<p>Join Global Forest Watch (GFW) and partners to explore the latest version of the Spatial Database of Planted Trees (SDPT), a harmonized database of planted forest and tree crop boundaries derived from national and regional sources.<br />
<a href="https://www.wri.org/events/2025/6/leveraging-new-planted-trees-data-improve-forest-monitoring">Register here</a>.</p>


New Planted Tree Data to Improve Forest Monitoring

Data &amp; Tools

Data &amp; Tools | Global Forest Watch Blog

mapping

mapping | Global Forest Watch Blog

Radost Stanimirova

Michelle Sims

Anton Raichuk

Maxim Neumann

<p>Over the past several decades, forest loss has been a <a href="https://research.wri.org/gfr/latest-analysis-deforestation-trends" target="_blank" rel="noreferrer noopener">stubbornly persistent problem</a> that can disrupt ecosystems, biodiversity and climate stability, as well as negatively impact forest-dependent people around the world.</p>



<p>However, <a href="https://research.wri.org/gfr/key-terms-definitions#tree-cover-loss-and-deforestation" target="_blank" rel="noreferrer noopener">not all forest loss is created equal</a>. Deforestation, which typically refers to the permanent conversion of forests to other land uses, often has more severe carbon and ecological impacts compared to temporary forest disturbances such as from logging and other natural and anthropogenic causes.</p>



<p>To better track and differentiate these changes, Global Forest Watch (GFW), Land & Carbon Lab and <a href="https://deepmind.google/" target="_blank" rel="noreferrer noopener">Google DeepMind</a> have developed a <a href="https://doi.org/10.1088/1748-9326/add606" target="_blank" rel="noreferrer noopener">new global data set</a> — <a href="https://gfw.global/39qbPdC">available on GFW</a> — on the drivers of tree cover loss at 1-kilometer (km) resolution from 2001 to 2024. Previously, data on drivers was available at <a href="https://www.science.org/doi/10.1126/science.aau3445" target="_blank" rel="noreferrer noopener">10-km resolution</a>. The development of this data was led by <a href="https://sustainabilityconsortium.org/" target="_blank" rel="noreferrer noopener">The Sustainability Consortium</a> and provided the foundation for the new 1-km data set. The higher resolution of the new data makes it possible to assess drivers in local or regional applications for the first time. The new data also has more driver classes, providing the most detailed view of drivers yet.</p>



<figure class="wp-block-image size-full"><img decoding="async" loading="lazy" width="1500" height="619" src="https://content.globalforestwatch.org/wp-content/uploads/2025/05/global_drivers_wlogging-1.png" alt="" class="wp-image-19070" srcset="https://content.globalforestwatch.org/wp-content/uploads/2025/05/global_drivers_wlogging-1.png 1500w, https://content.globalforestwatch.org/wp-content/uploads/2025/05/global_drivers_wlogging-1-1024x423.png 1024w, https://content.globalforestwatch.org/wp-content/uploads/2025/05/global_drivers_wlogging-1-768x317.png 768w" sizes="(max-width: 1500px) 100vw, 1500px" /></figure>



<p>Thanks to this increased granularity, the new data can be used to support the development of forest conservation and management policies, inform supply chain actors and governments bodies about the causes of deforestation, carbon emissions and biodiversity loss within their supply chains and jurisdictions, and track progress towards global goals to end deforestation.</p>



<h2 class="wp-block-heading">How was the new drivers of tree cover loss data developed?&nbsp;</h2>



<p>The new drivers of tree cover loss data, part of a World Resources Institute (WRI) and Google DeepMind collaboration, was developed using deep learning, which is a type of advanced AI model. We developed a <a href="https://arxiv.org/abs/1912.11370" target="_blank" rel="noreferrer noopener">customized</a> <a href="https://arxiv.org/abs/1512.03385" target="_blank" rel="noreferrer noopener">Residual Network</a> (or ResNet, a convolutional neural network model) that uses publicly available satellite observations from Landsat 7 & 8 and Sentinel 2 along with additional satellite-derived biophysical and population data relevant to the driver classes (<a href="https://iopscience.iop.org/article/10.1088/1748-9326/add606" target="_blank" rel="noreferrer noopener">see Table 2</a>) to predict the dominant driver of tree cover loss from 2001 to 2024 at 1-km resolution.</p>



<p>To train the model to make accurate predictions, we visually interpreted nearly 7,000 training samples using very-high resolution imagery. The model uses these labeled samples to learn how to associate the patterns from the input satellite imagery and other supporting data with a driver class. ResNet is a powerful AI algorithm because it uses many data transformations (or “layers”) to extract important features or patterns from an image. It can handle intricate tasks like recognizing objects in images more accurately and efficiently than traditional machine learning approaches.</p>



<p>We also collected an independent stratified random sample of 3,574 1-km plots to estimate the accuracy of the final drivers of tree cover loss map. Both the training and validation data sets are available on <a href="https://zenodo.org/records/15366671" target="_blank" rel="noreferrer noopener">Zenodo</a> and <a href="https://datasets.wri.org/datasets/dominant-drivers-of-tree-cover-loss-at-1km" target="_blank" rel="noreferrer noopener">WRI’s Data Explorer</a>. You can <a href="https://doi.org/10.1088/1748-9326/add606" target="_blank" rel="noreferrer noopener">learn more here</a> about the methodology behind the new data. </p>



<p>The data distinguishes between seven classes of drivers: permanent agriculture, hard commodities, shifting cultivation, logging, settlements and infrastructure, wildfire, and other natural disturbances. The dominant driver is defined as the direct driver that caused the majority of <a href="https://gfw.global/2HrzxeF">tree cover loss area</a> within each 1-km grid cell from 2001 to 2024.</p>



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<p>In addition to the drivers of tree cover loss classification, we also created seven probability layers, one for each of the seven driver classes. With these layers, users can implement different probability thresholds to customize the driver classification based on their knowledge of a region of interest. For example, a stakeholder in Southeast Asia interested in understanding tree cover loss due to palm oil expansion can select a custom threshold for the permanent agriculture class (e.g., greater than 0.7), and can exclude areas where probabilities of multiple drivers are high (e.g., no single class has a probability higher than 0.6) as those are more uncertain. The probabilities are available on <a href="https://datasets.wri.org/datasets/dominant-drivers-of-tree-cover-loss-at-1km" target="_blank" rel="noreferrer noopener">WRI’s Data Explorer</a> and <a href="https://developers.google.com/earth-engine/datasets/catalog/projects_landandcarbon_assets_wri_gdm_drivers_forest_loss_1km_v1_2_2001_2024" target="_blank" rel="noreferrer noopener">Google Earth Engine.</a></p>



<p>Despite the improvements the new data provides, there are some limitations:</p>



<ul>
<li>The map does not distinguish between the loss of natural forest and planted trees. For example, logging can occur in both natural forests and plantations. Similarly, permanent agriculture, hard commodities, and settlements and infrastructure classes represent a close approximation of deforestation but do not always represent the conversion of natural forests to other land uses.</li>



<li>We do not disentangle different drivers that are co-located at scales smaller than 1- km or that occur in quick succession in time.</li>
</ul>



<p><a href="https://doi.org/10.1088/1748-9326/add606" target="_blank" rel="noreferrer noopener">Read more details here</a> about the limitations of the data.</p>



<h2 class="wp-block-heading">Where can I find the new drivers of tree cover loss data on GFW?&nbsp;</h2>



<p>Users can access the data on the<a href="https://gfw.global/39qbPdC"> GFW map</a>. Users can also analyze the area and proportion of loss attributable to each driver from 2001 to 2024 within their area of interest.</p>



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



<p>Note that results from the previous drivers of tree cover loss data were displayed on the GFW dashboard as a bar chart time series, while results from the new data are displayed as a donut chart. We have changed the visualization to better reflect the characteristics of the underlying data set — the dominant driver of tree cover loss for the full time period between 2001 and 2024.</p>



<h2 class="wp-block-heading">How does the new drivers of tree cover loss data compare with the previous data?&nbsp;</h2>



<p>Compared to the <a href="https://www.science.org/doi/10.1126/science.aau3445" target="_blank" rel="noreferrer noopener">previous drivers of tree cover loss data set</a>, the new data has the following improvements:</p>



<ul>
<li>Higher spatial resolution<ul><li>Improves differentiation between small-scale commodity crop production and shifting cultivation</li></ul>
<ul>
<li>Improves detection of small-scale drivers, such as small wildfires, settlements and infrastructure, and selective logging</li>
</ul>
</li>



<li>More driver classes<ul><li>Separates commodity-driven deforestation into two separate classes: permanent agriculture and hard commodities (i.e., mining and energy infrastructure)</li></ul>
<ul>
<li>Adds a new class: other natural disturbances (e.g., storms, flooding, landslides, etc.)</li>
</ul>
</li>



<li>Higher accuracy and added probability layers<ul><li>Has higher accuracy for most regions (except Europe and Africa) and smaller confidence intervals across all regions</li></ul>
<ul>
<li>Provides probability layers, one for each of the seven driver classes</li>
</ul>
</li>
</ul>



<h4 class="wp-block-heading">Specifications of the previous 10-km data and the new 1-km data&nbsp;</h4>



<table>
    <tr>
        <td><strong>Data set</strong></td>
        <td><strong>Geographic coverage</strong></td>
        <td><strong>Years of coverage</strong></td>
        <td><strong>Spatial resolution</strong></td>
        <td><strong>Number of driver classes</strong></td>
        <td><strong>Number of layers</strong></td>
        <td><strong>Global overall accuracy</strong></td>
    </tr>
    <tr>
        <td>Previous 10-km drivers data 
<a href="https://www.science.org/doi/10.1126/science.aau3445">(Curtis et al., 2018)</a>
 </td>
        <td>Global </td>
        <td>2001-2023 </td>
        <td>10-km  </td>
        <td>5 </td>
        <td>1 </td>
        <td>89 ± 3% </td>
    </tr>
    <tr>
        <td>New 1-km drivers data <a href="https://doi.org/10.1088/1748-9326/add606">(Sims et al. 2025)</a></td>
        <td>Global </td>
        <td>2001-2024, to be updated annually with new tree cover loss data </td>
        <td>1-km  </td>
        <td>7 </td>
        <td>8, 1 for driver classes and 7 layers of probabilities </td>
        <td>91 ± 1% </td>
    </tr>
</table>



