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<p><strong>Stay atop the latest forest research and news! The Global Forest Watch blog uses data to illuminate the state of forests worldwide and tells the stories of people dedicated to protecting them. Read about rainforests, deforestation, fires, sustainable agriculture, forest management and other topics critical to the future of forests.</strong></p>

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<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="700" 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>

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<p>Indigenous Peoples and local communities <a href="https://www.wri.org/insights/4-ways-indigenous-and-community-lands-can-reduce-emissions#:~:text=For%20example%2C%20research%20by%20WRI,not%20managed%20by%20indigenous%20peoples." target="_blank" rel="noreferrer noopener">play a crucial role</a> in protecting forests and the areas they manage tend to experience <a href="https://conbio.onlinelibrary.wiley.com/doi/abs/10.1111/cobi.14195" target="_blank" rel="noreferrer noopener">lower deforestation</a> rates than other forests. In fact, forests managed by Indigenous Peoples in the Amazon Basin are some of the <a href="https://www.wri.org/insights/amazon-carbon-sink-indigenous-forests" target="_blank" rel="noreferrer noopener">most effective carbon sinks</a> on the planet. By maintaining these forests, they actively contribute to global climate change mitigation efforts.</p>



<p>New climate financing mechanisms are creating opportunities for Indigenous Peoples and local communities to generate revenue to support the long-term stewardship of their ancestral lands and forest resources. However, communities often lack access to the data and tools required to quantify forest carbon fluxes (emissions from forest loss and disturbance, and removals due to plant growth) and communicate their contributions in ways recognized by these mechanisms.</p>



<p>To help communities supply such data, Global Forest Watch (GFW) offers accessible, open-source maps and statistics on forest carbon fluxes. GFW’s interactive <a href="https://www.globalforestwatch.org/map/?map=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&mapMenu=eyJtZW51U2VjdGlvbiI6ImRhdGFzZXRzIiwiZGF0YXNldENhdGVnb3J5IjoiY2xpbWF0ZSJ9">emissions, removals and net flux maps</a>, with associated statistics, support action unlike any other forest carbon monitoring system. The maps are updated annually, allowing communities to tell the carbon story behind every pixel of forest. &nbsp;</p>



<p>Rainforest Foundation US (RFUS), a non-profit organization dedicated to securing Indigenous Peoples’ land rights across Central and South America, is working with Indigenous communities and their allies to use this data and information to access climate financing opportunities. Since 2016, RFUS has worked alongside Indigenous communities to leverage tools like GFW data to detect and stop land invasions in their territories. This has resulted in <a href="https://www.pnas.org/doi/10.1073/pnas.2015171118" target="_blank" rel="noreferrer noopener">significant reductions in deforestation</a> around some communities.</p>



<p>More recently, RFUS has collaborated with communities to interpret and apply GFW’s forest carbon data to help them access climate finance and participate in carbon-related decision-making. In recent years, GFW data on carbon fluxes has been an integral part of RFUS’ programming and advocacy for Indigenous Peoples’ rights.</p>



<figure class="wp-block-image size-large"><img decoding="async" loading="lazy" width="2048" height="1365" src="https://content.globalforestwatch.org/wp-content/uploads/2025/09/Sep2024_Titulacion-Carococha_079_Sebastian-Castaneda-2048x1365.jpg" alt="" class="wp-image-19529" srcset="https://content.globalforestwatch.org/wp-content/uploads/2025/09/Sep2024_Titulacion-Carococha_079_Sebastian-Castaneda-2048x1365.jpg 2048w, https://content.globalforestwatch.org/wp-content/uploads/2025/09/Sep2024_Titulacion-Carococha_079_Sebastian-Castaneda-1024x682.jpg 1024w, https://content.globalforestwatch.org/wp-content/uploads/2025/09/Sep2024_Titulacion-Carococha_079_Sebastian-Castaneda-768x512.jpg 768w, https://content.globalforestwatch.org/wp-content/uploads/2025/09/Sep2024_Titulacion-Carococha_079_Sebastian-Castaneda-1536x1024.jpg 1536w" sizes="(max-width: 2048px) 100vw, 2048px" /><figcaption class="wp-element-caption">Titling teams map and demarcate community boundaries in Carcocha, Peru. Credit Sebastian Castañeda</figcaption></figure>



