR monitoring, read <a href="https://www.globalforestwatch.org/blog/data-and-tools/satellite-data-eu-regulation-deforestation-free-supply-chains/">part one</a> and <a href="https://www.globalforestwatch.org/blog/data-and-tools/monitoring-forest-degradation-eudr/">two</a> of our blog series.</p>



<p>Whenever using the SBTN Natural Lands Map, including the natural forests map on GFW, users should also be aware of a few limitations of the data:</p>



<ul type="1">
<li>Overestimation of natural forest in agroforestry systems and in temperate and boreal forests: Agroforestry systems, especially those where crops are grown under shade trees (such as some types of coffee and cocoa systems), are difficult to differentiate from natural forests in satellite imagery, and therefore available data on their extent is limited. Similarly, publicly available data on planted forests is limited in many temperate and boreal regions. As a result, these areas may be included as natural forest in the Map.</li>



<li>Inconsistent forest definitions in certain regions: Because the SBTN Natural Lands Map team prioritized local and regional input data over global data during the compilation and harmonization process when the Map was developed, there may be inconsistencies in the height and canopy density thresholds used to define forests in some regions where local data was used, including Brazil, the Amazon, Atlantic Forest, Pampa, Chaco, Indonesia, South Africa and New Zealand.</li>



<li>Temporal inconsistencies: The Map is as close to the year 2020 as possible, but due to limited data availability, some input data is from earlier time periods (e.g., 2015).</li>



<li>Resolution inconsistencies: Most input data used to create the Map is at least 30-meter resolution, but in some cases lower resolution data was used when higher resolution data was unavailable. These inconsistencies create data artifacts (sharp boundary lines that are only due to resolutions) in some areas.</li>
</ul>



<p>See more information on these limitations in the <a href="https://sciencebasedtargetsnetwork.org/wp-content/uploads/2023/05/Technical-Guidance-2023-Step3-Land-v0.3-Natural-Lands-Map.pdf" target="_blank" rel="noreferrer noopener">technical documentation</a>.</p>



<h2 class="wp-block-heading">What’s next for the natural forest data on GFW?</h2>



<p>Currently, <a href="https://sciencebasedtargetsnetwork.org/wp-content/uploads/2023/05/Technical-Guidance-2023-Step3-Land-v0.3-Natural-Lands-Map.pdf" target="_blank" rel="noreferrer noopener">version 0.3</a> of the natural forest map is available on GFW. In the coming months, we will update GFW to <a href="https://sciencebasedtargetsnetwork.org/wp-content/uploads/2024/09/Technical-Guidance-2024-Step3-Land-v1-Natural-Lands-Map.pdf" target="_blank" rel="noreferrer noopener">version 1</a>, which is now available on the <a href="https://datasets.wri.org/datasets/sbtn-natural-lands-map?map=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" target="_blank" rel="noreferrer noopener">WRI Open Data Portal</a>, <a href="https://developers.google.com/earth-engine/datasets/catalog/WRI_SBTN_naturalLands_v1" target="_blank" rel="noreferrer noopener">Google Earth Engine</a> and <a href="https://pro-news.globalforestwatch.org/news-events/how-gfw-pro-supports-eudr-compliance" target="_blank" rel="noreferrer noopener">GFW Pro</a>. We plan to continue to update the data on GFW as future versions of the SBTN Natural Lands Map become available.</p>



<p>We also plan to release additional analysis capabilities with the data, such as the option to filter deforestation and fire alerts to within natural forests. Stay tuned for future updates!</p>



<p></p>



<p>* <em>Note that the validation points were labeled based on definitions of natural forests from v1 of the SBTN Natural Lands Map, which includes more regional data sets and their corresponding definitions, as well as an additional filtering of local savanna classes to remove vegetation shorter than 5 meters from the forest class. This may affect the validation of the v0.3 natural forest layer because of variation in definitions of natural forest where local data was used. See the <a href="https://sciencebasedtargetsnetwork.org/wp-content/uploads/2024/09/Technical-Guidance-2024-Step3-Land-v1-Natural-Lands-Map.pdf" target="_blank" rel="noreferrer noopener">v1 technical note change log</a> to see the full list of changes.</em></p>



<p><em>** We generally </em><a href="https://landcarbonlab.org/insights/natural-lands-map-companies-no-conversion-targets/" target="_blank" rel="noreferrer noopener"><em>caution against</em></a><em> using the SBTN Natural Lands Map to quantify the area of natural lands due to data limitations, including overestimation of natural lands. However, data on natural and non-natural forest cover is much more widely available than other land covers, such as natural grassland and pasture, so we consider the natural forest classes to provide a reasonable approximation of natural forest area. Users should still be aware of the limitations of the data when using it to quantify area.</em></p>



<style type="text/css"></style>

New Data on Global Forest Watch Distinguishes Natural Forests from Other Tree Cover

<p>It’s well established that forests are important for people, nature and climate, but not all forests are created equal. Natural forests tend to <a href="https://zenodo.org/records/3553579#.ZFU8GnbMJwI" target="_blank" rel="noreferrer noopener">harbor more biodiversity</a> and offer a wider array of ecosystem services than planted forests, and therefore keeping natural forests standing is particularly critical.</p>



<p>The tree cover data available on Global Forest Watch (GFW) includes all types of tree cover, including natural forests and planted trees such tree crops and wood fiber plantations. Although data on primary forests are available for the humid tropics, distinguishing natural forests globally from other types of tree cover previously required overlaying multiple data sets to exclude areas that are not natural forests.</p>



<p>Now, new <a href="https://gfw.global/4fQfl03">natural forest data on GFW</a> from the <a href="https://sciencebasedtargetsnetwork.org/" target="_blank" rel="noreferrer noopener">Science Based Target Network (SBTN)</a> Natural Lands Map can help shed light on where the world’s natural forests are located and provide a baseline for monitoring loss within them since 2020.</p>



<h2 class="wp-block-heading">What is the Science Based Target Network Natural Lands Map?</h2>



<p>Land &amp; Carbon Lab collaborated with WWF and Systemiq to develop the <a href="https://landcarbonlab.org/insights/natural-lands-map-companies-no-conversion-targets/" target="_blank" rel="noreferrer noopener">Natural Lands Map</a> to support companies who have committed to eliminate conversion of natural lands in their supply chains through targets set with the SBTN land sector framework. The map provides a 2020 baseline of natural lands that companies can use to see where production activities have caused conversion since 2020, as well as identify and prevent future risk of conversion.</p>



<p>The Natural Lands Map includes several classes of natural land cover. The natural forest layer on GFW is a subset of the SBTN Natural Lands Map that includes the natural forest class and relevant subclasses, including wetland forests, mangroves and peat forests.</p>