<figure class="wp-block-image size-large is-resized"><img decoding="async" loading="lazy" width="2048" height="1638" src="https://content.globalforestwatch.org/wp-content/uploads/2025/05/Drivers-accuracy-comparison-2048x1638.png" alt="" class="wp-image-19053" style="aspect-ratio:1.2503052503052503;width:840px;height:auto" srcset="https://content.globalforestwatch.org/wp-content/uploads/2025/05/Drivers-accuracy-comparison-2048x1638.png 2048w, https://content.globalforestwatch.org/wp-content/uploads/2025/05/Drivers-accuracy-comparison-1024x819.png 1024w, https://content.globalforestwatch.org/wp-content/uploads/2025/05/Drivers-accuracy-comparison-768x614.png 768w, https://content.globalforestwatch.org/wp-content/uploads/2025/05/Drivers-accuracy-comparison-1536x1229.png 1536w" sizes="(max-width: 2048px) 100vw, 2048px" /></figure>



<p>These improvements can be seen when comparing the two data sets in various places.</p>



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<p>The new data differentiates small scale fires from logging in Oregon, USA. The previous data in the same location classifies all loss as forestry.</p>



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<p>The new data detects mining, smallholder cocoa production, and urban expansion outside Kumasi, Ghana. The previous data in the same location classifies shifting agriculture and urban expansion.</p>



<div class="flourish-embed flourish-photo-slider" data-src="visualisation/21452353?163031"><script src="https://public.flourish.studio/resources/embed.js"></script><noscript><img decoding="async" src="https://public.flourish.studio/visualisation/21452353/thumbnail" width="100%" alt="photo-slider visualization" /></noscript></div>



<p>The new data detects selective logging, fires and flooding for hydropower in the Ouésso District of the Republic of Congo. The previous data in the same location classifies all loss as shifting agriculture.</p>



<p>Due to the substantial improvements the new data offers, we recommend using the 1-km drivers data set for analysis of tree cover loss drivers going forward. However, the previous 10-km data can still be accessed via the <a href="https://data.globalforestwatch.org/documents/ff304784a9f04ac4a45a40f60bae5b26/about" target="_blank" rel="noreferrer noopener">GFW open data portal</a>.</p>



<h2 class="wp-block-heading">How can the new data be used and what does it tell us about drivers of tree cover loss?&nbsp;</h2>



<iframe loading="lazy" width="670" height="490" frameborder="0" src="https://www.globalforestwatch.org/embed/map/?map=eyJkYXRhc2V0cyI6W3siZGF0YXNldCI6InRyZWUtY292ZXItbG9zcy1ieS1kb21pbmFudC1kcml2ZXIiLCJvcGFjaXR5IjoxLCJ2aXNpYmlsaXR5Ijp0cnVlLCJsYXllcnMiOlsidHJlZS1jb3Zlci1sb3NzLWJ5LWRvbWluYW50LWRyaXZlciJdfSx7ImRhdGFzZXQiOiJwb2xpdGljYWwtYm91bmRhcmllcyIsImxheWVycyI6WyJkaXNwdXRlZC1wb2xpdGljYWwtYm91bmRhcmllcyIsInBvbGl0aWNhbC1ib3VuZGFyaWVzIl0sIm9wYWNpdHkiOjEsInZpc2liaWxpdHkiOnRydWV9XX0%3D"></iframe>



<p>On a global scale, our analysis of the new data reveals that most tree cover loss can be attributed to three main drivers: permanent agriculture, wildfire and logging. But while drivers like other natural disturbances, <a href="https://www.wri.org/insights/how-mining-impacts-forests" target="_blank" rel="noreferrer noopener">hard commodities</a> and settlements and infrastructure represent a relatively small proportion of loss globally, they can play an important role regionally. <a href="https://doi.org/10.1088/1748-9326/add606" target="_blank" rel="noreferrer noopener">Read more here</a> about findings from the data on what’s driving tree cover loss.</p>



<p>This analysis demonstrates how the higher level of spatial detail in the new map provides useful contextual information for users to understand the nature of tree cover loss in their local area of interest. For example, using the map, GFW users can now separate tree cover loss due to expansion of “soft” agricultural commodities from “hard” commodities such as minerals, better characterize selective logging in the tropics and better differentiate permanent agriculture from shifting cultivation. Moreover, this map represents a major advancement in differentiating between natural and anthropogenic losses by detecting events such as bark beetle outbreaks, hurricane damage, meandering rivers and other natural disturbance events. &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</p>



<p>Because these improvements allow us to disentangle deforestation from temporary disturbances in greater detail, the new data improves our ability to track progress towards reducing deforestation such as in the <a href="https://forestdeclaration.org/about/assessment/" target="_blank" rel="noreferrer noopener">Forest Declaration Assessment</a>, the <a href="https://research.wri.org/gfr/forest-targets-tracker" target="_blank" rel="noreferrer noopener">Global Forest Review Targets Tracker</a> and the <a href="https://www.wri.org/research/state-climate-action-2023" target="_blank" rel="noreferrer noopener">State of Climate Action</a> report.</p>



<p>The new data can be used to support the development of forest conservation and management policies by making it possible to pinpoint the causes of deforestation hotspots at finer scales than ever before possible. Detailed insights allow policymakers and conservationists to design tailored interventions to address specific drivers such as logging, for example, and to hold accountable governments and organizations based on their conservation commitments.</p>



<p>Additionally, using this new data, we can refine <a href="https://gfw.global/3jLklJ9" target="_blank" rel="noreferrer noopener">maps</a> of <a href="https://www.wri.org/insights/forests-absorb-twice-much-carbon-they-emit-each-year" target="_blank" rel="noreferrer noopener">greenhouse gas emissions</a> due to tree cover loss by assigning different amounts of emissions to each driver of loss. It also improves our understanding of the causes of emissions from tree cover loss.</p>



<h2 class="wp-block-heading">What’s next for 1-km global drivers of tree cover loss data?&nbsp;</h2>



<p>This new data replaces the previous 10-km data across the whole GFW platform and in all analyses, such as <a href="https://www.nature.com/articles/s41558-020-00976-6" target="_blank" rel="noreferrer noopener">GFW’s carbon flux model</a>. The new data is used in the <a href="https://gfr.wri.org/latest-analysis-deforestation-trends" target="_blank" rel="noreferrer noopener">2024 analysis of tree cover loss</a> and in the updated <a href="https://gfr.wri.org/" target="_blank" rel="noreferrer noopener">Global Forest Review</a>. We will update the new 1-km drivers of tree cover loss data annually. </p>



<p>In the future, we plan to develop an AI model to map drivers of tree cover loss at even higher temporal and spatial resolution to understand how different drivers play out over time. Annual data on the drivers of tree cover loss is critical for assessing deforestation after specific cutoff dates relevant for policy commitments such as European Union Deforestation Regulation (EUDR) and for quantifying trends in drivers such as expansion of commodity agriculture.</p>



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

New Data on GFW Provides the Most Detailed Look Yet of What’s Driving Forest Loss Globally

New data on GFW shows drivers of tree cover loss at 1-kilometer resolution, providing the most detailed view of drivers yet.

The Most Detailed Look Yet of What’s Driving Forest Loss Globally

Comment

Global Forest Watch Content

https://content.globalforestwatch.org/wp-content/uploads/2018/06/gfwGlobal.png

https://secure.gravatar.com/avatar/be19f67e91ba81d93d32ae47706dcbb8?s=96&d=mm&r=g

Paige Johnson

Teresa Schofield

Liz Goldman

<p>Global Forest Watch (GFW) is constantly being updated to reflect the most recent and accurate data related to forests. To that end, we’ve updated the political boundaries available on GFW to the most recent version from the Database of Global Administrative Areas (GADM), an open-source political boundary data set. This update ensures that the map, statistics and analyses on GFW use the latest and most accurate information.</p>



<p>With this update, you may observe some changes that are important to be aware of, including changes to the names of political areas; the boundaries for countries, regions and subregions; map functionality around disputed areas; information in forest change and fire alert emails; and data set statistics.</p>



<p>This blog will walk through each of these changes — read on to learn more.</p>



<h2 class="wp-block-heading">What is changing and who do these changes affect?</h2>



<p>For many years, GFW has used <a href="https://gadm.org/" target="_blank" rel="noreferrer noopener">GADM boundaries</a> as political boundaries for analyses of geospatial data hosted on GFW. When a user performs an analysis of a political boundary on the map or views statistics for a country on the dashboards, they are seeing statistics for a GADM boundary.</p>



<p>In this recent update, we moved from GADM version 3.6 to version 4.1 to provide newer and more accurate information, including renamed areas, adjustments to political borders and more.</p>



<p>Please note, however, that there are various sources of political boundaries available. You can <a href="https://www.globalforestwatch.org/help/map/guides/analyze-data-map/">view instructions in our Help Center</a> on how to upload shapefiles of an alternative country, region or subregion’s boundary.</p>



<p>At the time of this article’s publication, this change is only relevant to the main GFW site, map and dashboards. GFW Pro will also update its political boundaries soon.</p>



<h2 class="wp-block-heading">Which areas are affected by this update?</h2>



<p>This update includes changes in boundaries across the globe at different levels. GADM labels these different levels as “administrative units,” and breaks them down as follows: “admin 0” refers to country level, “admin 1” refers to state/province level, and “admin 2” refers to county/district level.</p>



<h3 class="wp-block-heading">Country boundaries</h3>



<p>There is no official changelog available from GADM for this update, but our team has identified several changes to country boundaries. We saw small but noticeable differences in the borders of approximately 10 countries: Chile, China, Colombia, Costa Rica, Djibouti, Saudi Arabia, Somalia, Togo and Uruguay.</p>