<p>Read on to learn more about two case studies where RFUS is working with Indigenous communities to use GFW’s carbon monitoring data to strengthen the protection of their forests and rights.</p>



<h2 class="wp-block-heading">Direct payments program as an alternative to carbon markets</h2>



<p>External incentives can help communities carry out forest monitoring more consistently and effectively. They also help finance essential infrastructure and services, such as electricity, latrines and clean water systems, allowing communities to avoid turning to activities that drive deforestation, such as mining or commercial agriculture, and instead pursue livelihoods that keep forests standing and sequestering carbon.</p>



<p>To help provide these incentives, RFUS established a direct payments fund with support from private donors to compensate 32 communities in Ecuador and northern Peru for protecting over 350,000 hectares of standing tropical forest. For approximately two years, communities conducted forest patrols, documented evidence of land incursions and filed legal complaints to protect their territories. In this innovative direct payment program — which was independent of the carbon market and did not issue carbon credits — RFUS used GFW’s tree cover, tree cover loss, <a href="https://gfw.global/3tauzVt">forest carbon removals</a> and <a href="https://gfw.global/47iENb6">net forest carbon flux</a> data to estimate the carbon sequestered by communities’ forests.</p>



<p>By using the custom area analysis tool on <a href="https://gfw.global/4bOp721">GFW’s dashboard</a>, RFUS was able to quickly and easily estimate the standing forest area and carbon sequestration rates within the forests of participating communities. This data enabled RFUS and participating communities to quantify the climate benefits of their forests, providing a clear rationale for the payments. Based on this information, communities received 10 soles (~$4 USD) per hectare of standing forest per year, commensurate with Peru’s national forest payments program, Probosques.<em></em></p>



<p>Unlike carbon credits, these payments were not tied to reductions in emissions or reforestation. Instead, these payments were designed to recognize, support and honor communities’ continued stewardship of their forests. The only conditions attached to the payments were that the resulting projects had to benefit communities and receive full community approval. Furthermore, funds could not be used for activities that contributed to deforestation, and communities had to maintain deforestation rates within their recent average.&nbsp; &nbsp;</p>



<p>Communities used these funds to invest in priority projects such as continuing their traditional agricultural practices and initiatives, constructing solar panel arrays, sanitation systems, potable water systems, communal boats and sustainable economic development projects. The unique nature of this program — making payments directly to communities based on public GFW carbon monitoring data — gave communities greater autonomy and agency to invest in and manage the projects they chose.</p>



<p>In the Peru-Colombia-Brazil tri-border area, Ticuna communities used the funds to advance their land titling efforts. By using the funds to cover the costs of surveyors and legal support, the communities <a href="https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Frainforestfoundation.org%2Fhow-climate-finance-can-reach-indigenous-peoples-and-local-communities%2F&data=05%7C02%7CPaige.Johnson%40wri.org%7C5904f82b68234045a96408ddefd86e63%7C476bac1f36b24ad98699cda6bad1f862%7C0%7C0%7C638930435315519121%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=ULYpl8%2BqV%2Fn3NyG3RyYnQvvMuPiBB0P5lns2AaggRvE%3D&reserved=0" target="_blank" rel="noreferrer noopener">secured an additional 45,000 hectares</a> of titled land, creating a contiguous Ticuna territory along the banks of the Amazon River. They are also piloting a collaborative titling effort with the regional government of Loreto that has since expanded across the state of Loreto, 59 territories, and over 100,000 hectares in three years.</p>



<figure class="wp-block-image size-large"><img decoding="async" loading="lazy" width="2048" height="1538" src="https://content.globalforestwatch.org/wp-content/uploads/2025/09/IMG_0863-2048x1538.jpg" alt="" class="wp-image-19530" srcset="https://content.globalforestwatch.org/wp-content/uploads/2025/09/IMG_0863-2048x1538.jpg 2048w, https://content.globalforestwatch.org/wp-content/uploads/2025/09/IMG_0863-1024x769.jpg 1024w, https://content.globalforestwatch.org/wp-content/uploads/2025/09/IMG_0863-768x577.jpg 768w, https://content.globalforestwatch.org/wp-content/uploads/2025/09/IMG_0863-1536x1153.jpg 1536w" sizes="(max-width: 2048px) 100vw, 2048px" /><figcaption class="wp-element-caption">Titling ceremony in Loreto, Peru. Credit: Daniel Tuesta</figcaption></figure>