<p>The <a href="https://sciencebasedtargetsnetwork.org/wp-content/uploads/2023/05/Technical-Guidance-2023-Step3-Land-v0.3-Natural-Lands-Map.pdf" target="_blank" rel="noreferrer noopener">Natural Lands Map</a> was created by combining the best available global and local land cover and land use data sets into a single harmonized map at 30-meter resolution circa the year 2020. This includes data sets such as the University of Maryland GLAD Lab’s 2020 <a href="https://www.frontiersin.org/journals/remote-sensing/articles/10.3389/frsen.2022.856903/full" target="_blank" rel="noreferrer noopener">land cover data set</a>, various data sets on cropland and <a href="https://www.wri.org/research/spatial-database-planted-trees-sdpt-version-2" target="_blank" rel="noreferrer noopener">planted trees</a>, and local data sets such as <a href="https://brasil.mapbiomas.org/en/" target="_blank" rel="noreferrer noopener">MapBiomas</a> in South America and Indonesia, among others. The various input data sets were selected based on accuracies reported from the data producers when available and alignment with the definitions used by SBTN. Input data sets were combined to create the final Map.</p>



<h2 class="wp-block-heading">How does the Map define natural forests?</h2>



<p>SBTN uses the Accountability Framework Initiative (AFi) <a href="https://accountability-framework.org/use-the-accountability-framework/definitions/" target="_blank" rel="noreferrer noopener">definitions</a> of natural ecosystems and natural forests to align with other standard setting initiatives. AFi adopts the Food and Agriculture Organization (FAO) definition of forests: land spanning more than 0.5 hectares with trees higher than 5 meters and a canopy cover of more than 10%, or trees able to reach these thresholds in situ, not including land that is predominantly under agricultural or other land use. AFi then differentiates <em>natural</em> forests as those where the species composition, structure and ecological function do not show effects of major human impacts.</p>



<p>Because satellite data cannot directly map all the elements of these definitions, the data development team operationalized them using proxies based on available data to exclude tree cover that would not meet the natural forest definition. Non-natural tree cover may include tree crops (e.g., palm oil, orchards, cocoa), planted forests (e.g., eucalyptus, teak, or pine plantations), patches of trees under 0.5 hectares, or trees within areas predominantly under agricultural or urban land use (e.g., trees planted within agricultural fields or within small urban parks). Natural forests may include primary, secondary or naturally regenerating forests, and may include some forms of low-intensity management.</p>



<p>AFi guidance states that quantitative thresholds established by national and sub-national forest definitions may take precedence over the global definitions, so local maps were given priority over global data in select regions.</p>



<h4 class="wp-block-heading">The natural forest map distinguishes natural forests from other tree cover</h4>



<div class="flourish-embed flourish-photo-slider" data-src="visualisation/21139033?163031"><script src="https://public.flourish.studio/resources/embed.js"></script><noscript><img src="https://public.flourish.studio/visualisation/21139033/thumbnail" width="100%" alt="photo-slider visualization" /></noscript></div>



<h2 class="wp-block-heading">What data is available on Global Forest Watch?</h2>



<p>The natural forest layer now available on the GFW map includes all natural forest subclasses from the SBTN Natural Lands Map (<a href="https://sciencebasedtargetsnetwork.org/wp-content/uploads/2023/05/Technical-Guidance-2023-Step3-Land-v0.3-Natural-Lands-Map.pdf" target="_blank" rel="noreferrer noopener">version 0.3</a>). This natural forest layer has an overall accuracy of 88%.*</p>



<iframe width="670" height="490" frameborder="0" src="https://www.globalforestwatch.org/embed/map/?map=eyJkYXRhc2V0cyI6W3siZGF0YXNldCI6Im5hdHVyYWwtZm9yZXN0cyIsIm9wYWNpdHkiOjEsInZpc2liaWxpdHkiOnRydWUsImxheWVycyI6WyJuYXR1cmFsLWZvcmVzdHMtMjAyMCJdfSx7ImRhdGFzZXQiOiJwb2xpdGljYWwtYm91bmRhcmllcyIsImxheWVycyI6WyJkaXNwdXRlZC1wb2xpdGljYWwtYm91bmRhcmllcyIsInBvbGl0aWNhbC1ib3VuZGFyaWVzIl0sIm9wYWNpdHkiOjEsInZpc2liaWxpdHkiOnRydWV9XX0%3D"></iframe>



<p>Previously, GFW users could analyze tree cover loss within and outside of the <a href="https://gfw.global/2Qbv7fM">Spatial Database of Planted Trees</a>, which helped identify which losses were more likely to represent plantation harvesting or tree crop rotation. Now, the GFW dashboard allows users to separate tree cover loss in natural forests and non-natural tree cover from 2021 onwards using the natural forest map, meaning users can specifically monitor loss of natural forests around the world. This provides users with a more comprehensive and improved method to estimate loss in natural forests that is more aligned with widely accepted definitions.</p>



<iframe width="630" height="460" frameborder="0" src="https://www.globalforestwatch.org/embed/widget/treeLossPlantations/country/BRA"></iframe>



<p></p>



<p>Users can also now calculate the area** of natural forest, non-natural tree cover and other land cover within administrative boundaries and other land use categories, such as protected areas.</p>



<iframe width="315" height="460" frameborder="0" src="https://www.globalforestwatch.org/embed/widget/naturalForest/global"></iframe>



<p></p>



<h2 class="wp-block-heading">How can this data be used?</h2>



<p>The natural forest layer can be used to assess the extent of natural forest in 2020, and can be combined with additional data, such as tree cover loss, to monitor loss of natural forests from 2021 onward in a user’s area of interest. For example, companies can use the data to assess whether their production or sourcing activities have caused deforestation since 2020, or if their future plans pose a risk of deforestation, for tracking progress under voluntary commitments or the European Union Deforestation Regulation (EUDR).</p>



<p>For any use case however, users should consider the definitions used for the natural forest layer and determine whether these definitions align with their monitoring needs. For example, there is a key difference in how AFi and EUDR define deforestation that users must consider: while AFi defines deforestation as conversion of natural forest to non-natural tree cover or another land cover, <a href="https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32023R1115&amp;qid=1686611894470" target="_blank" rel="noreferrer noopener">EUDR defines deforestation</a> as the conversion of any type of forest — including planted forest — to agricultural use. Because the natural forest layer does not include planted forest, users may need to use additional data to include planted forests in their forest baseline to monitor conversion of natural and planted forest to agriculture for EUDR purposes.</p>



<p>For a full description of how the natural forest map relates to EUDR, see <a href="https://landcarbonlab.org/insights/natural-lands-map-companies-no-conversion-targets/" target="_blank" rel="noreferrer noopener">this blog</a>. For more information on EUDR definitions and how GFW can support EUDR monitoring, read <a href="https://www.globalforestwatch.org/blog/data-and-tools/satellite-data-eu-regulation-deforestation-free-supply-chains/">part one</a> and <a href="https://www.globalforestwatch.org/blog/data-and-tools/monitoring-forest-degradation-eudr/">two</a> of our blog series.</p>