<h3 class="wp-block-heading">Subnational boundaries</h3>



<p>Our analysis also revealed several updated subnational boundaries.</p>



<p>Multiple countries added or removed regions (admin 2 areas):</p>



<table>
    <tr>
        <td>Countries</td>
        <td>Number of regions in GADM 3.6</td>
        <td>Number of regions in GADM 4.1</td>
        <td>Change </td>
    </tr>
    <tr>
        <td>Colombia</td>
        <td>1065</td>
        <td>1119</td>
        <td>+54 </td>
    </tr>
    <tr>
        <td>Togo</td>
        <td>21</td>
        <td>40</td>
        <td>+19 </td>
    </tr>
    <tr>
        <td>Djibouti</td>
        <td>11</td>
        <td>21</td>
        <td>+10 </td>
    </tr>
    <tr>
        <td>Brunei</td>
        <td>32</td>
        <td>39</td>
        <td>+7 </td>
    </tr>
    <tr>
        <td>American Samoa</td>
        <td>16</td>
        <td>17</td>
        <td>+1 </td>
    </tr>
    <tr>
        <td>Benin</td>
        <td>76</td>
        <td>77</td>
        <td>+1 </td>
    </tr>
    <tr>
        <td>Chile</td>
        <td>54</td>
        <td>55</td>
        <td>+1 </td>
    </tr>
    <tr>
        <td>Costa Rica</td>
        <td>81</td>
        <td>82</td>
        <td>+1 </td>
    </tr>
    <tr>
        <td>Australia</td>
        <td>569</td>
        <td>568</td>
        <td>-1 </td>
    </tr>
    <tr>
        <td>Kenya</td>
        <td>301</td>
        <td>300</td>
        <td>-1 </td>
    </tr>
    <tr>
        <td>Ukraine</td>
        <td>629</td>
        <td>628</td>
        <td>-1 </td>
    </tr>
</table>



<p></p>



<p>At the subnational level, we noted some changes in names, identification codes and/or borders, especially in West and Southern Africa, Central America, South America, Europe and Southeast Asia. The yellow areas of the map below show the updated admin 2 areas that were changed: &nbsp;&nbsp;</p>



<figure class="wp-block-image size-full"><img decoding="async" loading="lazy" width="1500" height="885" src="https://content.globalforestwatch.org/wp-content/uploads/2025/04/gadm_changes_gold-1.png" alt="" class="wp-image-18783" srcset="https://content.globalforestwatch.org/wp-content/uploads/2025/04/gadm_changes_gold-1.png 1500w, https://content.globalforestwatch.org/wp-content/uploads/2025/04/gadm_changes_gold-1-1024x604.png 1024w, https://content.globalforestwatch.org/wp-content/uploads/2025/04/gadm_changes_gold-1-768x453.png 768w" sizes="(max-width: 1500px) 100vw, 1500px" /></figure>



<h3 class="wp-block-heading">Disputed boundaries</h3>



<p>One major change in this update is that some politically disputed boundaries are no longer included in any country or subnational analysis (note that GADM does not include all disputed boundaries in their data).</p>



<p>With this update, disputed areas are only included in global analysis available on the dashboards. This is because the previous GADM version (3.6) did not delineate disputed boundaries, but GADM 4.1 does: in version 4.1, disputed areas are separated from adjacent admin areas and have their own identification codes. This will mean that the GFW country analyses will no longer include any areas GADM identifies as politically disputed.</p>



<p>For example, the disputed region of Kashmir between China, Pakistan and India is now delineated in version 4.1.</p>



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<h2 class="wp-block-heading">How will this update affect GFW data and statistics?</h2>



<h3 class="wp-block-heading">Analyses</h3>



<p>With this update, any changes in area boundaries will result in some changes to statistics and results of analyses. If you’d like to compare the previous and new version of your admin area, we recommend downloading the 3.6 version for the chosen area via the <a href="https://gadm.org/old_versions.html" target="_blank" rel="noreferrer noopener">GADM site</a> and comparing it to the same area on the GFW map or dashboard. Please see <a href="https://www.globalforestwatch.org/help/map/guides/analyze-data-map/">this article in our Help Center</a> for instructions on how to upload shapefiles<strong><em>.</em></strong></p>



<p>As an example of this type of change, there are now five provinces in Kalimantan, Indonesia instead of four: Kalimantan Timur (East Kalimantan) has split into two areas — <a href="https://www.globalforestwatch.org/dashboards/country/IDN/34/?location=WyJjb3VudHJ5IiwiSUROIiwiMzQiXQ%3D%3D&map=eyJjYW5Cb3VuZCI6dHJ1ZX0%3D">Kalimantan Timur</a> and <a href="https://www.globalforestwatch.org/dashboards/country/IDN/35/?map=eyJjYW5Cb3VuZCI6dHJ1ZX0%3D">Kalimantan Utara (North Kalimantan)</a>.&nbsp;</p>



<h3 class="wp-block-heading">Alert subscriptions and areas saved to MyGFW accounts</h3>



<p>Users will no longer receive alert subscription emails for countries, regions or subregions saved to their MyGFW account before April 29, 2025<strong><em>.</em></strong></p>



<p>To make this change more convenient, we automatically updated political boundaries for saved countries, regions and subregions that maintained the same name between GADM versions 3.6 and 4.1. Users whose areas were automatically updated will receive an email notifying them of this change.</p>



<p>However, if you did not receive an email from us or have multiple saved political boundaries, we recommend that you re-save relevant areas of interest to your MyGFW account:</p>



<ol type="1" start="1">
<li>Navigate to your <a href="https://www.globalforestwatch.org/my-gfw/?utm_medium=email&utm_source=email1&utm_campaign=gadmupdate">MyGFW account</a> and look for areas marked with an “outdated area, notifications paused” tag.</li>



<li>Once you have noted the country, region or subregion that is no longer receiving alert emails, navigate to <a href="https://www.globalforestwatch.org/map/?utm_medium=email&utm_source=email1&utm_campaign=gadmupdate">www.globalforestwatch.org/map</a>.</li>



<li><a href="https://www.globalforestwatch.org/map/?map=eyJkYXRhc2V0cyI6W3siZGF0YXNldCI6InBvbGl0aWNhbC1ib3VuZGFyaWVzIiwibGF5ZXJzIjpbImRpc3B1dGVkLXBvbGl0aWNhbC1ib3VuZGFyaWVzIiwicG9saXRpY2FsLWJvdW5kYXJpZXMiXSwiYm91bmRhcnkiOnRydWUsIm9wYWNpdHkiOjEsInZpc2liaWxpdHkiOnRydWV9XX0%3D&mapMenu=eyJtZW51U2VjdGlvbiI6InNlYXJjaCJ9&utm_medium=email&utm_source=email1&utm_campaign=gadmupdate">Search for the area</a> or navigate to it.</li>



<li>Click on the area, select “analyze,” and then select “save in MyGFW.”</li>



<li>Customize the saved area by selecting a name, tags, alert notifications and more, and then click “save.”</li>
</ol>



<p>You will then continue to receive alert notification emails for this area.</p>



<h3 class="wp-block-heading">Embeds and URLs</h3>



<p>Embeds of and links to countries, regions and subregions on the dashboard and map may now show or link to new areas. This is due to the GADM identification code changing between versions.</p>



<p>If you are using an embed that shows a political boundary, we recommend checking that it still shows the area you originally chose; if the area’s identifier changed, the embed may show an entirely new area.</p>



<h4 class="wp-block-heading">Example from Ghana where the embed shows a new area due to the area identifier changing</h4>



<iframe loading="lazy" width="670" height="490" frameborder="0" src="https://www.globalforestwatch.org/embed/map/?mainMap=eyJzaG93QW5hbHlzaXMiOnRydWV9&map=eyJjZW50ZXIiOnsibGF0Ijo2LjkxNjA4ODMwOTEyNDQ2MiwibG5nIjotMC4zOTI1OTAxODgxNzM3Mzk5fSwiem9vbSI6OC42ODQxODM4MTA0ODgzNTMsImNhbkJvdW5kIjpmYWxzZSwiZGF0YXNldHMiOlt7ImRhdGFzZXQiOiJwb2xpdGljYWwtYm91bmRhcmllcyIsImxheWVycyI6WyJkaXNwdXRlZC1wb2xpdGljYWwtYm91bmRhcmllcyIsInBvbGl0aWNhbC1ib3VuZGFyaWVzIl0sImJvdW5kYXJ5Ijp0cnVlLCJvcGFjaXR5IjoxLCJ2aXNpYmlsaXR5Ijp0cnVlfV19&mapMenu=eyJzZWFyY2giOiJzZW5lLCBnaGFuYSJ9&mapPrompts=eyJvcGVuIjp0cnVlLCJzdGVwc0tleSI6InJlY2VudEltYWdlcnkifQ%3D%3D"></iframe>



<p>If you saved a URL that links to a political boundary, we also recommend checking that the URL still shows the desired area of interest. If it does not, follow <a href="https://www.globalforestwatch.org/help/map/guides/how-to-use-map-dashboards/">these instructions</a> on how you can search for an area on the map and dashboards.</p>



<h2 class="wp-block-heading">Where can I ask questions and get help?</h2>



<p>The GFW team aims to provide the latest forest monitoring updates for users and support your use of the GFW platform, and we highly value your feedback. If you have feedback on these changes or need help, please contact us at <a href="mailto:gfw@wri.org">gfw@wri.org.</a></p>



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Global Forest Watch Has Updated Political Boundaries — Here’s What You Should Know

<p>Global Forest Watch (GFW) is constantly being updated to reflect the most recent and accurate data related to forests. To that end, we’ve updated the political boundaries available on GFW to the most recent version from the Database of Global Administrative Areas (GADM), an open-source political boundary data set. This update ensures that the map, statistics and analyses on GFW use the latest and most accurate information.</p>



<p>With this update, you may observe some changes that are important to be aware of, including changes to the names of political areas; the boundaries for countries, regions and subregions; map functionality around disputed areas; information in forest change and fire alert emails; and data set statistics.</p>



<p>This blog will walk through each of these changes — read on to learn more.</p>



<h2 class="wp-block-heading">What is changing and who do these changes affect?</h2>



<p>For many years, GFW has used <a href="https://gadm.org/" target="_blank" rel="noreferrer noopener">GADM boundaries</a> as political boundaries for analyses of geospatial data hosted on GFW. When a user performs an analysis of a political boundary on the map or views statistics for a country on the dashboards, they are seeing statistics for a GADM boundary.</p>