<p>Across the border in Ecuador, the Indigenous community of Sarayaku is one of the largest territories to receive these direct payments, which they have used to invest directly in their “life plan,” or <a href="https://www.instagram.com/p/Cw0EBmUON0K/" target="_blank" rel="noreferrer noopener">Kawsak Sacha</a>, which in Kichwa means “The Living Forest.” This reflects the Sarayaku’s philosophy of being an integral part of the forest ecosystem, as well as their vision for the future. While the funding available through this program did not cover all elements of the life plan, the funds and decisions were managed autonomously by the Sarayaku communities. They focused primarily on community infrastructure projects that resulted in significant improvements in the quality of life for community members.</p>



<p>Samai Gualinga, Vice President of the Sarayaku community, said of the direct payments program: “a new standard of fair compensation and retribution is being created … it’s necessary to seek our own ways of monitoring our territory … to have our own databases … to show how much biodiversity and carbon we have … we need economic funds to support the families working on our monitoring projects.”</p>



<p>Scaling this direct payment program across the Amazon Basin may be difficult. However, the flexibility of GFW data allowed RFUS to put climate financing directly in the hands of Indigenous Peoples and support locally-led climate finance outside of carbon markets.</p>



<h2 class="wp-block-heading">Informing community roles in national carbon credit deals</h2>



<p>In 2022, the national government of Guyana signed a <a href="https://carboncredits.com/hess-signs-750m-redd-carbon-credits-deal-with-guyana/" target="_blank" rel="noreferrer noopener">jurisdictional REDD+</a> deal to sell $750 million worth of carbon credits from reducing deforestation in the country (REDD+ is a <a href="https://unfccc.int/topics/land-use/workstreams/redd/what-is-redd" target="_blank" rel="noreferrer noopener">framework</a> for paying developing countries when they reduce emissions from deforestation). Guyana was the first country to sell carbon credits at the national level and the deal requires that the revenue from the sale of credits are distributed to communities around the country through a process of <a href="https://blog.aspiration.com/benefit-sharing-voluntary-carbon-market/" target="_blank" rel="noreferrer noopener">benefits sharing</a>. Under this deal, 242 Indigenous communities opted in to receive the proposed 15% share of the benefits from the sale to support community led projects.</p>



<p>RFUS uses GFW forest carbon data to help inform communities in Guyana about how forests emit and sequester carbon, how these can be estimated and monitored, and to calculate the amount of carbon being sequestered on both titled and customary lands. While RFUS and local partners such as the Amerindian People’s Association are not using GFW’s data to dispute Guyana’s national REDD+ calculations, GFW data informs Indigenous organizations on how the contributions of their communities are <a href="https://www.development-today.com/archive/2023/dt-2--2023/carbon-certifier-admits-that-key-indigenous-complaints-were-not-on-the-table-when-credits-were-issued-to-guyana-last-year" target="_blank" rel="noreferrer noopener">or are not</a> reflected in the benefit sharing program.</p>



<figure class="wp-block-image size-large"><img decoding="async" loading="lazy" width="2048" height="1536" src="https://content.globalforestwatch.org/wp-content/uploads/2025/09/IMG_3115-2048x1536.jpeg" alt="" class="wp-image-19527" srcset="https://content.globalforestwatch.org/wp-content/uploads/2025/09/IMG_3115-2048x1536.jpeg 2048w, https://content.globalforestwatch.org/wp-content/uploads/2025/09/IMG_3115-1024x768.jpeg 1024w, https://content.globalforestwatch.org/wp-content/uploads/2025/09/IMG_3115-768x576.jpeg 768w, https://content.globalforestwatch.org/wp-content/uploads/2025/09/IMG_3115-1536x1152.jpeg 1536w" sizes="(max-width: 2048px) 100vw, 2048px" /><figcaption class="wp-element-caption">A Patamona woman cooks cassava in Guyana’s North Pakaraimas mountain range. Credit RFUS</figcaption></figure>