<p>Whenever using the SBTN Natural Lands Map, including the natural forests map on GFW, users should also be aware of a few limitations of the data:</p>



<ul type="1">
<li>Overestimation of natural forest in agroforestry systems and in temperate and boreal forests: Agroforestry systems, especially those where crops are grown under shade trees (such as some types of coffee and cocoa systems), are difficult to differentiate from natural forests in satellite imagery, and therefore available data on their extent is limited. Similarly, publicly available data on planted forests is limited in many temperate and boreal regions. As a result, these areas may be included as natural forest in the Map.</li>



<li>Inconsistent forest definitions in certain regions: Because the SBTN Natural Lands Map team prioritized local and regional input data over global data during the compilation and harmonization process when the Map was developed, there may be inconsistencies in the height and canopy density thresholds used to define forests in some regions where local data was used, including Brazil, the Amazon, Atlantic Forest, Pampa, Chaco, Indonesia, South Africa and New Zealand.</li>



<li>Temporal inconsistencies: The Map is as close to the year 2020 as possible, but due to limited data availability, some input data is from earlier time periods (e.g., 2015).</li>



<li>Resolution inconsistencies: Most input data used to create the Map is at least 30-meter resolution, but in some cases lower resolution data was used when higher resolution data was unavailable. These inconsistencies create data artifacts (sharp boundary lines that are only due to resolutions) in some areas.</li>
</ul>



<p>See more information on these limitations in the <a href="https://sciencebasedtargetsnetwork.org/wp-content/uploads/2023/05/Technical-Guidance-2023-Step3-Land-v0.3-Natural-Lands-Map.pdf" target="_blank" rel="noreferrer noopener">technical documentation</a>.</p>



<h2 class="wp-block-heading">What’s next for the natural forest data on GFW?</h2>



<p>Currently, <a href="https://sciencebasedtargetsnetwork.org/wp-content/uploads/2023/05/Technical-Guidance-2023-Step3-Land-v0.3-Natural-Lands-Map.pdf" target="_blank" rel="noreferrer noopener">version 0.3</a> of the natural forest map is available on GFW. In the coming months, we will update GFW to <a href="https://sciencebasedtargetsnetwork.org/wp-content/uploads/2024/09/Technical-Guidance-2024-Step3-Land-v1-Natural-Lands-Map.pdf" target="_blank" rel="noreferrer noopener">version 1</a>, which is now available on the <a href="https://datasets.wri.org/datasets/sbtn-natural-lands-map?map=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" target="_blank" rel="noreferrer noopener">WRI Open Data Portal</a>, <a href="https://developers.google.com/earth-engine/datasets/catalog/WRI_SBTN_naturalLands_v1" target="_blank" rel="noreferrer noopener">Google Earth Engine</a> and <a href="https://pro-news.globalforestwatch.org/news-events/how-gfw-pro-supports-eudr-compliance" target="_blank" rel="noreferrer noopener">GFW Pro</a>. We plan to continue to update the data on GFW as future versions of the SBTN Natural Lands Map become available.</p>



<p>We also plan to release additional analysis capabilities with the data, such as the option to filter deforestation and fire alerts to within natural forests. Stay tuned for future updates!</p>



<p></p>



<p>* <em>Note that the validation points were labeled based on definitions of natural forests from v1 of the SBTN Natural Lands Map, which includes more regional data sets and their corresponding definitions, as well as an additional filtering of local savanna classes to remove vegetation shorter than 5 meters from the forest class. This may affect the validation of the v0.3 natural forest layer because of variation in definitions of natural forest where local data was used. See the <a href="https://sciencebasedtargetsnetwork.org/wp-content/uploads/2024/09/Technical-Guidance-2024-Step3-Land-v1-Natural-Lands-Map.pdf" target="_blank" rel="noreferrer noopener">v1 technical note change log</a> to see the full list of changes.</em></p>



<p><em>** We generally </em><a href="https://landcarbonlab.org/insights/natural-lands-map-companies-no-conversion-targets/" target="_blank" rel="noreferrer noopener"><em>caution against</em></a><em> using the SBTN Natural Lands Map to quantify the area of natural lands due to data limitations, including overestimation of natural lands. However, data on natural and non-natural forest cover is much more widely available than other land covers, such as natural grassland and pasture, so we consider the natural forest classes to provide a reasonable approximation of natural forest area. Users should still be aware of the limitations of the data when using it to quantify area.</em></p>



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New natural forest data on GFW reveals where the world’s natural forests are located and provides a baseline for monitoring loss within them.

New Data Distinguishes Natural Forests from Other Tree Cover

Comment

Global Forest Watch Content

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Paige Johnson

Forest Insights

Forest Insights | Global Forest Watch Blog

Brazil

Brazil | Global Forest Watch Blog

restoration

restoration | Global Forest Watch Blog

Katie Reytar

Jefferson Ferreira-Ferreira

Luciana Alves

Carlos Leandro de Oliveira Cordeiro

Miguel Calmon

<p>In 2022, Global Forest Watch (GFW) in partnership with <a href="https://landcarbonlab.org/" target="_blank" rel="noreferrer noopener">Land & Carbon Lab</a> <a href="https://www.globalforestwatch.org/blog/data-and-tools/new-gfw-tree-cover-gain-net-change-data/">released new tree cover gain data</a> from the University of Maryland that shows <a href="https://www.wri.org/insights/tracking-global-tree-cover-gain" target="_blank" rel="noreferrer noopener">where and how much land has gained tree cover globally</a> between 2000 and 2020. This data set provided much-needed information to complement data on tree cover loss, revealing a more complete picture of forest change dynamics.</p>



<p>We’ve <a href="https://www.globalforestwatch.org/blog/data-and-tools/new-gfw-tree-cover-gain-net-change-data/">now added a new dimension</a> to the gain data showing not just the cumulative change between 2000 and 2020, but also how much tree cover was gained in the intervening five-year periods — 2000-2005, 2005-2010, 2010-2015, and 2015-2020. Data from these intervals provides valuable information on the global trajectory and pace of gain, which can help us better track the extent to which tree cover is coming back. This can include gain resulting from <a href="https://www.wri.org/forest-landscape-restoration-principles" target="_blank" rel="noreferrer noopener">forest landscape restoration</a>, which typically involves a variety of strategic interventions that lead to increased tree cover across the landscape.</p>



<p>While we now have a better global picture of tree cover gain, the data captures a wide variety of forms of tree cover, from industrial scale monoculture of Eucalyptus and oil palm — which are not typically considered forms of restoration — to regenerating natural forests. This means that though the data does include gain resulting from forest landscape restoration, it is difficult to identify or measure the success of restoration investments and interventions using the tree cover gain data alone.</p>