<p>In this recent update, we moved from GADM version 3.6 to version 4.1 to provide newer and more accurate information, including renamed areas, adjustments to political borders and more.</p>



<p>Please note, however, that there are various sources of political boundaries available. You can <a href="https://www.globalforestwatch.org/help/map/guides/analyze-data-map/">view instructions in our Help Center</a> on how to upload shapefiles of an alternative country, region or subregion’s boundary.</p>



<p>At the time of this article’s publication, this change is only relevant to the main GFW site, map and dashboards. GFW Pro will also update its political boundaries soon.</p>



<h2 class="wp-block-heading">Which areas are affected by this update?</h2>



<p>This update includes changes in boundaries across the globe at different levels. GADM labels these different levels as “administrative units,” and breaks them down as follows: “admin 0” refers to country level, “admin 1” refers to state/province level, and “admin 2” refers to county/district level.</p>



<h3 class="wp-block-heading">Country boundaries</h3>



<p>There is no official changelog available from GADM for this update, but our team has identified several changes to country boundaries. We saw small but noticeable differences in the borders of approximately 10 countries: Chile, China, Colombia, Costa Rica, Djibouti, Saudi Arabia, Somalia, Togo and Uruguay.</p>



<h3 class="wp-block-heading">Subnational boundaries</h3>



<p>Our analysis also revealed several updated subnational boundaries.</p>



<p>Multiple countries added or removed regions (admin 2 areas):</p>



<table>
    <tr>
        <td>Countries</td>
        <td>Number of regions in GADM 3.6</td>
        <td>Number of regions in GADM 4.1</td>
        <td>Change </td>
    </tr>
    <tr>
        <td>Colombia</td>
        <td>1065</td>
        <td>1119</td>
        <td>+54 </td>
    </tr>
    <tr>
        <td>Togo</td>
        <td>21</td>
        <td>40</td>
        <td>+19 </td>
    </tr>
    <tr>
        <td>Djibouti</td>
        <td>11</td>
        <td>21</td>
        <td>+10 </td>
    </tr>
    <tr>
        <td>Brunei</td>
        <td>32</td>
        <td>39</td>
        <td>+7 </td>
    </tr>
    <tr>
        <td>American Samoa</td>
        <td>16</td>
        <td>17</td>
        <td>+1 </td>
    </tr>
    <tr>
        <td>Benin</td>
        <td>76</td>
        <td>77</td>
        <td>+1 </td>
    </tr>
    <tr>
        <td>Chile</td>
        <td>54</td>
        <td>55</td>
        <td>+1 </td>
    </tr>
    <tr>
        <td>Costa Rica</td>
        <td>81</td>
        <td>82</td>
        <td>+1 </td>
    </tr>
    <tr>
        <td>Australia</td>
        <td>569</td>
        <td>568</td>
        <td>-1 </td>
    </tr>
    <tr>
        <td>Kenya</td>
        <td>301</td>
        <td>300</td>
        <td>-1 </td>
    </tr>
    <tr>
        <td>Ukraine</td>
        <td>629</td>
        <td>628</td>
        <td>-1 </td>
    </tr>
</table>



<p></p>



<p>At the subnational level, we noted some changes in names, identification codes and/or borders, especially in West and Southern Africa, Central America, South America, Europe and Southeast Asia. The yellow areas of the map below show the updated admin 2 areas that were changed: &nbsp;&nbsp;</p>



<figure class="wp-block-image size-full"><img src="https://content.globalforestwatch.org/wp-content/uploads/2025/04/gadm_changes_gold-1.png" alt="" class="wp-image-18783"/></figure>



<h3 class="wp-block-heading">Disputed boundaries</h3>



<p>One major change in this update is that some politically disputed boundaries are no longer included in any country or subnational analysis (note that GADM does not include all disputed boundaries in their data).</p>



<p>With this update, disputed areas are only included in global analysis available on the dashboards. This is because the previous GADM version (3.6) did not delineate disputed boundaries, but GADM 4.1 does: in version 4.1, disputed areas are separated from adjacent admin areas and have their own identification codes. This will mean that the GFW country analyses will no longer include any areas GADM identifies as politically disputed.</p>



<p>For example, the disputed region of Kashmir between China, Pakistan and India is now delineated in version 4.1.</p>



<div class="flourish-embed flourish-photo-slider" data-src="visualisation/22364626?163031"><script src="https://public.flourish.studio/resources/embed.js"></script><noscript><img src="https://public.flourish.studio/visualisation/22364626/thumbnail" width="100%" alt="photo-slider visualization" /></noscript></div>



<h2 class="wp-block-heading">How will this update affect GFW data and statistics?</h2>



<h3 class="wp-block-heading">Analyses</h3>



<p>With this update, any changes in area boundaries will result in some changes to statistics and results of analyses. If you’d like to compare the previous and new version of your admin area, we recommend downloading the 3.6 version for the chosen area via the <a href="https://gadm.org/old_versions.html" target="_blank" rel="noreferrer noopener">GADM site</a> and comparing it to the same area on the GFW map or dashboard. Please see <a href="https://www.globalforestwatch.org/help/map/guides/analyze-data-map/">this article in our Help Center</a> for instructions on how to upload shapefiles<strong><em>.</em></strong></p>



<p>As an example of this type of change, there are now five provinces in Kalimantan, Indonesia instead of four: Kalimantan Timur (East Kalimantan) has split into two areas — <a href="https://www.globalforestwatch.org/dashboards/country/IDN/34/?location=WyJjb3VudHJ5IiwiSUROIiwiMzQiXQ%3D%3D&amp;map=eyJjYW5Cb3VuZCI6dHJ1ZX0%3D">Kalimantan Timur</a> and <a href="https://www.globalforestwatch.org/dashboards/country/IDN/35/?map=eyJjYW5Cb3VuZCI6dHJ1ZX0%3D">Kalimantan Utara (North Kalimantan)</a>.&nbsp;</p>



<h3 class="wp-block-heading">Alert subscriptions and areas saved to MyGFW accounts</h3>



<p>Users will no longer receive alert subscription emails for countries, regions or subregions saved to their MyGFW account before April 29, 2025<strong><em>.</em></strong></p>



<p>To make this change more convenient, we automatically updated political boundaries for saved countries, regions and subregions that maintained the same name between GADM versions 3.6 and 4.1. Users whose areas were automatically updated will receive an email notifying them of this change.</p>



<p>However, if you did not receive an email from us or have multiple saved political boundaries, we recommend that you re-save relevant areas of interest to your MyGFW account:</p>



<ol type="1" start="1">
<li>Navigate to your <a href="https://www.globalforestwatch.org/my-gfw/?utm_medium=email&amp;utm_source=email1&amp;utm_campaign=gadmupdate">MyGFW account</a> and look for areas marked with an “outdated area, notifications paused” tag.</li>



<li>Once you have noted the country, region or subregion that is no longer receiving alert emails, navigate to <a href="https://www.globalforestwatch.org/map/?utm_medium=email&amp;utm_source=email1&amp;utm_campaign=gadmupdate">www.globalforestwatch.org/map</a>.</li>



<li><a href="https://www.globalforestwatch.org/map/?map=eyJkYXRhc2V0cyI6W3siZGF0YXNldCI6InBvbGl0aWNhbC1ib3VuZGFyaWVzIiwibGF5ZXJzIjpbImRpc3B1dGVkLXBvbGl0aWNhbC1ib3VuZGFyaWVzIiwicG9saXRpY2FsLWJvdW5kYXJpZXMiXSwiYm91bmRhcnkiOnRydWUsIm9wYWNpdHkiOjEsInZpc2liaWxpdHkiOnRydWV9XX0%3D&amp;mapMenu=eyJtZW51U2VjdGlvbiI6InNlYXJjaCJ9&amp;utm_medium=email&amp;utm_source=email1&amp;utm_campaign=gadmupdate">Search for the area</a> or navigate to it.</li>



<li>Click on the area, select “analyze,” and then select “save in MyGFW.”</li>



<li>Customize the saved area by selecting a name, tags, alert notifications and more, and then click “save.”</li>
</ol>



<p>You will then continue to receive alert notification emails for this area.</p>



<h3 class="wp-block-heading">Embeds and URLs</h3>



<p>Embeds of and links to countries, regions and subregions on the dashboard and map may now show or link to new areas. This is due to the GADM identification code changing between versions.</p>



<p>If you are using an embed that shows a political boundary, we recommend checking that it still shows the area you originally chose; if the area’s identifier changed, the embed may show an entirely new area.</p>



<h4 class="wp-block-heading">Example from Ghana where the embed shows a new area due to the area identifier changing</h4>



<iframe width="670" height="490" frameborder="0" src="https://www.globalforestwatch.org/embed/map/?mainMap=eyJzaG93QW5hbHlzaXMiOnRydWV9&map=eyJjZW50ZXIiOnsibGF0Ijo2LjkxNjA4ODMwOTEyNDQ2MiwibG5nIjotMC4zOTI1OTAxODgxNzM3Mzk5fSwiem9vbSI6OC42ODQxODM4MTA0ODgzNTMsImNhbkJvdW5kIjpmYWxzZSwiZGF0YXNldHMiOlt7ImRhdGFzZXQiOiJwb2xpdGljYWwtYm91bmRhcmllcyIsImxheWVycyI6WyJkaXNwdXRlZC1wb2xpdGljYWwtYm91bmRhcmllcyIsInBvbGl0aWNhbC1ib3VuZGFyaWVzIl0sImJvdW5kYXJ5Ijp0cnVlLCJvcGFjaXR5IjoxLCJ2aXNpYmlsaXR5Ijp0cnVlfV19&mapMenu=eyJzZWFyY2giOiJzZW5lLCBnaGFuYSJ9&mapPrompts=eyJvcGVuIjp0cnVlLCJzdGVwc0tleSI6InJlY2VudEltYWdlcnkifQ%3D%3D"></iframe>



<p>If you saved a URL that links to a political boundary, we also recommend checking that the URL still shows the desired area of interest. If it does not, follow <a href="https://www.globalforestwatch.org/help/map/guides/how-to-use-map-dashboards/">these instructions</a> on how you can search for an area on the map and dashboards.</p>



<h2 class="wp-block-heading">Where can I ask questions and get help?</h2>



<p>The GFW team aims to provide the latest forest monitoring updates for users and support your use of the GFW platform, and we highly value your feedback. If you have feedback on these changes or need help, please contact us at <a href="mailto:gfw@wri.org">gfw@wri.org.</a></p>



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Global Forest Watch Has Updated Political Boundaries — Here's What You Should Know

We’ve updated the political boundaries available on GFW using the latest and most accurate information. Learn about the changes in our blog.