<p>For example, in the South Rupununi region of Guyana, of the 2.9 million hectares of customary Indigenous land in Wapichan Wiizi, around 590,000 hectares have been formally recognized by the government. The unrecognized Indigenous lands account for the bulk of the area and an even higher percentage of the territory’s forests since many Guyanese land titles were granted primarily for savanna areas rather than for forests. The South Rupununi District Council (SRDC) <a href="https://www.globalforestwatch.org/dashboards/aoi/642b3e00493227001be0b2cf/?category=climate&map=eyJjYW5Cb3VuZCI6dHJ1ZX0%3D&widget=carbonFlux">uploaded their land claim</a> (delineated over years of community mapping) to GFW and saw that just their customary territory alone accounts for nearly 10% of Guyana’s overall annual carbon sequestration. This and other WRI data have generated key figures for ongoing collaborative discussions between the SRDC and the government of Guyana regarding formal recognition of these customary lands and potential designation of the area as a community conserved area.</p>



<figure class="wp-block-image size-large"><img decoding="async" loading="lazy" width="2048" height="1365" src="https://content.globalforestwatch.org/wp-content/uploads/2025/09/DSC06626-2048x1365.jpg" alt="" class="wp-image-19526" srcset="https://content.globalforestwatch.org/wp-content/uploads/2025/09/DSC06626-2048x1365.jpg 2048w, https://content.globalforestwatch.org/wp-content/uploads/2025/09/DSC06626-1024x683.jpg 1024w, https://content.globalforestwatch.org/wp-content/uploads/2025/09/DSC06626-768x512.jpg 768w, https://content.globalforestwatch.org/wp-content/uploads/2025/09/DSC06626-1536x1024.jpg 1536w" sizes="(max-width: 2048px) 100vw, 2048px" /><figcaption class="wp-element-caption">Indigenous communities in Guyana’s rugged interior often contain a mix of dense forests and tropical savannas. Credit RFUS</figcaption></figure>



<p>“Carbon and carbon sequestration are abstract concepts that can easily get lost in national policy discussions and financial transactions,” said Linburg Pearson, Mapping and Monitoring Leader at Amerindian People’s Association. “GFW data has helped us understand the role that specific communities and lands play in regard to carbon emissions and sequestration.”</p>



<h2 class="wp-block-heading">Democratizing data helps make forest protection more equitable</h2>



<p>GFW’s open-source data is helping to promote transparency and broaden access by making critical information on forests and carbon emissions and sequestration accessible to communities. This helps bridge the gap between Indigenous communities and sources of finance, creating more equitable and just opportunities.</p>



<p>In this vein, GFW’s forest carbon monitoring data has been an important resource for RFUS and the communities they work with, illustrating how free, global carbon emissions and sequestration maps can support forest monitoring on a community level and improved outcomes for communities. These examples from Indigenous and local communities effectively using the carbon data to improve their livelihoods and democratize data can shed light on how to create more equitable and responsive financial mechanisms that prioritize the needs and rights of forest protectors.</p>



<p></p>



<p><em>This work builds on WRI’s broader commitment to support Indigenous Peoples and local communities in securing rights, protecting forests and strengthening climate resilience. </em><a href="https://www.wri.org/equitable-development/indigenous-peoples-local-communities" target="_blank" rel="noreferrer noopener"><em>Learn more here</em></a><em> about how GFW and WRI are supporting Indigenous Peoples and local communities.</em></p>



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Forest Carbon Data Helps Communities Benefit Financially from their Forests

<p>Indigenous Peoples and local communities <a href="https://www.wri.org/insights/4-ways-indigenous-and-community-lands-can-reduce-emissions#:~:text=For%20example%2C%20research%20by%20WRI,not%20managed%20by%20indigenous%20peoples." target="_blank" rel="noreferrer noopener">play a crucial role</a> in protecting forests and the areas they manage tend to experience <a href="https://conbio.onlinelibrary.wiley.com/doi/abs/10.1111/cobi.14195" target="_blank" rel="noreferrer noopener">lower deforestation</a> rates than other forests. In fact, forests managed by Indigenous Peoples in the Amazon Basin are some of the <a href="https://www.wri.org/insights/amazon-carbon-sink-indigenous-forests" target="_blank" rel="noreferrer noopener">most effective carbon sinks</a> on the planet. By maintaining these forests, they actively contribute to global climate change mitigation efforts.</p>