<p>Some contextual data, such as mapped plantations from the <a href="https://www.wri.org/research/spatial-database-planted-trees-sdpt-version-2" target="_blank" rel="noreferrer noopener">Spatial Database of Planted Trees</a>, can provide additional information that can help users distinguish gain in plantations from more natural forms of tree cover gain. However, local information — such as geographic information on where and what type of restoration activities are taking place — is the most useful for interpreting what is actually occurring in different locations and whether it would count toward <a href="https://research.wri.org/gfr/forest-targets-tracker" target="_blank" rel="noreferrer noopener">achieving global targets</a>.</p>



<p>In this blog, we explore a few such examples in Brazil where we see areas of gain, but that represent very different scenarios for what is happening on the ground.</p>



<h2 class="wp-block-heading">Tree cover gain data can capture restoration successes</h2>



<h3 class="wp-block-heading"><em>Landless Rural Workers Movement supports forest regeneration in Pará State</em></h3>



<p>The Landless Workers’ Movement (MST) is a national social movement in Brazil that focuses on agrarian land reform, seeking to achieve a self-sustainable way of life for rural poor in the country. It is the largest rural network of smallholder farmers in Latin America, supporting more than 450,000 families.</p>



<p>In 2004, MST began occupying the Abril Vermelho settlement in Pará State, an area of 6,668 hectares that had previously been used for oil palm monoculture and belonged to a bankrupt palm oil company. The land was then designated for agrarian reform and became a rural settlement. Today, Abril Vermelho has more than 300 families <a href="https://www.wri.org/insights/amazon-restoration-brazil-agrarian-reform-settlements" target="_blank" rel="noreferrer noopener">dedicated to producing food with sustainable practices</a>.</p>



<p>When MST arrived, the land was degraded including an unbalanced insect population, poor soil quality and deteriorated water springs. MST first planted small crops of beans, corn and manioc. Over the years they experimented with several management practices to improve soil productivity, cope with pests and improve water quality and quantity. The settled families practiced agroecology, an approach focused on the recovery of native vegetation through the elimination of oil palm production areas, allowing the forest to regenerate.</p>



<p>The main practice in the settlement today is agroforestry, where food crops are introduced in the regenerating forests, or native tree species are planted among food crops.</p>



<p>The tree cover gain data captures the successful restoration efforts that resulted from forest regeneration and native tree species planting. The data shows that the landscape of Abril Vermelho gained a total of 1,981 hectares between 2000 and 2020, with the vast majority (89%) of the new tree cover gained between 2000 and 2010, corresponding with when MST began occupying and settling the area.</p>



<div class="flourish-embed flourish-chart" data-src="visualisation/20025052?163031"><script src="https://public.flourish.studio/resources/embed.js"></script><noscript><img decoding="async" src="https://public.flourish.studio/visualisation/20025052/thumbnail" width="100%" alt="chart visualization" /></noscript></div>



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<p><em>Blue pixels show the tree cover gain in the Abril Vermelho settlement area.</em></p>



<p>Forest restoration and assisted natural regeneration in the settlement became part of MST’s program “Plant Trees – Produce Healthy Food” launched in 2020, which aims to plant 100 million trees all over the country. Besides being a significant contribution for their agroecology practices, this initiative is a strong contributor to Brazilian restoration goals and Nationally Determined Contributions (NDCs). Future updates to the gain data combined with local information will help to visualize and measure the impact of this initiative.</p>



<h3 class="wp-block-heading"><em>Restoration of ecological corridors gives hope to black lion tamarin population in São Paulo</em></h3>



<p>In the Pontal do Paranapanema region, located in the western corner of São Paulo state between the Parana and Paranapanema Rivers, a project to save the endangered black lion tamarin evolved into a landscape-scale restoration project that has successfully restored thousands of hectares of forest cover to support the lion tamarins’ habitat. Once thought to be extinct, the population of black lion tamarins has recovered significantly, largely due to the landscape-scale restoration in and around the only forests where they are known to exist.</p>



<p><a href="https://royalsocietypublishing.org/doi/pdf/10.1098/rsos.200939" target="_blank" rel="noreferrer noopener">A combination of factors</a> and collaboration across several sectors led to the successful restoration of the region. These factors included scientists and researchers educating local farmers about conservation and agroforestry, agreements with government to include conservation area in land titles for newly settled farming communities, and coordination among local farmers and researchers to set aside certain areas to create forest corridors that allow the tamarins and other wildlife to move freely between the larger forests of Morro do Diabo State Park and the Mico Leão Preto Ecological Station. Brazil’s forest code, which obligates landowners to reforest riparian areas, created an incentive for reforestation of these corridors, and funding for the restoration activities was secured through dozens of organizations via voluntary carbon markets.</p>



<p>The tree cover gain data shows the results of these efforts for forest recovery. The Pontal do Paranapanema landscape gained a total of 2,476 hectares of tree cover between 2000 and 2020 with nearly three-quarters of that gain occurring after 2010, which reflects the dedicated efforts of the community to reforest the ecological corridors that began in 2012.</p>



<div class="flourish-embed flourish-chart" data-src="visualisation/20025099?163031"><script src="https://public.flourish.studio/resources/embed.js"></script><noscript><img decoding="async" src="https://public.flourish.studio/visualisation/20025099/thumbnail" width="100%" alt="chart visualization" /></noscript></div>



<p>The tree cover gain data also shows the results of restoration across the ecological corridors connecting the Morro do Diabo State Park to the Mico Leão Preto Ecological Station.</p>



<iframe loading="lazy" width="670" height="490" frameborder="0" src="https://www.globalforestwatch.org/embed/map/?map=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%3D%3D"></iframe>



<p><em>Blue pixels show the tree cover gain in forested corridors between the forests of Morro do Diabo State Park, the Mico Leão Preto Ecological Station, other patch forest and the Paranapanema River.</em></p>



<h2 class="wp-block-heading">Not all tree cover gain is restoration</h2>



<h3 class="wp-block-heading"><em>Production forests dominate the landscape in Southern Bahia state</em></h3>



<p>Southern Bahia in eastern Brazil is known for its diverse ecosystems and agricultural practices. Though one of the main agricultural activities, growing cacao, uses agroforestry systems, the region has also been a significant hub for cultivating eucalyptus over the past few decades. Eucalyptus is a non-native species that is used in manufacturing pulp and paper as well as various other uses like energy.</p>



<p>Historically, companies were drawn to the region due to the availability of large, inexpensive tracts of land that were ideal for mechanized practices. The favorable climate and soil conditions supported the rapid growth of tree species like eucalyptus and pine. Additionally, government policies, including fiscal incentives and investments from the National Social and Economic Development Bank (BNDES), further encouraged the expansion of tree plantations. Many of these plantations were established on previously degraded lands implementing ecological zoning systems to ensure ecosystems protection, promoting ecological restoration and native species in a “mosaic approach,” and adopting sustainable forestry practices, such as reduced-impact logging and maintaining buffer zones around water bodies to prevent soil erosion and protect water quality.</p>