Global Forest Watch has Updated Political Boundaries

Global Forest Watch Has Updated Political Boundaries — Here&#8217;s What You Should Know

<h3 class="wp-block-heading">Did you use Planet satellite imagery on GFW? Please tell us how this change affects you in our <a href="https://survey.alchemer.com/s3/8260607/Planet-blog" target="_blank" rel="noreferrer noopener">short survey here</a>.</h3>



<p>Recent, high-resolution satellite imagery is essential for providing context to other data layers available on Global Forest Watch (GFW), such as interpreting drivers of tree cover change, identifying possible causes of near-real-time deforestation alerts, and in validation protocols to assess accuracy of land and forest cover and change products.</p>



<p>Launched in 2020, Norway’s International Climate and Forest Initiative (NICFI) partnered with Planet and Kongsberg Satellite Services (KSAT) to provide high-resolution Planet imagery for free, including on GFW, through their Satellite Data Program.</p>



<p>However, the current phase of the program has ended, and <strong>Planet imagery is no longer available on GFW as of April 1, 2025</strong> — but GFW will continue to provide other satellite imagery. Here is what you need to know.</p>



<h2 class="wp-block-heading">What is Planet imagery?</h2>



<p>Planet’s high-resolution, analysis-ready mosaics (single images that combine multiple satellite images) of the world’s tropics are natural color images using information from visible light (red, green and blue) to show Earth’s surface as it would appear to the human eye. They are available biannually from December 2015 – May 2020, quarterly for June 2020 – August 2020, and monthly since September 2020.</p>



<p>Over the last few years, many GFW users have benefitted from Planet data, such as organizations like Mighty Earth and HAkA <a href="https://www.globalforestwatch.org/blog/people/video-patrol-leuser-ecosystem-forest-defenders-haka/">combatting illegal deforestation</a>, those <a href="https://www.globalforestwatch.org/blog/data-and-tools/satellite-data-eu-regulation-deforestation-free-supply-chains/">responding to policies such as EUDR</a>, and those reporting on deforestation and other critical forest-related news like Mongabay.</p>



<h2 class="wp-block-heading">What are the changes to Planet on GFW?</h2>



<p><strong>Planet imagery was removed from GFW on April 1, 2025.</strong> This means that as of April 1, new Planet mosaics AND historical mosaics are no longer available on GFW.</p>



<h2 class="wp-block-heading">What alternative satellite imagery can I use on GFW?</h2>



<p>GFW offers several other imagery sources that are already available to users and can be used to support their work. If resolution is most important, <a href="https://gfw.global/4hQKGAQ">Google satellite imagery</a>, which is available globally for the past 1-3 years, has a resolution that ranges from 15 meters to 15 centimeters depending on the location. For alternative sources of recent data, imagery from the <a href="https://gfw.global/4l7PnJi">Landsat 8 (30-meter resolution) and Sentinel-2A (10-meter resolution)</a> satellites is also available since 2012 and is updated daily on GFW.</p>



<p>Since all imagery has different characteristics (e.g. time periods available and update frequency), users should assess which is most suited to their needs.</p>



<p>To learn more about how to use the satellite imagery currently available on GFW to investigate forest change please <a href="https://www.globalforestwatch.org/help/map/guides/investigate-forest-change-satellite-imagery/">visit our Help Center</a>.</p>



<h2 class="wp-block-heading">Will new satellite imagery be available through the NICFI program in the future?</h2>



<p>NICFI plans to continue the Satellite Data Program, however, they are in the process of developing a new phase, to be launched later this year. As part of this process, NICFI is evaluating satellite data providers as well as other details of the program (such as frequency and type of data).</p>



<p>Once NICFI is ready to launch the new phase of the Satellite Data Program, GFW will explore whether we will add any new satellite imagery to the platform.</p>



<h2 class="wp-block-heading">How can I stay updated on these changes?</h2>



<p>To stay up to date with the latest developments on the NICFI Satellite Data Program, please sign up for the&nbsp;<a href="https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.nicfi.no%2Fnewsletter%2F&data=05%7C02%7CIsabela.Barriga%40wri.org%7C51c383e67cd4426038fd08dd3a349078%7C476bac1f36b24ad98699cda6bad1f862%7C0%7C0%7C638730719665838145%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=qcUFo47GOA4SkhXMOI8EvdXKIUlFp4b1KpOYWi%2FjD2Y%3D&reserved=0" target="_blank" rel="noreferrer noopener">NICFI newsletter</a>. You can learn more about Planet in their <a href="https://support.planet.com/hc/en-us" target="_blank" rel="noreferrer noopener">Help Center</a>.</p>



<p>We will also update this blog as new information is available. You can always see the latest updates about data changes and outages in the notifications on the GFW main menu:</p>



<figure class="wp-block-image size-full"><img decoding="async" loading="lazy" width="1738" height="902" src="https://content.globalforestwatch.org/wp-content/uploads/2025/03/GFW-notice-board.png" alt="" class="wp-image-18675" srcset="https://content.globalforestwatch.org/wp-content/uploads/2025/03/GFW-notice-board.png 1738w, https://content.globalforestwatch.org/wp-content/uploads/2025/03/GFW-notice-board-1024x531.png 1024w, https://content.globalforestwatch.org/wp-content/uploads/2025/03/GFW-notice-board-768x399.png 768w, https://content.globalforestwatch.org/wp-content/uploads/2025/03/GFW-notice-board-1536x797.png 1536w" sizes="(max-width: 1738px) 100vw, 1738px" /></figure>



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Planet Imagery is No Longer Available on GFW — Here’s What You Should Know

<h3 class="wp-block-heading">Did you use Planet satellite imagery on GFW? Please tell us how this change affects you in our <a href="https://survey.alchemer.com/s3/8260607/Planet-blog" target="_blank" rel="noreferrer noopener">short survey here</a>.</h3>



<p>Recent, high-resolution satellite imagery is essential for providing context to other data layers available on Global Forest Watch (GFW), such as interpreting drivers of tree cover change, identifying possible causes of near-real-time deforestation alerts, and in validation protocols to assess accuracy of land and forest cover and change products.</p>



<p>Launched in 2020, Norway’s International Climate and Forest Initiative (NICFI) partnered with Planet and Kongsberg Satellite Services (KSAT) to provide high-resolution Planet imagery for free, including on GFW, through their Satellite Data Program.</p>



<p>However, the current phase of the program has ended, and <strong>Planet imagery is no longer available on GFW as of April 1, 2025</strong> — but GFW will continue to provide other satellite imagery. Here is what you need to know.</p>



<h2 class="wp-block-heading">What is Planet imagery?</h2>



<p>Planet’s high-resolution, analysis-ready mosaics (single images that combine multiple satellite images) of the world’s tropics are natural color images using information from visible light (red, green and blue) to show Earth’s surface as it would appear to the human eye. They are available biannually from December 2015 - May 2020, quarterly for June 2020 - August 2020, and monthly since September 2020.</p>



<p>Over the last few years, many GFW users have benefitted from Planet data, such as organizations like Mighty Earth and HAkA <a href="https://www.globalforestwatch.org/blog/people/video-patrol-leuser-ecosystem-forest-defenders-haka/">combatting illegal deforestation</a>, those <a href="https://www.globalforestwatch.org/blog/data-and-tools/satellite-data-eu-regulation-deforestation-free-supply-chains/">responding to policies such as EUDR</a>, and those reporting on deforestation and other critical forest-related news like Mongabay.</p>



<h2 class="wp-block-heading">What are the changes to Planet on GFW?</h2>



<p><strong>Planet imagery was removed from GFW on April 1, 2025.</strong> This means that as of April 1, new Planet mosaics AND historical mosaics are no longer available on GFW.</p>



<h2 class="wp-block-heading">What alternative satellite imagery can I use on GFW?</h2>



<p>GFW offers several other imagery sources that are already available to users and can be used to support their work. If resolution is most important, <a href="https://gfw.global/4hQKGAQ">Google satellite imagery</a>, which is available globally for the past 1-3 years, has a resolution that ranges from 15 meters to 15 centimeters depending on the location. For alternative sources of recent data, imagery from the <a href="https://gfw.global/4l7PnJi">Landsat 8 (30-meter resolution) and Sentinel-2A (10-meter resolution)</a> satellites is also available since 2012 and is updated daily on GFW.</p>



<p>Since all imagery has different characteristics (e.g. time periods available and update frequency), users should assess which is most suited to their needs.</p>



<p>To learn more about how to use the satellite imagery currently available on GFW to investigate forest change please <a href="https://www.globalforestwatch.org/help/map/guides/investigate-forest-change-satellite-imagery/">visit our Help Center</a>.</p>



<h2 class="wp-block-heading">Will new satellite imagery be available through the NICFI program in the future?</h2>



<p>NICFI plans to continue the Satellite Data Program, however, they are in the process of developing a new phase, to be launched later this year. As part of this process, NICFI is evaluating satellite data providers as well as other details of the program (such as frequency and type of data).</p>



<p>Once NICFI is ready to launch the new phase of the Satellite Data Program, GFW will explore whether we will add any new satellite imagery to the platform.</p>



