<p>Total tropical primary forest loss in 2023 totaled 3.7 million hectares, the equivalent of losing almost 10 football (soccer) fields of forest per minute. <a href="https://gfw.global/3TPufvy" rel="noopener" target="_blank">View on the Global Forest Review.</a></p>


2023 Tree Cover Loss Data Analysis

overview of a river in Pantanal, Brazil

Insights

Insights | Global Forest Watch Blog

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amazon | Global Forest Watch Blog

Brazil

Brazil | Global Forest Watch Blog

Congo Basin

Congo Basin | Global Forest Watch Blog

deforestation

deforestation | Global Forest Watch Blog

forest change

forest change | Global Forest Watch Blog

Indonesia

Indonesia | Global Forest Watch Blog

Mikaela Weisse

Liz Goldman

Sarah Carter

Tropical Forest Loss Drops Steeply in Brazil and Colombia, but High Rates Persist Overall

Despite progress in some countries, the rate of tropical primary forest loss in 2023 remained persistent, according to new data from UMD on GFW.

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Side by side comparison of UMD tree cover loss and JRC Tropical Moist Forest data

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forest quality

forest quality | Global Forest Watch Blog

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Michelle Sims

Peter Potapov

Christelle Vancutsem

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Fréderic Achard

<p>The wide availability of forest and land cover maps based on satellite data provides more information on the world’s forests than ever before. However, this plethora of information can also be challenging for people trying to understand differences in data sources and decide which data to use for a specific purpose.</p>



<p>In the past, we’ve compared the <a href="https://gfw.global/3BfwQWz">annual tree cover loss data</a> from the University of Maryland (UMD) and available on Global Forest Watch (GFW) with national data from <a href="https://www.globalforestwatch.org/blog/data-and-research/2022-tree-cover-loss-data-explained/">Brazil and Indonesia</a>, as well as with data from the United Nations Food and Agriculture Organization’s (FAO) <a href="https://www.globalforestwatch.org/blog/data-and-research/global-forest-watch-and-the-forest-resources-assessment-explained-in-5-graphics-2/">Global Forest Resources Assessment</a>, to shed light on some of these differences.</p>



<p>Another data set that tracks forest change in the tropics is the <a href="https://forobs.jrc.ec.europa.eu/TMF" target="_blank" rel="noreferrer noopener">Tropical Moist Forest (TMF) data set</a> from the European Commission Joint Research Centre (JRC). Like the UMD tree cover loss data, the JRC TMF data is based on Landsat satellite imagery and is updated annually. Yet while both data sets map forest disturbances, the maps and numbers look a little different.</p>



<p>In this blog, we explain some key differences in the definitions and methods used for each data set that impact the resulting maps and discuss how the disturbances mapped by both data sets compare (while the data sets also map forest gain or regrowth, this blog focuses on comparing their mapping of forest disturbances). While understanding these differences can help determine the contexts for which each data set might be useful, note that this analysis does not evaluate the quality or accuracy of either data set.</p>



<h2 class="wp-block-heading">What areas do the JRC and UMD data sets cover, and how do they define forests?</h2>



<p>The UMD data set maps forests globally based on <a href="https://www.science.org/doi/10.1126/science.1244693" target="_blank" rel="noreferrer noopener">tree cover extent</a> in 2000. <a href="https://www.science.org/doi/10.1126/science.1244693" target="_blank" rel="noreferrer noopener">Tree cover</a> is defined as woody vegetation with a minimum height of at least five meters at 30-meter resolution, which includes all types of tree cover — including natural or managed forest and plantations — and is not limited to a specific forest type. The GFW map shows tree cover with a 30% canopy density, which we use in our analyses and in this comparison, although users can adjust the threshold based on their needs.</p>



<p>The JRC data set, on the other hand, <a href="https://www.science.org/doi/10.1126/sciadv.abe1603" target="_blank" rel="noreferrer noopener">maps forests</a> beginning in 1990. The data includes all closed primary and secondary forests in the humid tropics and does not apply a minimum height or canopy density threshold to delineate forest extent.</p>