<p>This has attracted large companies to grow and harvest eucalyptus, resulting in high eucalyptus production. Due to the expansion of eucalyptus and native species, the Southern Bahia region gained 220,100 hectares of tree cover between 2000 and 2020, which translates to a more than 5% increase in tree cover.</p>



<div class="flourish-embed flourish-chart" data-src="visualisation/20023118?163031"><script src="https://public.flourish.studio/resources/embed.js"></script><noscript><img decoding="async" src="https://public.flourish.studio/visualisation/20023118/thumbnail" width="100%" alt="chart visualization" /></noscript></div>



<iframe loading="lazy" width="670" height="490" frameborder="0" src="https://www.globalforestwatch.org/embed/map/?map=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%3D%3D"></iframe>



<p><em>In Bahia state, tree cover gain is widespread, but represents a large network of eucalyptus plantations and monoculture, which is typically not considered restoration.</em></p>



<iframe loading="lazy" width="670" height="490" frameborder="0" src="https://www.globalforestwatch.org/embed/map/?map=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%3D"></iframe>



<p><em>Detailed view of eucalyptus plantations in Nova Viçosa, Bahia, Brazil.</em></p>



<p>Despite the increase in tree cover captured by the tree cover gain data, these plantations are not typically considered restoration. This is because plantations, especially those involving non-native species, do not restore the original biodiversity and ecological functions of the native ecosystems they replace. While they may contribute to carbon sequestration and other ecosystem services, they are not considered true ecological restoration.</p>



<p>In the case of Southern Bahia, the consolidation of land ownership by the companies cultivating eucalyptus has caused conflict with local organizations and communities due to impact on the landscape, among other issues. An initiative was established in 2005 that led to a national Forest Dialogue and regional forums to promote collaborative efforts to minimize the environmental impacts of eucalyptus plantations. Now, a program led by the Forest Dialogue has assigned several locations as conservation areas, and the companies are enacting restoration programs and initiatives to form ecological corridors.</p>



<p>Future data will reveal whether the region continues to gain tree cover. However, more localized information will be necessary to determine how much of this gain can be attributed to the restoration efforts led by those companies and how much is due to plantations. As a start, we know that there are 19,300 hectares of restoration reported in the Bahia state in the Brazilian Restoration and Reforestation Observatory, although the amount of reported restoration is known to be underrepresented.</p>



<h2 class="wp-block-heading">What does this mean for using the tree cover gain data?</h2>



<p>The new data on tree cover gain represents a significant step forward in understanding the dynamics of forest change from space, and as the best-available global data, significantly expands the scale at which we can view such changes. Being able to see this gain in five-year intervals, instead of just as one 20-year cumulative sum, provides important detail on the timing of when new tree cover was established and the trajectory, which are important for monitoring efforts and tracking restoration targets over time. Additionally, when combined with data on tree cover loss, it provides the missing piece on calculating net tree cover change.</p>



<p>However, there are limitations in how this data can be used. Satellites can more easily capture taller trees with at least 10% canopy cover — which means that newly sprouting growth is seldom counted. Furthermore, even though the new five-year periods provide a more complete picture of gain, there is still a lag time between when tree growth begins and when it can be detected.</p>



<p>The Bonn Challenge, UN Decade on Ecosystem Restoration and other major global initiatives have helped national governments and other communities to set priorities and channel investments toward restoration, but global data on tree cover gain or other types of land cover change alone can’t measure their success. Detailed landscape restoration plans, as well as georeferenced information on local projects and investments, are still important for understanding the scope and scale of restoration success.</p>



<p>For example, the <a href="https://www.africa.terramatch.org/" target="_blank" rel="noreferrer noopener">TerraFund for AFR100</a> initiative, which channels funding to restoration projects in Africa, has developed a <a href="https://terramatchsupport.zendesk.com/hc/en-us/articles/21178354112539-The-TerraFund-Monitoring-Reporting-and-Verification-Framework" target="_blank" rel="noreferrer noopener">Monitoring, Reporting, and Verification Framework</a> that outlines a clear set of indicators and standards for how to measure and report information on restoration progress, integrating both field-based and satellite-based sources of data.</p>



<p>Further advancements to the tree cover gain data will continue to improve its usefulness. For example, dedicated research to differentiate natural tree cover gain from industrial or plantation-based gain has <a href="https://www.nature.com/articles/s41893-022-00904-w" target="_blank" rel="noreferrer noopener">been successfully applied</a> to a prior version of tree cover gain data, with plans to expand this research to the 20-year gain data shortly. But in addition to improving global data, tying local information on actions to the global data on change will continue to be critical for monitoring restoration at scale, and having confidence that we are achieving our goals to restore degraded landscapes.</p>



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What can Tree Cover Gain Data Tell Us About Restoration? Perspectives from Brazil

O que os dados de ganho de cobertura arbórea podem nos dizer sobre restauração? Perspectivas do Brasil

This blog explores case studies in Brazil where we see tree cover gain, but that are not always restoration.

What can Tree Cover Gain Data Tell Us About Restoration? Brazil Case Studies

Tree cover gain 2000-2020 visualized on the GFW map

Mikaela Weisse

Peter Potapov

Sarah Carter

<p>In 2022, researchers at the University of Maryland (UMD) <a href="https://www.frontiersin.org/articles/10.3389/frsen.2022.856903/full" target="_blank" rel="noreferrer noopener">published the first results</a> of global tree cover height and change monitoring between 2000 and 2020, providing an updated look at tree cover <strong>height</strong>, tree cover <strong>gain</strong>, and <strong>net change</strong> in tree cover worldwide. This data set provided much-needed information to complement data on tree cover loss, illustrating all the components of forest change. The data shows that though the world lost more tree cover than it gained from 2000-2020, <a href="https://www.wri.org/insights/tracking-global-tree-cover-gain" target="_blank" rel="noreferrer noopener">36 countries</a> experienced a net gain in tree cover.</p>



<p>Since then, UMD calculated tree height and change in the intervening five-year periods — from 2005, 2010 and 2015. We’ve now made the five-year gain <a href="https://gfw.global/3ZJS5L6">available on Global Forest Watch (GFW)</a> — read on to learn more about how to access it and how it differs from data you may have used in the past.</p>



<h2 class="wp-block-heading">What’s available on GFW, and how can I access it?</h2>



<p>Three different data sets on the GFW platform are based on the height data:</p>



<p>1.<strong> Tree cover height in 2000 and 2020: </strong>This data shows the height in meters of tree canopy cover in each 30-meter pixel. Users can set the minimum height threshold starting at three meters to view the extent of tree cover above a specific height.</p>



<iframe loading="lazy" width="670" height="490" frameborder="0" src="https://gfw.global/3rrHOm7"></iframe>