<h2 class="wp-block-heading">How can I stay updated on these changes?</h2>



<p>To stay up to date with the latest developments on the NICFI Satellite Data Program, please sign up for the&nbsp;<a href="https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.nicfi.no%2Fnewsletter%2F&amp;data=05%7C02%7CIsabela.Barriga%40wri.org%7C51c383e67cd4426038fd08dd3a349078%7C476bac1f36b24ad98699cda6bad1f862%7C0%7C0%7C638730719665838145%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&amp;sdata=qcUFo47GOA4SkhXMOI8EvdXKIUlFp4b1KpOYWi%2FjD2Y%3D&amp;reserved=0" target="_blank" rel="noreferrer noopener">NICFI newsletter</a>. You can learn more about Planet in their <a href="https://support.planet.com/hc/en-us" target="_blank" rel="noreferrer noopener">Help Center</a>.</p>



<p>We will also update this blog as new information is available. You can always see the latest updates about data changes and outages in the notifications on the GFW main menu:</p>



<figure class="wp-block-image size-full"><img src="https://content.globalforestwatch.org/wp-content/uploads/2025/03/GFW-notice-board.png" alt="" class="wp-image-18675"/></figure>



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Planet Imagery is No Longer Available on GFW — Here's What You Should Know

<h3 class="wp-block-heading"><strong><em>Apakah Anda menggunakan citra satelit Planet di GFW? Beritahu kami bagaimana perubahan ini mempengaruhi Anda dalam </em></strong><a href="https://survey.alchemer.com/s3/8260607/Planet-blog" target="_blank" rel="noreferrer noopener"><strong><em>survei singkat kami di sini</em></strong></a><strong><em>.</em></strong> </h3>



<p>Citra satelit resolusi tinggi terbaru sangat penting untuk memberikan konteks pada lapisan data lain yang tersedia di Global Forest Watch (GFW), seperti menginterpretasikan faktor pendorong perubahan tutupan pohon, mengidentifikasi kemungkinan penyebab peringatan deforestasi secara nyaris seketika, serta digunakan dalam proses validasi awal untuk menilai akurasi data tutupan dan perubahan hutan dan lahan.&nbsp;&nbsp;</p>



<p>Diluncurkan pada 2020, Inisiatif Iklim dan Hutan Internasional Norwegia (NICFI) bekerja sama dengan Planet dan Kongsberg Satellite Services (KSAT) untuk menyediakan citra resolusi tinggi dari Planet secara gratis, termasuk melalui platform GFW, lewat program mereka yang bernama Program Data Satelit.  </p>



<p>Namun, saat ini program tersebut telah berakhir, dan citra Planet tidak lagi tersedia di GFW per 1 April 2025, tetapi GFW akan terus menyediakan citra satelit lainnya. Inilah yang perlu Anda ketahui.&nbsp;</p>



<h2 class="wp-block-heading">Apa yang dimaksud dengan citra Planet? </h2>



<p>Citra Planet adalah mosaik resolusi tinggi yang siap dianalisis, yaitu gabungan dari beberapa citra satelit menjadi satu gambar utuh. Citra ini menampilkan kawasan tropis dalam warna alami, menggunakan kombinasi cahaya tampak (merah, hijau, dan biru) sehingga permukaan Bumi terlihat seperti yang tampak oleh mata manusia. Citra ini tersedia dua kali setahun dari Desember 2015 hingga Mei 2020, empat kali setahun pada periode Juni-Agustus 2020, dan setiap bulan sejak September 2020.&nbsp;</p>



<p>Selama beberapa tahun terakhir, banyak pengguna GFW yang telah mendapatkan manfaat dari data Planet. Misalnya, organisasi seperti Mighty Earth dan Yayasan Hutan, Alam, dan Lingkungan Aceh (HAkA) <a href="https://www.globalforestwatch.org/blog/people/video-patrol-leuser-ecosystem-forest-defenders-haka/" target="_blank" rel="noreferrer noopener">dalam memerangi deforestasi</a>, para pihak yang <a href="https://www.globalforestwatch.org/blog/data-and-tools/satellite-data-eu-regulation-deforestation-free-supply-chains/" target="_blank" rel="noreferrer noopener">merespons kebijakan seperti EUDR</a>, serta media seperti Mongabay yang melaporkan deforestasi dan isu penting lainnya terkait hutan.&nbsp;</p>



<h2 class="wp-block-heading">Apa saja perubahan yang terjadi pada Citra Planet di GFW? </h2>



<p><strong>Mulai 1 April 2025, citra Planet telah dihapus dari platform GFW</strong>. Artinya, sejak tanggal tersebut, baik mosaik Planet terbaru DAN arsip mosaik sebelumnya sudah tidak lagi tersedia di GFW. </p>



<h2 class="wp-block-heading">Citra satelit alternatif apa yang dapat saya gunakan di GFW? </h2>



<p>GFW masih menyediakan beberapa sumber citra satelit lain yang&nbsp; yang dapat digunakan untuk mendukung pekerjaan pengguna. Jika resolusi menjadi prioritas utama, <a href="https://gfw.global/4hQKGAQ" target="_blank" rel="noreferrer noopener">citra satelit Google</a> bisa menjadi pilihan. Citra ini tersedia secara global untuk kurun waktu 1-3 tahun terakhir dengan resolusi yang berkisar antara 15 meter hingga 15 sentimeter tergantung pada lokasinya. Untuk sumber alternatif data terbaru, GFW juga menyediakan citra dari satelit <a href="https://gfw.global/4l7PnJi" target="_blank" rel="noreferrer noopener">Landsat 8 (resolusi 30 meter) dan Sentinel-2A (resolusi 10 meter)</a> yang tersedia sejak tahun 2012 dan diperbarui setiap hari di GFW.&nbsp;</p>



<p>Karena masing-masing sumber citra satelit memiliki karakteristik yang berbeda (misalnya periode waktu yang tersedia dan frekuensi pembaruan), pengguna disarankan untuk menyesuaikan pilihan berdasarkan kebutuhan masing-masing.&nbsp;</p>



<p>Untuk mempelajari lebih lanjut mengenai cara menggunakan citra satelit yang tersedia di GFW untuk menginvestigasi perubahan hutan, silakan kunjungi <a href="https://www.globalforestwatch.org/help/map/guides/investigate-forest-change-satellite-imagery/" target="_blank" rel="noreferrer noopener">Pusat Bantuan kami</a>.&nbsp;</p>



<h2 class="wp-block-heading">Apakah akan ada citra satelit baru dari program NICFI di masa depan? </h2>



<p>NICFI berencana untuk melanjutkan Program Data Satelit, namun saat ini mereka sedang mempersiapkan fase baru yang akan diluncurkan akhir tahun ini. Dalam proses ini, NICFI sedang mengevaluasi penyedia data satelit serta berbagai aspek lain dari programnya, seperti frekuensi pembaruan dan jenis data yang akan disediakan.&nbsp;&nbsp;</p>



<p>Setelah NICFI siap untuk meluncurkan fase baru dari Program Data Satelit, GFW akan mempertimbangkan kemungkinan untuk menambahkan citra satelit baru ke dalam platform ini.</p>



<h2 class="wp-block-heading">Bagaimana cara saya tetap mendapatkan informasi terbaru terkait perubahan ini? </h2>



<p>Untuk mengikuti perkembangan terbaru dari Program Data Satelit NICFI, silakan mendaftar ke <a href="https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.nicfi.no%2Fnewsletter%2F&amp;data=05%7C02%7CIsabela.Barriga%40wri.org%7C51c383e67cd4426038fd08dd3a349078%7C476bac1f36b24ad98699cda6bad1f862%7C0%7C0%7C638730719665838145%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&amp;sdata=qcUFo47GOA4SkhXMOI8EvdXKIUlFp4b1KpOYWi%2FjD2Y%3D&amp;reserved=0" target="_blank" rel="noreferrer noopener">buletin NICFI</a>. Anda juga bisa mempelajari lebih lanjut tentang Planet melalui <a href="https://support.planet.com/hc/en-us" target="_blank" rel="noreferrer noopener">Pusat Bantuan</a> mereka.&nbsp;</p>



<p>Kami akan terus memperbarui blog ini seiring dengan ketersediaan informasi baru. Selain itu, Anda juga bisa melihat update terkini mengenai perubahan data atau gangguan layanan melalui notifikasi pada menu utama GFW:&nbsp;</p>



<figure class="wp-block-image size-full"><img src="https://content.globalforestwatch.org/wp-content/uploads/2025/03/GFW-notice-board.png" alt="" class="wp-image-18675"/></figure>



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Citra Planet Tidak Lagi Tersedia di GFW - Inilah yang Harus Anda Ketahui 

Planet imagery is no longer available on GFW as of April 1 2025, but GFW continues to provide other satellite imagery. Here's what you should know.

Planet Imagery is No Longer Available on GFW — Here&#8217;s What You Should Know

forest change

forest change | Global Forest Watch Blog

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=eyJ2aWV3U3RhdGUiOnsibGF0aXR1ZGUiOjAsImxvbmdpdHVkZSI6MCwiem9vbSI6MywiYmVhcmluZyI6MCwicGl0Y2giOjAsInBhZGRpbmciOnsidG9wIjowLCJib3R0b20iOjAsImxlZnQiOjAsInJpZ2h0IjowfX0sImJhc2VtYXAiOiJsaWdodCIsImJvdW5kYXJpZXMiOmZhbHNlLCJsYWJlbHMiOiJkYXJrIiwiYWN0aXZlTGF5ZXJHcm91cHMiOlt7ImRhdGFzZXRJZCI6IjgwYjhmNGYzLWNlZGItNDg5My04N2I4LTllM2VjNGE0MGMzMyIsImxheWVycyI6WyIzYzcyMmE0MC04NWVlLTQ1NDQtYTg1MC02MDdkNDljYzliMTgiXX1dLCJib3VuZHMiOnsiYmJveCI6bnVsbCwib3B0aW9ucyI6e319LCJsYXllcnNQYXJzZWQiOltbIjNjNzIyYTQwLTg1ZWUtNDU0NC1hODUwLTYwN2Q0OWNjOWIxOCIseyJ2aXNpYmlsaXR5Ijp0cnVlLCJhY3RpdmUiOnRydWUsIm9wYWNpdHkiOjEsInpJbmRleCI6MTF9XV19" 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 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>



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<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

Oil palm plantation in Sentabai Village, West Kalimantan, Indonesia.