<p>As a result of these definitional differences, some areas included in the 2000 UMD tree cover extent in the tropics like dry forests, young secondary forests and plantations are not classified as forests in the JRC data set in 2000 — a total of 655 million hectares (Mha), or 34%, of the UMD tree cover extent area that overlaps with the JRC data. Likewise, the JRC forest extent in 2000 includes some areas that do not meet the height and 30% canopy density threshold in the UMD data or are otherwise not mapped as tree cover by the UMD data — 17.2 Mha, or 1% of the JRC forest extent.</p>



<p>Because of the differences in geographic coverage and scope between the two data sets, this blog only compares forest disturbances from 2001-2022 for areas that, in the year 2000, are mapped both as tree cover by UMD and as forest by JRC.</p>



<h2 class="wp-block-heading">What types of forest disturbances do the UMD and JRC data map?</h2>



<h3 class="wp-block-heading"><em>The JRC Tropical Moist Forest data set maps degradation and deforestation in the humid tropics</em></h3>



<p>The JRC TMF data set maps disturbances to tropical moist forests — including degradation and deforestation — from 1990 to 2022. The JRC team maps these changes using an algorithm that detects forest disruptions, meaning an absence of tree foliage cover within a 30-meter pixel for each available Landsat image, and then classifies the status of forest based on how long these disruptions are visible.</p>



<p>The TMF data set <a href="https://www.science.org/doi/10.1126/sciadv.abe1603" target="_blank" rel="noreferrer noopener">defines degradation</a> as temporary disturbances occurring for up to 2.5 years, while it defines deforestation as longer-term disturbances where disruptions to tree cover are visible for more than 2.5 years and no tree regrowth is detected over the last three years. In any given year, a forest is considered disturbed if there is a disruption detected in at least one Landsat image during that year.</p>



<p>Thus, pixels classified as degraded are still considered forest, with existing or regrowing trees, while pixels classified as deforested are undergoing a longer-term loss of forest. Because disruptions are recorded and analyzed for the entire time series, the data set classifies dynamics over time; for example, a forest pixel may be classified as degraded in one year after a short-term disturbance, then after a period of recovery may later be classified as deforested after ongoing disturbances with no tree regrowth. The JRC deforestation class therefore includes direct deforestation (deforestation of undisturbed forest) or deforestation after degradation (deforestation of forest that was previously classified as degraded).</p>



<p>The data set also analyzes the frequency, duration of disruptions and time of forest recovery in between disruption events to identify deforestation following degradation versus multiple degradation events.</p>



<h3 class="wp-block-heading"><em>The UMD tree cover loss data set on GFW maps all types of tree cover loss globally</em></h3>



<p>The UMD tree cover loss data set maps annual tree cover loss from 2001 to 2022. The UMD team uses an algorithm that detects loss using change detection metrics based on comparison of Landsat images between the present and past years. Tree cover loss, <a href="https://www.science.org/doi/10.1126/science.1244693" target="_blank" rel="noreferrer noopener">defined as</a> a clearing of tree cover of at least a half of a 30-meter Landsat pixel, includes both temporary and permanent losses without defining or differentiating which loss is considered degradation or deforestation. Once classified as loss, pixels are masked from further updates, meaning that any following forest change dynamics — such as regrowth or subsequent disturbances — are not recorded.</p>



<p>The UMD tree cover loss data can be combined with contextual data layers, such as <a href="https://gfw.global/3kqcoqa">UMD’s map of humid tropical primary forest</a>, to see loss within specific forest types.</p>



<h4 class="wp-block-heading">Key differences between the JRC TMF and UMD tree cover loss data</h4>