<p></p>



<p>2. <strong>Tree cover gain between 2000, 2005, 2010, 2015 and 2020: </strong>This data shows areas of tree cover that grew from a height of less than five meters in the base year (either 2000, 2005, 2010 or 2015) to a height of greater than or equal to five meters in 2020. <a href="https://research.wri.org/gfr/key-terms-definitions#tree-cover-gain-and-restoration" target="_blank" rel="noreferrer noopener">Tree cover gain</a> can include regeneration of natural forests, regrowth after harvesting of planted trees or restoration activities. This layer replaces previous data on tree cover gain between 2000 and 2012.</p>



<iframe loading="lazy" width="670" height="490" frameborder="0" src="https://gfw.global/3ZJS5L6"></iframe>



<p></p>



<p>In addition to viewing the data on the map, users can access statistics on tree cover gain between an adjustable baseline year — either 2000, 2005, 2010 or 2015 — and end year 2020 on the analysis pane and dashboards. In the widget, access the settings to open up the options for adjusting the baseline.</p>



<iframe loading="lazy" width="315" height="460" frameborder="0" src="https://www.globalforestwatch.org/embed/widget/treeCoverGain/global"></iframe>



<p></p>



<p>3. <strong>Net change in tree cover between 2000 and 2020: </strong>This data shows how much more or less tree cover a given location (country, state/province or county/municipality) had in 2020 compared to 2000. This data layer was newly added to GFW in 2022.</p>



<iframe loading="lazy" width="670" height="490" frameborder="0" src="https://gfw.global/3CJo9TN"></iframe>



<p></p>



<p>In addition to viewing the data on the map, users can access statistics on net change in tree cover between 2000 and 2020 on the analysis pane and dashboards.</p>



<iframe loading="lazy" width="630" height="460" frameborder="0" src="https://www.globalforestwatch.org/embed/widget/netChange/global"></iframe>



<p></p>



<p>Annual data for all three of these data sets will eventually be available. Read more about what we’re learning from these three data sets in the <a href="https://research.wri.org/gfr/forest-extent-indicators/forest-extent" target="_blank" rel="noreferrer noopener">Forest Extent</a> and <a href="https://research.wri.org/gfr/forest-extent-indicators/forest-gain" target="_blank" rel="noreferrer noopener">Forest Gain</a> Indicators in the Global Forest Review.</p>



<h2 class="wp-block-heading">Why is GFW using tree cover height as well as canopy cover?</h2>



<p>The first iteration of the tree cover change data on GFW, including the current annual tree cover loss data and the previous tree cover gain between 2000 and 2012, used definitions based on the percent canopy cover. The three data sets discussed above are all based instead on tree cover height.</p>



<p>The main reason for this switch is because the tree cover height data is more accurate. <a href="https://gedi.umd.edu/mission/mission-overview/" target="_blank" rel="noreferrer noopener">NASA’s GEDI mission</a>, which uses a lidar sensor aboard the International Space Station, provides point-based measurements of vegetation structure, including forest canopy height, which UMD uses as training data to model tree height globally. The data defining tree cover in 2000 using a minimum height of five meters resulted in an accuracy of 97%, compared to 95% accuracy when tree cover is defined as a minimum canopy cover of 30%.</p>



<p>Additionally, tree cover height allows for improved detection of tree cover gain. Unlike tree canopy cover, which reaches its maximum soon after tree growth begins, tree height changes gradually.</p>



<p>Another value of tree cover height is that it better highlights changes in forest structure related to biomass, carbon storage and wildlife habitat. For example, tree height is linearly related to the increase of forest biomass and carbon storage, and therefore allows us to more accurately monitor carbon sequestration in trees over time.</p>



<h2 class="wp-block-heading">What’s different about the updated tree cover gain data?</h2>



<p>Like the previous tree cover gain data based on canopy cover, the data based on height shows cumulative gain between a base year and an end year. However, the updated data shows tree cover gain in five-year increments between 2000 and 2020, where the previous layer showed gain between 2000 and 2012. With eight additional years of data and a higher temporal cadence, we are now able to see a more recent view of gain and its trajectory since the start of the millennium.</p>



<p>The old data based on canopy cover and updated data based on height also feature slightly different definitions of gain due to the methodological shift from measuring canopy cover to measuring tree cover height, as described above. The old data defined gain as an increase in tree cover to at least 50% canopy cover, while the updated data defines gain as an increase in tree cover to at least five meters tall.</p>



<p>Like the previous data, the updated gain data is available at 30-meter resolution and was produced by the GLAD lab at the University of Maryland based on Landsat satellite images. Future versions of this data will show annual tree cover gain.</p>



<h2 class="wp-block-heading">What do the new 5-year intervals of tree cover gain data show?</h2>



<p>Data from the new intervals provides valuable information on the <a href="https://research.wri.org/gfr/forest-targets-tracker" target="_blank" rel="noreferrer noopener">global trajectory and pace of gain</a> and can help better reveal forest dynamics.</p>



<p>Between 2000 and 2020, a total of 130 million hectares (Mha) of tree cover was gained globally, meaning that 130 Mha of land that had no or very low tree cover in 2000 had trees at least five meters tall in 2020. But what can we say about the trajectory over time? </p>



<p>With the new five-year interval information, we now know that the rate of gain was not consistent over that 20-year time period, ranging from 41.5 Mha gained between 2000-2005 to 22.6 Mha gained between 2015-2020. While the overall trajectory shows a decline in the pace of gain, the decline in the last five-year period for which data are available is less severe. It is also important to consider the lag time between when seedlings are established and when they can be detected by satellite, with a longer time horizon needed for slower growing species. In other words, seedling establishment that occurred at the middle or end of the last five-year period (such as 2017 or later) is likely not captured in the data.&nbsp;&nbsp;</p>



<div class="flourish-embed flourish-chart" data-src="visualisation/20323036?163031"><script src="https://public.flourish.studio/resources/embed.js"></script><noscript><img decoding="async" src="https://public.flourish.studio/visualisation/20323036/thumbnail" width="100%" alt="chart visualization" /></noscript></div>



<p>Future annual tree cover height change products will improve our understanding of tree cover gain and allow for more precise and detailed measurements of forest changes over time.</p>



<h2 class="wp-block-heading">What is net change, and why is it important?</h2>



<p>The net tree cover change data tells us how much more or less tree cover there was in 2020 than in 2000 in a particular administrative area such as a country, province or district. This is different from the current annual tree cover loss data or the updated tree cover gain data, both of which focus on gross changes in tree cover. The net change corresponds to the area of gross gain minus the area of gross loss to show the overall change (which can be negative or positive).</p>



<p>Net change is important because loss and gain data by themselves show just one side of the coin. If we consider loss on its own, we‘re not accounting for tree cover that grows back due to restoration efforts, tree plantation establishment or natural regeneration (e.g. after a fire). If we consider gain on its own, we’re focusing only on new forest growth while turning a blind eye to any forests that are cut down next door.</p>