Jessica Richter

Nancy Harris

<p>Determining the boundaries of different forest types allows us to better understand how forests are changing over time. A longstanding limitation of the tree cover data available on Global Forest Watch (GFW) has been the inability to differentiate planted forests and tree crops from primary and secondary natural forests. There is no globally consistent data available on the location of planted trees, making it difficult to determine whether tree cover change occurred in natural forest or if it was simply harvesting or management activities in planted trees.</p>



<p>In 2019, GFW and World Resources Institute published the original Spatial Database of Planted Trees (SDPT) to fill this data gap by compiling data sources on planted tree boundaries across the globe. This effort allowed GFW users to view the location of planted trees on the GFW map and focus tree cover loss and gain statistics on change inside or outside planted tree areas.</p>



<p>Now, a new version of the SDPT is <a href="https://gfw.global/2Qbv7fM">available on GFW</a>, which provides broader geographic coverage and several key updates that improve its application to global forest monitoring and management.</p>



<h2 class="wp-block-heading">What is the Spatial Database of Planted Trees (SDPT)?</h2>



<p>The SDPT aims to spatially differentiate planted forests and tree crops from natural and seminatural forests on a global scale. We conducted extensive research and outreach to governments, civil society organizations and researchers to compile, synthesize and integrate national and regional data sources of the world’s planted trees into the SDPT.</p>



<figure class="wp-block-image size-large"><img decoding="async" loading="lazy" width="2048" height="1495" src="https://content.globalforestwatch.org/wp-content/uploads/2024/11/23_GRAPHIC-GFW-blog-SPDT-spatial-database-planted-trees_V2-2048x1495.png" alt="Table showing definitions of planted trees, planted forest and tree crops as defined in the Spatial Database of Planted Trees" class="wp-image-18224" srcset="https://content.globalforestwatch.org/wp-content/uploads/2024/11/23_GRAPHIC-GFW-blog-SPDT-spatial-database-planted-trees_V2-2048x1495.png 2048w, https://content.globalforestwatch.org/wp-content/uploads/2024/11/23_GRAPHIC-GFW-blog-SPDT-spatial-database-planted-trees_V2-1024x748.png 1024w, https://content.globalforestwatch.org/wp-content/uploads/2024/11/23_GRAPHIC-GFW-blog-SPDT-spatial-database-planted-trees_V2-768x561.png 768w, https://content.globalforestwatch.org/wp-content/uploads/2024/11/23_GRAPHIC-GFW-blog-SPDT-spatial-database-planted-trees_V2-1536x1121.png 1536w" sizes="(max-width: 2048px) 100vw, 2048px" /></figure>



<p>The SDPT includes key information on each integrated data set, including the planted tree type (planted forest vs. tree crop), original data source information and carbon removal factors — or the rate at which planted trees remove atmospheric carbon dioxide and store it in biomass. Where available, the SDPT also includes species information, as well as the method and year(s) of imagery used to determine the planted tree boundary.</p>



<p>The SDPT was established as a living database that will continue to evolve as new data becomes available. The recent publication of an updated version of SDPT (<a href="https://www.wri.org/research/spatial-database-planted-trees-sdpt-version-2" target="_blank" rel="noreferrer noopener">v2.0</a>) reflects this aim and provides significant updates to the initial (<a href="https://www.wri.org/research/spatial-database-planted-trees-sdpt-version-10" target="_blank" rel="noreferrer noopener">v1.0</a>) database.</p>



<p>Users can download the v2.0 database <a href="https://gfw2-data.s3.amazonaws.com/plantations/sdpt/sdpt_v2.zip">here</a>. The SDPT is also available as the <a href="https://gfw.global/2Qbv7fM">tree plantation</a> layer on the GFW map and is included in several analyses on the GFW dashboard.</p>



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<aside id="textbox"><em><b>Comparing the SDPT to Forest Resources Assessment Reporting</b><p></p>
The record of planted forest statistics provided in the <a href="https://www.globalforestwatch.org/blog/data-and-research/global-forest-watch-and-the-forest-resources-assessment-explained-in-5-graphics-2/" target="_blank" rel="noopener noreferrer">Food and Agriculture Organization of the United Nations’ (FAO)</a> <a href="https://www.fao.org/3/ca9825en/ca9825en.pdf" target="_blank" rel="noopener noreferrer">Forest Resources Assessment (FRA)</a> every five years serves as an important baseline of comparison to the SDPT. However, data sets included in the SDPT may not adhere to the definitions used by FAO as there are no universal definitions for the terms “planted trees,” “planted forests” and “tree crops.” In the SDPT, we focused on including data sets, or classes within data sets, that used the terms “plantation,” “plantation forest” or “planted forest,” which we classified under the term planted forest. The SDPT also includes maps of agroforestry systems and various perennial tree crops such as rubber, oil palm, coffee, coconut, cocoa and orchards, which we classified under the term tree crop. FAO instead uses the terms planted forest and plantation, defining planted forest as “forest predominantly composed of trees established through planting and/or deliberate seeding” and plantation as “planted forest that is intensively managed and meet ALL the following criteria at planting and stand maturity: one or two species, even age class, and regular spacing.” FAO’s reporting of planted forests does not include tree crop systems, so we compared FAO’s planted forest statistics to SDPT data classified as planted forest. The SDPT is not intended to resolve definitional debate surrounding these terms but rather to synthesize data.
</em> </aside>



<h2 class="wp-block-heading">What’s new in SDPT version 2.0?</h2>





<p>A range of <a href="https://www.wri.org/research/spatial-database-planted-trees-sdpt-version-2" target="_blank" rel="noreferrer noopener">improvements have been made</a> to the SDPT in v2.0 based on new global and national data sources. These include:</p>



<p><strong>1. Near-global coverage</strong></p>



<p>Coverage in v2.0 has expanded from 82 countries in v1.0 to a total of 158 countries represented. Based on the newly compiled data, v2.0 reports approximately 329 million hectares (Mha) of planted trees worldwide in 2020, made up of 264 Mha of planted forests and 65 Mha of tree crops. This represents 8% of total global tree cover (an area roughly the size of India).</p>



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<p><strong>2. Tree species information</strong></p>



<p>SDPT v2.0 added or updated tree species information for 39 countries and now includes species-level information for 52 out of the 158 countries covered. Users can view available species information by <a href="https://gfw2-data.s3.amazonaws.com/plantations/sdpt/sdpt_v2.zip">downloading the database</a> and referencing the <em>sciName</em> data attribute.</p>



<p><strong>3. Planting year information</strong></p>



<p>A new planting year attribute has been added to the database that provides the latest approximate year that an individual area was planted. Researchers at Tsinghua University were able to detect the year of planting in SDPT v2.0 using the <a href="https://www.nature.com/articles/s41597-022-01260-2" target="_blank" rel="noreferrer noopener">LandTrendr algorithm</a> on a time series of Landsat images from 1982 to 2020. Results from this analysis were added to each planted tree area and are available by <a href="https://gfw2-data.s3.amazonaws.com/plantations/sdpt/sdpt_v2.zip">downloading the database</a> and referencing the <em>plantedYear </em>data attribute.</p>



<p><strong>4. Carbon removal factors</strong></p>



<p>Carbon removal factors, or carbon sequestration rates, have been assigned to planted trees represented in SDPT v2.0 that were not included in v1.0. In addition to carbon removal factors for aboveground biomass, belowground biomass and the standard deviations of removal factors, the database includes notes on methods and sources for each removal factor. Users can access carbon removal factor information by <a href="https://gfw2-data.s3.amazonaws.com/plantations/sdpt/sdpt_v2.zip">downloading the database</a> and referencing attributes such as <em>removalFactorAGCBGCMgHaYr</em>, <em>removalFactorAGCBGCstdevMgHaYr</em>, <em>removalFactorSource</em> and <em>removalFactorNotes</em>.</p>



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



<p>The SDPT exists first and foremost to differentiate the geographic extent of planted trees from natural forests on a global scale, leading to easier identification of “natural forest” areas. Already, SDPT v2.0 is being used as an input layer into the Science Based Targets Network (SBTN) <a href="https://landcarbonlab.org/insights/natural-lands-map-companies-no-conversion-targets/" target="_blank" rel="noreferrer noopener">Natural Lands Map</a> to filter out planted forests and produce a natural forest class.</p>



<p>Specific SDPT attributes, such as species information, also have important global applications. Enforcement actors, such as United States government customs agencies, can use SDPT species information to expedite inspections of timber shipments. The database can help confirm whether there are other planted timber forests of the same species within the stated country of origin, as this impacts the legality of the import. The removal factors can be used to estimate carbon sequestration rates over large areas of planted trees where plot-level carbon measurements are not available.</p>



<p>Beyond these specific applications, the SDPT has implications for global forest monitoring and management. It can aid in tracking where and when planted trees may be replacing natural forests and help monitor the impact of these planted forests across diverse landscapes. This can lead to more effective tracking of national and global progress towards major international commitments associated with forests, climate and biodiversity.</p>



<h2 class="wp-block-heading">Future plans for the SDPT</h2>



<p>While major challenges remain in mapping planted trees, we expect to see continued, significant advances in large-scale planted tree mapping as well as improvements to national- and regional-scale data over time. The SDPT will continue to integrate these sources across all scales to provide users with the most detailed spatial information available. Incorporating more species-specific data into the SDPT is a key part of this effort. This includes species information taken directly from image-interpreted data sets as well as integrating non-spatial species information derived from literature reviews.</p>



<p>Users can <a href="https://www.wri.org/research/spatial-database-planted-trees-sdpt-version-2" target="_blank" rel="noreferrer noopener">explore the tree plantations layer on GFW</a> and can <a href="https://gfw2-data.s3.amazonaws.com/plantations/sdpt/sdpt_v2.zip">download the data</a><em>. </em>For more information on the SDPT v2.0 update, <a href="https://www.wri.org/research/spatial-database-planted-trees-sdpt-version-2">read the technical note here</a>.</p>



<p><em>The SDPT compiles data from a variety of sources. If you have spatial data on planted trees that you think should be incorporated into the data set, </em><a href="https://forms.gle/pUzJy72N7szVMydg9" target="_blank" rel="noreferrer noopener"><em>please let us know here</em></a><em>.</em></p>