<p>New climate financing mechanisms are creating opportunities for Indigenous Peoples and local communities to generate revenue to support the long-term stewardship of their ancestral lands and forest resources. However, communities often lack access to the data and tools required to quantify forest carbon fluxes (emissions from forest loss and disturbance, and removals due to plant growth) and communicate their contributions in ways recognized by these mechanisms.</p>



<p>To help communities supply such data, Global Forest Watch (GFW) offers accessible, open-source maps and statistics on forest carbon fluxes. GFW’s interactive <a href="https://www.globalforestwatch.org/map/?map=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&amp;mapMenu=eyJtZW51U2VjdGlvbiI6ImRhdGFzZXRzIiwiZGF0YXNldENhdGVnb3J5IjoiY2xpbWF0ZSJ9">emissions, removals and net flux maps</a>, with associated statistics, support action unlike any other forest carbon monitoring system. The maps are updated annually, allowing communities to tell the carbon story behind every pixel of forest. &nbsp;</p>



<p>Rainforest Foundation US (RFUS), a non-profit organization dedicated to securing Indigenous Peoples’ land rights across Central and South America, is working with Indigenous communities and their allies to use this data and information to access climate financing opportunities. Since 2016, RFUS has worked alongside Indigenous communities to leverage tools like GFW data to detect and stop land invasions in their territories. This has resulted in <a href="https://www.pnas.org/doi/10.1073/pnas.2015171118" target="_blank" rel="noreferrer noopener">significant reductions in deforestation</a> around some communities.</p>



<p>More recently, RFUS has collaborated with communities to interpret and apply GFW’s forest carbon data to help them access climate finance and participate in carbon-related decision-making. In recent years, GFW data on carbon fluxes has been an integral part of RFUS’ programming and advocacy for Indigenous Peoples’ rights.</p>



<figure class="wp-block-image size-large"><img src="https://content.globalforestwatch.org/wp-content/uploads/2025/09/Sep2024_Titulacion-Carococha_079_Sebastian-Castaneda-2048x1365.jpg" alt="" class="wp-image-19529"/><figcaption class="wp-element-caption">Titling teams map and demarcate community boundaries in Carcocha, Peru. Credit Sebastian Castañeda</figcaption></figure>



<p>Read on to learn more about two case studies where RFUS is working with Indigenous communities to use GFW's carbon monitoring data to strengthen the protection of their forests and rights.</p>



<h2 class="wp-block-heading">Direct payments program as an alternative to carbon markets</h2>



<p>External incentives can help communities carry out forest monitoring more consistently and effectively. They also help finance essential infrastructure and services, such as electricity, latrines and clean water systems, allowing communities to avoid turning to activities that drive deforestation, such as mining or commercial agriculture, and instead pursue livelihoods that keep forests standing and sequestering carbon.</p>



<p>To help provide these incentives, RFUS established a direct payments fund with support from private donors to compensate 32 communities in Ecuador and northern Peru for protecting over 350,000 hectares of standing tropical forest. For approximately two years, communities conducted forest patrols, documented evidence of land incursions and filed legal complaints to protect their territories. In this innovative direct payment program — which was independent of the carbon market and did not issue carbon credits — RFUS used GFW’s tree cover, tree cover loss, <a href="https://gfw.global/3tauzVt">forest carbon removals</a> and <a href="https://gfw.global/47iENb6">net forest carbon flux</a> data to estimate the carbon sequestered by communities’ forests.</p>



<p>By using the custom area analysis tool on <a href="https://gfw.global/4bOp721">GFW’s dashboard</a>, RFUS was able to quickly and easily estimate the standing forest area and carbon sequestration rates within the forests of participating communities. This data enabled RFUS and participating communities to quantify the climate benefits of their forests, providing a clear rationale for the payments. Based on this information, communities received 10 soles (~$4 USD) per hectare of standing forest per year, commensurate with Peru’s national forest payments program, Probosques.<em></em></p>