<table border="1" cellpadding="0" cellspacing="0">
	<tbody>
		<tr>
			<td style="width:165px;height:20px;">
			<p>&nbsp;</p>
			</td>
			<td style="width:320px;height:20px;">
			<p><strong>JRC TMF</strong></p>
			</td>
			<td style="width:320px;height:20px;">
			<p><strong>UMD tree cover loss</strong></p>
			</td>
		</tr>
		<tr>
			<td style="width:165px;height:20px;">
			<p>Temporal coverage</p>
			</td>
			<td style="width:320px;height:20px;">
			<p>1990-2022</p>
			</td>
			<td style="width:320px;height:20px;">
			<p>&nbsp;2000-2022</p>
			</td>
		</tr>
		<tr>
			<td style="width:165px;height:20px;">
			<p>Geographic coverage and extent</p>
			</td>
			<td style="width:320px;height:20px;">
			<p><strong>Tropical moist forest:</strong> closed primary and secondary forests in the humid tropics in 1990.</p>
			</td>
			<td style="width:320px;height:20px;">
			<p><strong>Global tree cover: </strong>woody vegetation with a minimum height of at least five meters at 30-meter resolution in 2000.</p>
			</td>
		</tr>
		<tr>
			<td style="width:165px;height:20px;">
			<p>Definition of disturbance</p>
			</td>
			<td style="width:320px;height:20px;">
			<p>An absence of tree foliage cover within a 30-meter pixel.</p>
			</td>
			<td style="width:320px;height:20px;">
			<p>Clearing of at least half of tree cover within a 30-meter pixel.</p>
			</td>
		</tr>
		<tr>
			<td style="width:165px;height:20px;">
			<p>Disturbance classes</p>
			</td>
			<td style="width:320px;height:20px;">
			<p>Disturbances are classified as <strong>degradation </strong>if they are visible for less than 2.5 years, and <strong>deforestation </strong>if they are visible for more than 2.5 years with no vegetative regrowth over the last three years.</p>
			</td>
			<td style="width:320px;height:20px;">
			<p>All disturbances classified as <strong>tree cover loss. </strong>The length of disturbance is not considered.</p>
			</td>
		</tr>
		<tr>
			<td style="width:165px;height:20px;">
			<p>Methods</p>
			</td>
			<td style="width:320px;height:20px;">
			<p>Classifies valid single-date Landsat images and derives disturbance classes by analyzing the single-date classifications. Dynamics of disturbance events over time are recorded.</p>
			</td>
			<td style="width:320px;height:20px;">
			<p>Classifies change using change detection metrics derived from all valid Landsat images over the present and past years. Only the first loss event that is detected is recorded.</p>
			</td>
		</tr>
	</tbody>
</table>



<h2 class="wp-block-heading">What do the UMD and JRC data show about forest disturbances in the tropics?</h2>



<p>Overall, the JRC data detects a larger area of disturbances across the tropics from 2001-2022 compared with the UMD data. The JRC data detects 258 Mha of disturbances, including 113 Mha of degradation and 145 Mha of deforestation, while the UMD data detects 143 Mha of tree cover loss. However, trends in total deforestation mapped by JRC and tree cover loss mapped by UMD are generally aligned: They are largely similar for the first decade; then from 2013-2015, JRC detects a larger area as deforestation than UMD detects as loss, and after 2016, UMD detects a larger area.</p>



<div class="flourish-embed" data-src="story/2112582?163031"><script src="https://public.flourish.studio/resources/embed.js"></script></div>



<p>We further separated out the disturbance types mapped by the JRC data and overlaid the data sets to evaluate how the two data sets compare at each pixel.</p>



<p>Among all the JRC data’s disturbance classes, the JRC direct deforestation class aligned most closely with UMD tree cover loss. Across the tropics from 2001-2022, 46.8 Mha, or 68%, of the area classified as direct deforestation by the JRC data was also classified as tree cover loss in the UMD data. This varied by region and was highest in Asia/Oceania and the Americas (66% and 75% respectively) and lowest in Africa (50%). The UMD data less often classified areas that JRC identified as deforestation after degradation as tree cover loss (38.1 Mha, or 50% across the tropics).</p>



<p>In some areas, disturbances classified as degradation by the JRC TMF data set were classified as tree cover loss by the UMD data. Across the tropics from 2001-2022, 32.6 Mha, or 29%, of the area the JRC data classified as degradation was also classified as tree cover loss in the UMD data. The JRC degradation class includes three types of degradation: short-duration (less than one year), long-duration (1-2.5 years) and short-duration over 2-3 periods (short-duration degradation that occurs two to three separate times throughout the time period). The JRC data also measures “intensity” of degradation based on the total number of Landsat images where disruptions in tree cover were visible. We found that, in general, the UMD data:</p>