<p><em>Additional minor updates have been made to the SDPT in a version 2.1 incorporating new data in Brazil, Cambodia, Cote d’Ivoire and Ghana. </em><a href="https://gfw-files.s3.amazonaws.com/plantations/SDPT_v2.1/sdpt_v21_v09152024_public.gdb.zip"><em>Access the latest version here</em></a><em>.</em></p>



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Updated Planted Trees Map Reaches Near-Global Coverage

<p>Determining the boundaries of different forest types allows us to better understand how forests are changing over time. A longstanding limitation of the tree cover data available on Global Forest Watch (GFW) has been the inability to differentiate planted forests and tree crops from primary and secondary natural forests. There is no globally consistent data available on the location of planted trees, making it difficult to determine whether tree cover change occurred in natural forest or if it was simply harvesting or management activities in planted trees.</p>



<p>In 2019, GFW and World Resources Institute published the original Spatial Database of Planted Trees (SDPT) to fill this data gap by compiling data sources on planted tree boundaries across the globe. This effort allowed GFW users to view the location of planted trees on the GFW map and focus tree cover loss and gain statistics on change inside or outside planted tree areas.</p>



<p>Now, a new version of the SDPT is <a href="https://gfw.global/2Qbv7fM">available on GFW</a>, which provides broader geographic coverage and several key updates that improve its application to global forest monitoring and management.</p>



<h2 class="wp-block-heading">What is the Spatial Database of Planted Trees (SDPT)?</h2>



<p>The SDPT aims to spatially differentiate planted forests and tree crops from natural and seminatural forests on a global scale. We conducted extensive research and outreach to governments, civil society organizations and researchers to compile, synthesize and integrate national and regional data sources of the world’s planted trees into the SDPT.</p>



<figure class="wp-block-image size-large"><img src="https://content.globalforestwatch.org/wp-content/uploads/2024/11/23_GRAPHIC-GFW-blog-SPDT-spatial-database-planted-trees_V2-2048x1495.png" alt="Table showing definitions of planted trees, planted forest and tree crops as defined in the Spatial Database of Planted Trees" class="wp-image-18224"/></figure>



<p>The SDPT includes key information on each integrated data set, including the planted tree type (planted forest vs. tree crop), original data source information and carbon removal factors — or the rate at which planted trees remove atmospheric carbon dioxide and store it in biomass. Where available, the SDPT also includes species information, as well as the method and year(s) of imagery used to determine the planted tree boundary.</p>



<p>The SDPT was established as a living database that will continue to evolve as new data becomes available. The recent publication of an updated version of SDPT (<a href="https://www.wri.org/research/spatial-database-planted-trees-sdpt-version-2" target="_blank" rel="noreferrer noopener">v2.0</a>) reflects this aim and provides significant updates to the initial (<a href="https://www.wri.org/research/spatial-database-planted-trees-sdpt-version-10" target="_blank" rel="noreferrer noopener">v1.0</a>) database.</p>



<p>Users can download the v2.0 database <a href="https://gfw2-data.s3.amazonaws.com/plantations/sdpt/sdpt_v2.zip">here</a>. The SDPT is also available as the <a href="https://gfw.global/2Qbv7fM">tree plantation</a> layer on the GFW map and is included in several analyses on the GFW dashboard.</p>



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<aside id="textbox"><em><b>Comparing the SDPT to Forest Resources Assessment Reporting</b><p></p>
The record of planted forest statistics provided in the <a href="https://www.globalforestwatch.org/blog/data-and-research/global-forest-watch-and-the-forest-resources-assessment-explained-in-5-graphics-2/" target="_blank" rel="noopener noreferrer">Food and Agriculture Organization of the United Nations' (FAO)</a> <a href="https://www.fao.org/3/ca9825en/ca9825en.pdf" target="_blank" rel="noopener noreferrer">Forest Resources Assessment (FRA)</a> every five years serves as an important baseline of comparison to the SDPT. However, data sets included in the SDPT may not adhere to the definitions used by FAO as there are no universal definitions for the terms “planted trees,” “planted forests” and “tree crops.” In the SDPT, we focused on including data sets, or classes within data sets, that used the terms “plantation,” “plantation forest” or “planted forest,” which we classified under the term planted forest. The SDPT also includes maps of agroforestry systems and various perennial tree crops such as rubber, oil palm, coffee, coconut, cocoa and orchards, which we classified under the term tree crop. FAO instead uses the terms planted forest and plantation, defining planted forest as “forest predominantly composed of trees established through planting and/or deliberate seeding” and plantation as “planted forest that is intensively managed and meet ALL the following criteria at planting and stand maturity: one or two species, even age class, and regular spacing.” FAO’s reporting of planted forests does not include tree crop systems, so we compared FAO’s planted forest statistics to SDPT data classified as planted forest. The SDPT is not intended to resolve definitional debate surrounding these terms but rather to synthesize data.
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<h2 class="wp-block-heading">What’s new in SDPT version 2.0?</h2>





<p>A range of <a href="https://www.wri.org/research/spatial-database-planted-trees-sdpt-version-2" target="_blank" rel="noreferrer noopener">improvements have been made</a> to the SDPT in v2.0 based on new global and national data sources. These include:</p>



<p><strong>1. Near-global coverage</strong></p>



<p>Coverage in v2.0 has expanded from 82 countries in v1.0 to a total of 158 countries represented. Based on the newly compiled data, v2.0 reports approximately 329 million hectares (Mha) of planted trees worldwide in 2020, made up of 264 Mha of planted forests and 65 Mha of tree crops. This represents 8% of total global tree cover (an area roughly the size of India).</p>



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<p><strong>2. Tree species information</strong></p>



<p>SDPT v2.0 added or updated tree species information for 39 countries and now includes species-level information for 52 out of the 158 countries covered. Users can view available species information by <a href="https://gfw2-data.s3.amazonaws.com/plantations/sdpt/sdpt_v2.zip">downloading the database</a> and referencing the <em>sciName</em> data attribute.</p>



<p><strong>3. Planting year information</strong></p>



<p>A new planting year attribute has been added to the database that provides the latest approximate year that an individual area was planted. Researchers at Tsinghua University were able to detect the year of planting in SDPT v2.0 using the <a href="https://www.nature.com/articles/s41597-022-01260-2" target="_blank" rel="noreferrer noopener">LandTrendr algorithm</a> on a time series of Landsat images from 1982 to 2020. Results from this analysis were added to each planted tree area and are available by <a href="https://gfw2-data.s3.amazonaws.com/plantations/sdpt/sdpt_v2.zip">downloading the database</a> and referencing the <em>plantedYear </em>data attribute.</p>



<p><strong>4. Carbon removal factors</strong></p>



<p>Carbon removal factors, or carbon sequestration rates, have been assigned to planted trees represented in SDPT v2.0 that were not included in v1.0. In addition to carbon removal factors for aboveground biomass, belowground biomass and the standard deviations of removal factors, the database includes notes on methods and sources for each removal factor. Users can access carbon removal factor information by <a href="https://gfw2-data.s3.amazonaws.com/plantations/sdpt/sdpt_v2.zip">downloading the database</a> and referencing attributes such as <em>removalFactorAGCBGCMgHaYr</em>, <em>removalFactorAGCBGCstdevMgHaYr</em>, <em>removalFactorSource</em> and <em>removalFactorNotes</em>.</p>



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



<p>The SDPT exists first and foremost to differentiate the geographic extent of planted trees from natural forests on a global scale, leading to easier identification of “natural forest” areas. Already, SDPT v2.0 is being used as an input layer into the Science Based Targets Network (SBTN) <a href="https://landcarbonlab.org/insights/natural-lands-map-companies-no-conversion-targets/" target="_blank" rel="noreferrer noopener">Natural Lands Map</a> to filter out planted forests and produce a natural forest class.</p>



<p>Specific SDPT attributes, such as species information, also have important global applications. Enforcement actors, such as United States government customs agencies, can use SDPT species information to expedite inspections of timber shipments. The database can help confirm whether there are other planted timber forests of the same species within the stated country of origin, as this impacts the legality of the import. The removal factors can be used to estimate carbon sequestration rates over large areas of planted trees where plot-level carbon measurements are not available.</p>



<p>Beyond these specific applications, the SDPT has implications for global forest monitoring and management. It can aid in tracking where and when planted trees may be replacing natural forests and help monitor the impact of these planted forests across diverse landscapes. This can lead to more effective tracking of national and global progress towards major international commitments associated with forests, climate and biodiversity.</p>



<h2 class="wp-block-heading">Future plans for the SDPT</h2>



<p>While major challenges remain in mapping planted trees, we expect to see continued, significant advances in large-scale planted tree mapping as well as improvements to national- and regional-scale data over time. The SDPT will continue to integrate these sources across all scales to provide users with the most detailed spatial information available. Incorporating more species-specific data into the SDPT is a key part of this effort. This includes species information taken directly from image-interpreted data sets as well as integrating non-spatial species information derived from literature reviews.</p>



<p>Users can <a href="https://www.wri.org/research/spatial-database-planted-trees-sdpt-version-2" target="_blank" rel="noreferrer noopener">explore the tree plantations layer on GFW</a> and can <a href="https://gfw2-data.s3.amazonaws.com/plantations/sdpt/sdpt_v2.zip">download the data</a><em>. </em>For more information on the SDPT v2.0 update, <a href="https://www.wri.org/research/spatial-database-planted-trees-sdpt-version-2">read the technical note here</a>.</p>



<p><em>The SDPT compiles data from a variety of sources. If you have spatial data on planted trees that you think should be incorporated into the data set, </em><a href="https://forms.gle/pUzJy72N7szVMydg9" target="_blank" rel="noreferrer noopener"><em>please let us know here</em></a><em>.</em></p>



<p><em>Additional minor updates have been made to the SDPT in a version 2.1 incorporating new data in Brazil, Cambodia, Cote d’Ivoire and Ghana. </em><a href="https://gfw-files.s3.amazonaws.com/plantations/SDPT_v2.1/sdpt_v21_v09152024_public.gdb.zip"><em>Access the latest version here</em></a><em>.</em></p>



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