<p>Unlike carbon credits, these payments were not tied to reductions in emissions or reforestation. Instead, these payments were designed to recognize, support and honor communities’ continued stewardship of their forests. The only conditions attached to the payments were that the resulting projects had to benefit communities and receive full community approval. Furthermore, funds could not be used for activities that contributed to deforestation, and communities had to maintain deforestation rates within their recent average.&nbsp; &nbsp;</p>



<p>Communities used these funds to invest in priority projects such as continuing their traditional agricultural practices and initiatives, constructing solar panel arrays, sanitation systems, potable water systems, communal boats and sustainable economic development projects. The unique nature of this program — making payments directly to communities based on public GFW carbon monitoring data — gave communities greater autonomy and agency to invest in and manage the projects they chose.</p>



<p>In the Peru-Colombia-Brazil tri-border area, Ticuna communities used the funds to advance their land titling efforts. By using the funds to cover the costs of surveyors and legal support, the communities <a href="https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Frainforestfoundation.org%2Fhow-climate-finance-can-reach-indigenous-peoples-and-local-communities%2F&amp;data=05%7C02%7CPaige.Johnson%40wri.org%7C5904f82b68234045a96408ddefd86e63%7C476bac1f36b24ad98699cda6bad1f862%7C0%7C0%7C638930435315519121%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&amp;sdata=ULYpl8%2BqV%2Fn3NyG3RyYnQvvMuPiBB0P5lns2AaggRvE%3D&amp;reserved=0" target="_blank" rel="noreferrer noopener">secured an additional 45,000 hectares</a> of titled land, creating a contiguous Ticuna territory along the banks of the Amazon River. They are also piloting a collaborative titling effort with the regional government of Loreto that has since expanded across the state of Loreto, 59 territories, and over 100,000 hectares in three years.</p>



<figure class="wp-block-image size-large"><img src="https://content.globalforestwatch.org/wp-content/uploads/2025/09/IMG_0863-2048x1538.jpg" alt="" class="wp-image-19530"/><figcaption class="wp-element-caption">Titling ceremony in Loreto, Peru. Credit: Daniel Tuesta</figcaption></figure>



<p>Across the border in Ecuador, the Indigenous community of Sarayaku is one of the largest territories to receive these direct payments, which they have used to invest directly in their “life plan,” or <a href="https://www.instagram.com/p/Cw0EBmUON0K/" target="_blank" rel="noreferrer noopener">Kawsak Sacha</a>, which in Kichwa means “The Living Forest.” This reflects the Sarayaku’s philosophy of being an integral part of the forest ecosystem, as well as their vision for the future. While the funding available through this program did not cover all elements of the life plan, the funds and decisions were managed autonomously by the Sarayaku communities. They focused primarily on community infrastructure projects that resulted in significant improvements in the quality of life for community members.</p>



<p>Samai Gualinga, Vice President of the Sarayaku community, said of the direct payments program: “a new standard of fair compensation and retribution is being created … it’s necessary to seek our own ways of monitoring our territory … to have our own databases … to show how much biodiversity and carbon we have … we need economic funds to support the families working on our monitoring projects.”</p>



<p>Scaling this direct payment program across the Amazon Basin may be difficult. However, the flexibility of GFW data allowed RFUS to put climate financing directly in the hands of Indigenous Peoples and support locally-led climate finance outside of carbon markets.</p>



<h2 class="wp-block-heading">Informing community roles in national carbon credit deals</h2>



<p>In 2022, the national government of Guyana signed a <a href="https://carboncredits.com/hess-signs-750m-redd-carbon-credits-deal-with-guyana/" target="_blank" rel="noreferrer noopener">jurisdictional REDD+</a> deal to sell $750 million worth of carbon credits from reducing deforestation in the country (REDD+ is a <a href="https://unfccc.int/topics/land-use/workstreams/redd/what-is-redd" target="_blank" rel="noreferrer noopener">framework</a> for paying developing countries when they reduce emissions from deforestation). Guyana was the first country to sell carbon credits at the national level and the deal requires that the revenue from the sale of credits are distributed to communities around the country through a process of <a href="https://blog.aspiration.com/benefit-sharing-voluntary-carbon-market/" target="_blank" rel="noreferrer noopener">benefits sharing</a>. Under this deal, 242 Indigenous communities opted in to receive the proposed 15% share of the benefits from the sale to support community led projects.</p>