<ul>
<li>More often detected longer duration degradation as tree cover loss. Short-duration degradation (including events occurring just once or over 2-3 periods), which represents 85% of the forest area mapped as degraded by JRC since 2001, is usually not shown as tree cover loss by the UMD data.</li>



<li>Classified degradation events as tree cover loss that had an intensity of greater than six images on average, while those UMD did not classify as loss had approximately three images or less on average.</li>



<li>Detected a larger proportion of the area JRC classified as degradation from 2015 onwards, which may be <a href="https://www.globalforestwatch.org/blog/data-and-research/tree-cover-loss-satellite-data-trend-analysis/">due to the algorithm changes</a> in the UMD data that increase forest loss detection sensitivity in case of fires, selective logging and other disturbance types that JRC classified as degradation.</li>
</ul>



<p>In other areas across the tropics, the UMD data detected tree cover loss for 6.4 Mha, or 7%, of areas where there the JRC data detected no disturbance events.</p>



<figure class="wp-block-image size-full is-resized"><img decoding="async" loading="lazy" width="1222" height="1163" src="https://content.globalforestwatch.org/wp-content/uploads/2024/01/Comparison-JRC-TMF-and-UMD-table.png" alt="Comparison of JRC TMF and UMD tree cover loss disturbances across the tropics" class="wp-image-16572" style="aspect-ratio:1.0507308684436802;width:771px;height:auto" srcset="https://content.globalforestwatch.org/wp-content/uploads/2024/01/Comparison-JRC-TMF-and-UMD-table.png 1222w, https://content.globalforestwatch.org/wp-content/uploads/2024/01/Comparison-JRC-TMF-and-UMD-table-1024x975.png 1024w, https://content.globalforestwatch.org/wp-content/uploads/2024/01/Comparison-JRC-TMF-and-UMD-table-768x731.png 768w" sizes="(max-width: 1222px) 100vw, 1222px" /></figure>



<h4 class="wp-block-heading">Forest disturbances related to shifting cultivation in Mongala, DRC</h4>



<div class="flourish-embed flourish-photo-slider" data-src="visualisation/16055613?163031"><script src="https://public.flourish.studio/resources/embed.js"></script></div>



<h4 class="wp-block-heading">Large scale deforestation along BR-230 in Amazonas, Brazil</h4>



<div class="flourish-embed flourish-photo-slider" data-src="visualisation/16055698?163031"><script src="https://public.flourish.studio/resources/embed.js"></script></div>



<h4 class="wp-block-heading">Selective logging in Pará, Brazil</h4>



<div class="flourish-embed flourish-photo-slider" data-src="visualisation/16365261?163031"><script src="https://public.flourish.studio/resources/embed.js"></script></div>



<h2 class="wp-block-heading">Why does the UMD and JRC data align in some ways and differ in others?</h2>



<p>The two data sets align more closely for more abrupt disturbances that are likely to meet the definitions used in both data sets, such as intense fires (which the JRC data may classify as long-duration degradation) or clearance of tree cover for agricultural expansion (usually classified as deforestation in the JRC data). The two data sets are less likely to detect the same disturbance when it is followed by a rapid recovery (such as short-duration degradation in the JRC data, including disturbances like drought, selective logging or low-intensity fires, which may only be detected in as few as one Landsat image) or disturbances resulting in gradual reduction of tree cover over a longer time period (such as degradation followed by deforestation in the JRC data). In these cases, the disturbance may not meet the UMD definition of tree cover loss and therefore is less likely to be detected in the UMD data.</p>



<p>Both data sets have different strengths. The UMD data is global in scope, allowing for comparative analysis across regions due to global consistency in definitions and methods. Within the tropics, the UMD data includes broader coverage of forest types beyond tropical moist forests, including tropical dry forests.<a href="https://gfw.global/3GEmSQh"></a> The UMD data also provides flexibility for users to adjust the canopy density threshold according to their preference or needs, which can be used to align with a specific forest definition or forest characteristics of a specific biome.</p>