<p>Looking at net change in addition to gross gains and losses gives us a more holistic picture. Net change data is also important for better estimates of <a href="https://www.globalforestwatch.org/blog/data-and-research/forest-carbon-flux-data-explained/">carbon fluxes from forests</a> and aligns better with other data such as the FAO’s “forest area net change” statistics in the <a href="https://www.globalforestwatch.org/blog/data/global-forest-watch-and-the-forest-resources-assessment-explained-in-5-graphics-2/?ap3c=IGc_RkUBX32y-fYCAGc_RkU8wbYWz5JGo6zjLQ9HiOVomSzZ_g">Forest Resources Assessment</a>.</p>



<p>However, net change alone doesn’t tell us about the quality of tree cover that was lost or gained. For example, primary forests in Southeast Asia that have been replaced by rubber plantations are considered to have no net change if that location had tree cover in both 2000 and 2020. It is important to look at other data sets available on GFW that can help us better understand these dynamics, such as those on <a href="https://gfw.global/3y9CGGQ">primary forests</a>, Intact Forest Landscapes and <a href="https://gfw.global/3ya4v1Q">tree plantations</a>.</p>



<h2 class="wp-block-heading">How does the annual tree cover loss data fit in?</h2>



<p>Future updates to the annual tree cover loss data will also be based on tree cover height data to allow direct comparisons with the updated tree cover height and gain layers going forward. Watch for more information on this change and what it means for tree cover loss resources on GFW and in the Global Forest Review.</p>



<p>Previous years of loss data will also be eventually reprocessed. However, note that until then, the gain and loss data cannot be compared to each other because they are based on different methods and definitions.</p>



<h2 class="wp-block-heading">What are the plans for updating this data?</h2>



<p>GFW is working with UMD to deliver annual data on tree height, including tree cover loss and gain data, which will eventually replace the 20-year data we have now. This will allow us to provide annual updates on global tree cover gain and net change in addition to our annual tree cover loss updates.</p>



<p>In the meantime, you can explore key takeaways about 2000 and 2020 extent, gain and progress toward restoration goals in the <a href="https://research.wri.org/gfr/global-forest-review" target="_blank" rel="noreferrer noopener">Global Forest Review</a>; learn more about what the gain data <a href="https://www.globalforestwatch.org/blog/forest-insights/tree-cover-gain-restoration-brazil">can and can’t show us about restoration</a>; and explore the data on the GFW <a href="https://gfw.global/3ZJS5L6">map</a> and <a href="https://www.globalforestwatch.org/dashboards/global/?category=forest-change&location=WyJnbG9iYWwiXQ%3D%3D&scrollTo=forest-gain">dashboards</a>.</p>



<p><em>This piece was originally published in October 2022. It was updated in December 2024 to reflect the latest developments on GFW.</em></p>



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Exploring Tree Cover Gain and Net Change on Global Forest Watch

<p>In 2022, researchers at the University of Maryland (UMD) <a href="https://www.frontiersin.org/articles/10.3389/frsen.2022.856903/full" target="_blank" rel="noreferrer noopener">published the first results</a> of global tree cover height and change monitoring between 2000 and 2020, providing an updated look at tree cover <strong>height</strong>, tree cover <strong>gain</strong>, and <strong>net change</strong> in tree cover worldwide. This data set provided much-needed information to complement data on tree cover loss, illustrating all the components of forest change. The data shows that though the world lost more tree cover than it gained from 2000-2020, <a href="https://www.wri.org/insights/tracking-global-tree-cover-gain" target="_blank" rel="noreferrer noopener">36 countries</a> experienced a net gain in tree cover.</p>



<p>Since then, UMD calculated tree height and change in the intervening five-year periods — from 2005, 2010 and 2015. We’ve now made the five-year gain <a href="https://gfw.global/3ZJS5L6">available on Global Forest Watch (GFW)</a> — read on to learn more about how to access it and how it differs from data you may have used in the past.</p>



<h2 class="wp-block-heading">What’s available on GFW, and how can I access it?</h2>



<p>Three different data sets on the GFW platform are based on the height data:</p>



<p>1.<strong> Tree cover height in 2000 and 2020: </strong>This data shows the height in meters of tree canopy cover in each 30-meter pixel. Users can set the minimum height threshold starting at three meters to view the extent of tree cover above a specific height.</p>



<iframe width="670" height="490" frameborder="0" src="https://gfw.global/3rrHOm7"></iframe>



<p></p>



<p>2. <strong>Tree cover gain between 2000, 2005, 2010, 2015 and 2020: </strong>This data shows areas of tree cover that grew from a height of less than five meters in the base year (either 2000, 2005, 2010 or 2015) to a height of greater than or equal to five meters in 2020. <a href="https://research.wri.org/gfr/key-terms-definitions#tree-cover-gain-and-restoration" target="_blank" rel="noreferrer noopener">Tree cover gain</a> can include regeneration of natural forests, regrowth after harvesting of planted trees or restoration activities. This layer replaces previous data on tree cover gain between 2000 and 2012.</p>



<iframe width="670" height="490" frameborder="0" src="https://gfw.global/3ZJS5L6"></iframe>



<p></p>



<p>In addition to viewing the data on the map, users can access statistics on tree cover gain between an adjustable baseline year — either 2000, 2005, 2010 or 2015 — and end year 2020 on the analysis pane and dashboards. In the widget, access the settings to open up the options for adjusting the baseline.</p>



<iframe width="315" height="460" frameborder="0" src="https://www.globalforestwatch.org/embed/widget/treeCoverGain/global"></iframe>



<p></p>



<p>3. <strong>Net change in tree cover between 2000 and 2020: </strong>This data shows how much more or less tree cover a given location (country, state/province or county/municipality) had in 2020 compared to 2000. This data layer was newly added to GFW in 2022.</p>



<iframe width="670" height="490" frameborder="0" src="https://gfw.global/3CJo9TN"></iframe>



<p></p>



<p>In addition to viewing the data on the map, users can access statistics on net change in tree cover between 2000 and 2020 on the analysis pane and dashboards.</p>



<iframe width="630" height="460" frameborder="0" src="https://www.globalforestwatch.org/embed/widget/netChange/global"></iframe>



<p></p>



<p>Annual data for all three of these data sets will eventually be available. Read more about what we’re learning from these three data sets in the <a href="https://research.wri.org/gfr/forest-extent-indicators/forest-extent" target="_blank" rel="noreferrer noopener">Forest Extent</a> and <a href="https://research.wri.org/gfr/forest-extent-indicators/forest-gain" target="_blank" rel="noreferrer noopener">Forest Gain</a> Indicators in the Global Forest Review.</p>



<h2 class="wp-block-heading">Why is GFW using tree cover height as well as canopy cover?</h2>



<p>The first iteration of the tree cover change data on GFW, including the current annual tree cover loss data and the previous tree cover gain between 2000 and 2012, used definitions based on the percent canopy cover. The three data sets discussed above are all based instead on tree cover height.</p>