<p>RFUS uses GFW forest carbon data to help inform communities in Guyana about how forests emit and sequester carbon, how these can be estimated and monitored, and to calculate the amount of carbon being sequestered on both titled and customary lands. While RFUS and local partners such as the Amerindian People’s Association are not using GFW’s data to dispute Guyana’s national REDD+ calculations, GFW data informs Indigenous organizations on how the contributions of their communities are <a href="https://www.development-today.com/archive/2023/dt-2--2023/carbon-certifier-admits-that-key-indigenous-complaints-were-not-on-the-table-when-credits-were-issued-to-guyana-last-year" target="_blank" rel="noreferrer noopener">or are not</a> reflected in the benefit sharing program.</p>



<figure class="wp-block-image size-large"><img src="https://content.globalforestwatch.org/wp-content/uploads/2025/09/IMG_3115-2048x1536.jpeg" alt="" class="wp-image-19527"/><figcaption class="wp-element-caption">A Patamona woman cooks cassava in Guyana’s North Pakaraimas mountain range. Credit RFUS</figcaption></figure>



<p>For example, in the South Rupununi region of Guyana, of the 2.9 million hectares of customary Indigenous land in Wapichan Wiizi, around 590,000 hectares have been formally recognized by the government. The unrecognized Indigenous lands account for the bulk of the area and an even higher percentage of the territory’s forests since many Guyanese land titles were granted primarily for savanna areas rather than for forests. The South Rupununi District Council (SRDC) <a href="https://www.globalforestwatch.org/dashboards/aoi/642b3e00493227001be0b2cf/?category=climate&amp;map=eyJjYW5Cb3VuZCI6dHJ1ZX0%3D&amp;widget=carbonFlux">uploaded their land claim</a> (delineated over years of community mapping) to GFW and saw that just their customary territory alone accounts for nearly 10% of Guyana’s overall annual carbon sequestration. This and other WRI data have generated key figures for ongoing collaborative discussions between the SRDC and the government of Guyana regarding formal recognition of these customary lands and potential designation of the area as a community conserved area.</p>



<figure class="wp-block-image size-large"><img src="https://content.globalforestwatch.org/wp-content/uploads/2025/09/DSC06626-2048x1365.jpg" alt="" class="wp-image-19526"/><figcaption class="wp-element-caption">Indigenous communities in Guyana’s rugged interior often contain a mix of dense forests and tropical savannas. Credit RFUS</figcaption></figure>



<p>“Carbon and carbon sequestration are abstract concepts that can easily get lost in national policy discussions and financial transactions,” said Linburg Pearson, Mapping and Monitoring Leader at Amerindian People’s Association. “GFW data has helped us understand the role that specific communities and lands play in regard to carbon emissions and sequestration.”</p>



<h2 class="wp-block-heading">Democratizing data helps make forest protection more equitable</h2>



<p>GFW’s open-source data is helping to promote transparency and broaden access by making critical information on forests and carbon emissions and sequestration accessible to communities. This helps bridge the gap between Indigenous communities and sources of finance, creating more equitable and just opportunities.</p>



<p>In this vein, GFW's forest carbon monitoring data has been an important resource for RFUS and the communities they work with, illustrating how free, global carbon emissions and sequestration maps can support forest monitoring on a community level and improved outcomes for communities. These examples from Indigenous and local communities effectively using the carbon data to improve their livelihoods and democratize data can shed light on how to create more equitable and responsive financial mechanisms that prioritize the needs and rights of forest protectors.</p>



<p></p>



<p><em>This work builds on WRI’s broader commitment to support Indigenous Peoples and local communities in securing rights, protecting forests and strengthening climate resilience. </em><a href="https://www.wri.org/equitable-development/indigenous-peoples-local-communities" target="_blank" rel="noreferrer noopener"><em>Learn more here</em></a><em> about how GFW and WRI are supporting Indigenous Peoples and local communities.</em></p>



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