<p>Meanwhile, the JRC data detects degradation and less intense disturbances, which can be helpful for users who want to understand where forests have experienced various types of stresses that have not resulted in complete loss. The JRC data also monitors forests after initial disturbances to track forest recovery and subsequent disturbances, which is helpful for users who would like to understand yearly change dynamics and identify where there are repeated disturbances.</p>



<p>However, it is important to note that we are not evaluating the accuracy of either data set. Assessing which data set is more accurate for a specific use case or geography would require a formal validation exercise.</p>



<p>Ultimately, these two data sets present complementary information that can help us better understand the various types of changes occurring in tropical forests.</p>



<hr> 

<div class="attribute" style="”padding-bottom:" 10px;”="">
 

Note: This blog investigates the JRC TMF map, which is a separate product from the JRC global map of forest cover for year 2020, released on December 7, 2023.

 

</div> 

 

<hr>



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

Differences Between Global Forest Watch’s Tree Cover Loss Data and JRC’s Tropical Moist Forest Data Explained

<p>The wide availability of forest and land cover maps based on satellite data provides more information on the world’s forests than ever before. However, this plethora of information can also be challenging for people trying to understand differences in data sources and decide which data to use for a specific purpose.</p>



<p>In the past, we’ve compared the <a href="https://gfw.global/3BfwQWz">annual tree cover loss data</a> from the University of Maryland (UMD) and available on Global Forest Watch (GFW) with national data from <a href="https://www.globalforestwatch.org/blog/data-and-research/2022-tree-cover-loss-data-explained/">Brazil and Indonesia</a>, as well as with data from the United Nations Food and Agriculture Organization’s (FAO) <a href="https://www.globalforestwatch.org/blog/data-and-research/global-forest-watch-and-the-forest-resources-assessment-explained-in-5-graphics-2/">Global Forest Resources Assessment</a>, to shed light on some of these differences.</p>



<p>Another data set that tracks forest change in the tropics is the <a href="https://forobs.jrc.ec.europa.eu/TMF" target="_blank" rel="noreferrer noopener">Tropical Moist Forest (TMF) data set</a> from the European Commission Joint Research Centre (JRC). Like the UMD tree cover loss data, the JRC TMF data is based on Landsat satellite imagery and is updated annually. Yet while both data sets map forest disturbances, the maps and numbers look a little different.</p>



<p>In this blog, we explain some key differences in the definitions and methods used for each data set that impact the resulting maps and discuss how the disturbances mapped by both data sets compare (while the data sets also map forest gain or regrowth, this blog focuses on comparing their mapping of forest disturbances). While understanding these differences can help determine the contexts for which each data set might be useful, note that this analysis does not evaluate the quality or accuracy of either data set.</p>



<h2 class="wp-block-heading">What areas do the JRC and UMD data sets cover, and how do they define forests?</h2>



<p>The UMD data set maps forests globally based on <a href="https://www.science.org/doi/10.1126/science.1244693" target="_blank" rel="noreferrer noopener">tree cover extent</a> in 2000. <a href="https://www.science.org/doi/10.1126/science.1244693" target="_blank" rel="noreferrer noopener">Tree cover</a> is defined as woody vegetation with a minimum height of at least five meters at 30-meter resolution, which includes all types of tree cover — including natural or managed forest and plantations — and is not limited to a specific forest type. The GFW map shows tree cover with a 30% canopy density, which we use in our analyses and in this comparison, although users can adjust the threshold based on their needs.</p>



<p>The JRC data set, on the other hand, <a href="https://www.science.org/doi/10.1126/sciadv.abe1603" target="_blank" rel="noreferrer noopener">maps forests</a> beginning in 1990. The data includes all closed primary and secondary forests in the humid tropics and does not apply a minimum height or canopy density threshold to delineate forest extent.</p>