<p>The main reason for this switch is because the tree cover height data is more accurate. <a href="https://gedi.umd.edu/mission/mission-overview/" target="_blank" rel="noreferrer noopener">NASA’s GEDI mission</a>, which uses a lidar sensor aboard the International Space Station, provides point-based measurements of vegetation structure, including forest canopy height, which UMD uses as training data to model tree height globally. The data defining tree cover in 2000 using a minimum height of five meters resulted in an accuracy of 97%, compared to 95% accuracy when tree cover is defined as a minimum canopy cover of 30%.</p>



<p>Additionally, tree cover height allows for improved detection of tree cover gain. Unlike tree canopy cover, which reaches its maximum soon after tree growth begins, tree height changes gradually.</p>



<p>Another value of tree cover height is that it better highlights changes in forest structure related to biomass, carbon storage and wildlife habitat. For example, tree height is linearly related to the increase of forest biomass and carbon storage, and therefore allows us to more accurately monitor carbon sequestration in trees over time.</p>



<h2 class="wp-block-heading">What’s different about the updated tree cover gain data?</h2>



<p>Like the previous tree cover gain data based on canopy cover, the data based on height shows cumulative gain between a base year and an end year. However, the updated data shows tree cover gain in five-year increments between 2000 and 2020, where the previous layer showed gain between 2000 and 2012. With eight additional years of data and a higher temporal cadence, we are now able to see a more recent view of gain and its trajectory since the start of the millennium.</p>



<p>The old data based on canopy cover and updated data based on height also feature slightly different definitions of gain due to the methodological shift from measuring canopy cover to measuring tree cover height, as described above. The old data defined gain as an increase in tree cover to at least 50% canopy cover, while the updated data defines gain as an increase in tree cover to at least five meters tall.</p>



<p>Like the previous data, the updated gain data is available at 30-meter resolution and was produced by the GLAD lab at the University of Maryland based on Landsat satellite images. Future versions of this data will show annual tree cover gain.</p>



<h2 class="wp-block-heading">What do the new 5-year intervals of tree cover gain data show?</h2>



<p>Data from the new intervals provides valuable information on the <a href="https://research.wri.org/gfr/forest-targets-tracker" target="_blank" rel="noreferrer noopener">global trajectory and pace of gain</a> and can help better reveal forest dynamics.</p>



<p>Between 2000 and 2020, a total of 130 million hectares (Mha) of tree cover was gained globally, meaning that 130 Mha of land that had no or very low tree cover in 2000 had trees at least five meters tall in 2020. But what can we say about the trajectory over time? </p>



<p>With the new five-year interval information, we now know that the rate of gain was not consistent over that 20-year time period, ranging from 41.5 Mha gained between 2000-2005 to 22.6 Mha gained between 2015-2020. While the overall trajectory shows a decline in the pace of gain, the decline in the last five-year period for which data are available is less severe. It is also important to consider the lag time between when seedlings are established and when they can be detected by satellite, with a longer time horizon needed for slower growing species. In other words, seedling establishment that occurred at the middle or end of the last five-year period (such as 2017 or later) is likely not captured in the data.&nbsp;&nbsp;</p>



<div class="flourish-embed flourish-chart" data-src="visualisation/20323036?163031"><script src="https://public.flourish.studio/resources/embed.js"></script><noscript><img src="https://public.flourish.studio/visualisation/20323036/thumbnail" width="100%" alt="chart visualization" /></noscript></div>



<p>Future annual tree cover height change products will improve our understanding of tree cover gain and allow for more precise and detailed measurements of forest changes over time.</p>



<h2 class="wp-block-heading">What is net change, and why is it important?</h2>



<p>The net tree cover change data tells us how much more or less tree cover there was in 2020 than in 2000 in a particular administrative area such as a country, province or district. This is different from the current annual tree cover loss data or the updated tree cover gain data, both of which focus on gross changes in tree cover. The net change corresponds to the area of gross gain minus the area of gross loss to show the overall change (which can be negative or positive).</p>



<p>Net change is important because loss and gain data by themselves show just one side of the coin. If we consider loss on its own, we‘re not accounting for tree cover that grows back due to restoration efforts, tree plantation establishment or natural regeneration (e.g. after a fire). If we consider gain on its own, we’re focusing only on new forest growth while turning a blind eye to any forests that are cut down next door.</p>



<p>Looking at net change in addition to gross gains and losses gives us a more holistic picture. Net change data is also important for better estimates of <a href="https://www.globalforestwatch.org/blog/data-and-research/forest-carbon-flux-data-explained/">carbon fluxes from forests</a> and aligns better with other data such as the FAO’s "forest area net change” statistics in the <a href="https://www.globalforestwatch.org/blog/data/global-forest-watch-and-the-forest-resources-assessment-explained-in-5-graphics-2/?ap3c=IGc_RkUBX32y-fYCAGc_RkU8wbYWz5JGo6zjLQ9HiOVomSzZ_g">Forest Resources Assessment</a>.</p>



<p>However, net change alone doesn’t tell us about the quality of tree cover that was lost or gained. For example, primary forests in Southeast Asia that have been replaced by rubber plantations are considered to have no net change if that location had tree cover in both 2000 and 2020. It is important to look at other data sets available on GFW that can help us better understand these dynamics, such as those on <a href="https://gfw.global/3y9CGGQ">primary forests</a>, Intact Forest Landscapes and <a href="https://gfw.global/3ya4v1Q">tree plantations</a>.</p>



<h2 class="wp-block-heading">How does the annual tree cover loss data fit in?</h2>



<p>Future updates to the annual tree cover loss data will also be based on tree cover height data to allow direct comparisons with the updated tree cover height and gain layers going forward. Watch for more information on this change and what it means for tree cover loss resources on GFW and in the Global Forest Review.</p>



<p>Previous years of loss data will also be eventually reprocessed. However, note that until then, the gain and loss data cannot be compared to each other because they are based on different methods and definitions.</p>



<h2 class="wp-block-heading">What are the plans for updating this data?</h2>



<p>GFW is working with UMD to deliver annual data on tree height, including tree cover loss and gain data, which will eventually replace the 20-year data we have now. This will allow us to provide annual updates on global tree cover gain and net change in addition to our annual tree cover loss updates.</p>



<p>In the meantime, you can explore key takeaways about 2000 and 2020 extent, gain and progress toward restoration goals in the <a href="https://research.wri.org/gfr/global-forest-review" target="_blank" rel="noreferrer noopener">Global Forest Review</a>; learn more about what the gain data <a href="https://www.globalforestwatch.org/blog/forest-insights/tree-cover-gain-restoration-brazil">can and can’t show us about restoration</a>; and explore the data on the GFW <a href="https://gfw.global/3ZJS5L6">map</a> and <a href="https://www.globalforestwatch.org/dashboards/global/?category=forest-change&amp;location=WyJnbG9iYWwiXQ%3D%3D&amp;scrollTo=forest-gain">dashboards</a>.</p>



<p><em>This piece was originally published in October 2022. It was updated in December 2024 to reflect the latest developments on GFW.</em></p>



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