<p>As a result of these definitional differences, some areas included in the 2000 UMD tree cover extent in the tropics like dry forests, young secondary forests and plantations are not classified as forests in the JRC data set in 2000 — a total of 655 million hectares (Mha), or 34%, of the UMD tree cover extent area that overlaps with the JRC data. Likewise, the JRC forest extent in 2000 includes some areas that do not meet the height and 30% canopy density threshold in the UMD data or are otherwise not mapped as tree cover by the UMD data — 17.2 Mha, or 1% of the JRC forest extent.</p>



<p>Because of the differences in geographic coverage and scope between the two data sets, this blog only compares forest disturbances from 2001-2022 for areas that, in the year 2000, are mapped both as tree cover by UMD and as forest by JRC.</p>



<h2 class="wp-block-heading">What types of forest disturbances do the UMD and JRC data map?</h2>



<h3 class="wp-block-heading"><em>The JRC Tropical Moist Forest data set maps degradation and deforestation in the humid tropics</em></h3>



<p>The JRC TMF data set maps disturbances to tropical moist forests — including degradation and deforestation — from 1990 to 2022. The JRC team maps these changes using an algorithm that detects forest disruptions, meaning an absence of tree foliage cover within a 30-meter pixel for each available Landsat image, and then classifies the status of forest based on how long these disruptions are visible.</p>



<p>The TMF data set <a href="https://www.science.org/doi/10.1126/sciadv.abe1603" target="_blank" rel="noreferrer noopener">defines degradation</a> as temporary disturbances occurring for up to 2.5 years, while it defines deforestation as longer-term disturbances where disruptions to tree cover are visible for more than 2.5 years and no tree regrowth is detected over the last three years. In any given year, a forest is considered disturbed if there is a disruption detected in at least one Landsat image during that year.</p>



<p>Thus, pixels classified as degraded are still considered forest, with existing or regrowing trees, while pixels classified as deforested are undergoing a longer-term loss of forest. Because disruptions are recorded and analyzed for the entire time series, the data set classifies dynamics over time; for example, a forest pixel may be classified as degraded in one year after a short-term disturbance, then after a period of recovery may later be classified as deforested after ongoing disturbances with no tree regrowth. The JRC deforestation class therefore includes direct deforestation (deforestation of undisturbed forest) or deforestation after degradation (deforestation of forest that was previously classified as degraded).</p>



<p>The data set also analyzes the frequency, duration of disruptions and time of forest recovery in between disruption events to identify deforestation following degradation versus multiple degradation events.</p>



<h3 class="wp-block-heading"><em>The UMD tree cover loss data set on GFW maps all types of tree cover loss globally</em></h3>



<p>The UMD tree cover loss data set maps annual tree cover loss from 2001 to 2022. The UMD team uses an algorithm that detects loss using change detection metrics based on comparison of Landsat images between the present and past years. Tree cover loss, <a href="https://www.science.org/doi/10.1126/science.1244693" target="_blank" rel="noreferrer noopener">defined as</a> a clearing of tree cover of at least a half of a 30-meter Landsat pixel, includes both temporary and permanent losses without defining or differentiating which loss is considered degradation or deforestation. Once classified as loss, pixels are masked from further updates, meaning that any following forest change dynamics — such as regrowth or subsequent disturbances — are not recorded.</p>



<p>The UMD tree cover loss data can be combined with contextual data layers, such as <a href="https://gfw.global/3kqcoqa">UMD’s map of humid tropical primary forest</a>, to see loss within specific forest types.</p>



<h4 class="wp-block-heading">Key differences between the JRC TMF and UMD tree cover loss data</h4>



<table border="1" cellpadding="0" cellspacing="0">
	<tbody>
		<tr>
			<td style="width:165px;height:20px;">
			<p>&nbsp;</p>
			</td>
			<td style="width:320px;height:20px;">
			<p><strong>JRC TMF</strong></p>
			</td>
			<td style="width:320px;height:20px;">
			<p><strong>UMD tree cover loss</strong></p>
			</td>
		</tr>
		<tr>
			<td style="width:165px;height:20px;">
			<p>Temporal coverage</p>
			</td>
			<td style="width:320px;height:20px;">
			<p>1990-2022</p>
			</td>
			<td style="width:320px;height:20px;">
			<p>&nbsp;2000-2022</p>
			</td>
		</tr>
		<tr>
			<td style="width:165px;height:20px;">
			<p>Geographic coverage and extent</p>
			</td>
			<td style="width:320px;height:20px;">
			<p><strong>Tropical moist forest:</strong> closed primary and secondary forests in the humid tropics in 1990.</p>
			</td>
			<td style="width:320px;height:20px;">
			<p><strong>Global tree cover: </strong>woody vegetation with a minimum height of at least five meters at 30-meter resolution in 2000.</p>
			</td>
		</tr>
		<tr>
			<td style="width:165px;height:20px;">
			<p>Definition of disturbance</p>
			</td>
			<td style="width:320px;height:20px;">
			<p>An absence of tree foliage cover within a 30-meter pixel.</p>
			</td>
			<td style="width:320px;height:20px;">
			<p>Clearing of at least half of tree cover within a 30-meter pixel.</p>
			</td>
		</tr>
		<tr>
			<td style="width:165px;height:20px;">
			<p>Disturbance classes</p>
			</td>
			<td style="width:320px;height:20px;">
			<p>Disturbances are classified as <strong>degradation </strong>if they are visible for less than 2.5 years, and <strong>deforestation </strong>if they are visible for more than 2.5 years with no vegetative regrowth over the last three years.</p>
			</td>
			<td style="width:320px;height:20px;">
			<p>All disturbances classified as <strong>tree cover loss. </strong>The length of disturbance is not considered.</p>
			</td>
		</tr>
		<tr>
			<td style="width:165px;height:20px;">
			<p>Methods</p>
			</td>
			<td style="width:320px;height:20px;">
			<p>Classifies valid single-date Landsat images and derives disturbance classes by analyzing the single-date classifications. Dynamics of disturbance events over time are recorded.</p>
			</td>
			<td style="width:320px;height:20px;">
			<p>Classifies change using change detection metrics derived from all valid Landsat images over the present and past years. Only the first loss event that is detected is recorded.</p>
			</td>
		</tr>
	</tbody>
</table>



<h2 class="wp-block-heading">What do the UMD and JRC data show about forest disturbances in the tropics?</h2>



<p>Overall, the JRC data detects a larger area of disturbances across the tropics from 2001-2022 compared with the UMD data. The JRC data detects 258 Mha of disturbances, including 113 Mha of degradation and 145 Mha of deforestation, while the UMD data detects 143 Mha of tree cover loss. However, trends in total deforestation mapped by JRC and tree cover loss mapped by UMD are generally aligned: They are largely similar for the first decade; then from 2013-2015, JRC detects a larger area as deforestation than UMD detects as loss, and after 2016, UMD detects a larger area.</p>



<div class="flourish-embed" data-src="story/2112582?163031"><script src="https://public.flourish.studio/resources/embed.js"></script></div>



<p>We further separated out the disturbance types mapped by the JRC data and overlaid the data sets to evaluate how the two data sets compare at each pixel.</p>



<p>Among all the JRC data’s disturbance classes, the JRC direct deforestation class aligned most closely with UMD tree cover loss. Across the tropics from 2001-2022, 46.8 Mha, or 68%, of the area classified as direct deforestation by the JRC data was also classified as tree cover loss in the UMD data. This varied by region and was highest in Asia/Oceania and the Americas (66% and 75% respectively) and lowest in Africa (50%). The UMD data less often classified areas that JRC identified as deforestation after degradation as tree cover loss (38.1 Mha, or 50% across the tropics).</p>



<p>In some areas, disturbances classified as degradation by the JRC TMF data set were classified as tree cover loss by the UMD data. Across the tropics from 2001-2022, 32.6 Mha, or 29%, of the area the JRC data classified as degradation was also classified as tree cover loss in the UMD data. The JRC degradation class includes three types of degradation: short-duration (less than one year), long-duration (1-2.5 years) and short-duration over 2-3 periods (short-duration degradation that occurs two to three separate times throughout the time period). The JRC data also measures “intensity” of degradation based on the total number of Landsat images where disruptions in tree cover were visible. We found that, in general, the UMD data:</p>



<ul>
<li>More often detected longer duration degradation as tree cover loss. Short-duration degradation (including events occurring just once or over 2-3 periods), which represents 85% of the forest area mapped as degraded by JRC since 2001, is usually not shown as tree cover loss by the UMD data.</li>



<li>Classified degradation events as tree cover loss that had an intensity of greater than six images on average, while those UMD did not classify as loss had approximately three images or less on average.</li>



<li>Detected a larger proportion of the area JRC classified as degradation from 2015 onwards, which may be <a href="https://www.globalforestwatch.org/blog/data-and-research/tree-cover-loss-satellite-data-trend-analysis/">due to the algorithm changes</a> in the UMD data that increase forest loss detection sensitivity in case of fires, selective logging and other disturbance types that JRC classified as degradation.</li>
</ul>



<p>In other areas across the tropics, the UMD data detected tree cover loss for 6.4 Mha, or 7%, of areas where there the JRC data detected no disturbance events.</p>



<figure class="wp-block-image size-full is-resized"><img src="https://content.globalforestwatch.org/wp-content/uploads/2024/01/Comparison-JRC-TMF-and-UMD-table.png" alt="Comparison of JRC TMF and UMD tree cover loss disturbances across the tropics" class="wp-image-16572" style="aspect-ratio:1.0507308684436802;width:771px;height:auto"/></figure>



<h4 class="wp-block-heading">Forest disturbances related to shifting cultivation in Mongala, DRC</h4>



<div class="flourish-embed flourish-photo-slider" data-src="visualisation/16055613?163031"><script src="https://public.flourish.studio/resources/embed.js"></script></div>



<h4 class="wp-block-heading">Large scale deforestation along BR-230 in Amazonas, Brazil</h4>



<div class="flourish-embed flourish-photo-slider" data-src="visualisation/16055698?163031"><script src="https://public.flourish.studio/resources/embed.js"></script></div>



<h4 class="wp-block-heading">Selective logging in Pará, Brazil</h4>



<div class="flourish-embed flourish-photo-slider" data-src="visualisation/16365261?163031"><script src="https://public.flourish.studio/resources/embed.js"></script></div>



<h2 class="wp-block-heading">Why does the UMD and JRC data align in some ways and differ in others?</h2>



<p>The two data sets align more closely for more abrupt disturbances that are likely to meet the definitions used in both data sets, such as intense fires (which the JRC data may classify as long-duration degradation) or clearance of tree cover for agricultural expansion (usually classified as deforestation in the JRC data). The two data sets are less likely to detect the same disturbance when it is followed by a rapid recovery (such as short-duration degradation in the JRC data, including disturbances like drought, selective logging or low-intensity fires, which may only be detected in as few as one Landsat image) or disturbances resulting in gradual reduction of tree cover over a longer time period (such as degradation followed by deforestation in the JRC data). In these cases, the disturbance may not meet the UMD definition of tree cover loss and therefore is less likely to be detected in the UMD data.</p>



<p>Both data sets have different strengths. The UMD data is global in scope, allowing for comparative analysis across regions due to global consistency in definitions and methods. Within the tropics, the UMD data includes broader coverage of forest types beyond tropical moist forests, including tropical dry forests.<a href="https://gfw.global/3GEmSQh"></a> The UMD data also provides flexibility for users to adjust the canopy density threshold according to their preference or needs, which can be used to align with a specific forest definition or forest characteristics of a specific biome.</p>



<p>Meanwhile, the JRC data detects degradation and less intense disturbances, which can be helpful for users who want to understand where forests have experienced various types of stresses that have not resulted in complete loss. The JRC data also monitors forests after initial disturbances to track forest recovery and subsequent disturbances, which is helpful for users who would like to understand yearly change dynamics and identify where there are repeated disturbances.</p>



<p>However, it is important to note that we are not evaluating the accuracy of either data set. Assessing which data set is more accurate for a specific use case or geography would require a formal validation exercise.</p>



<p>Ultimately, these two data sets present complementary information that can help us better understand the various types of changes occurring in tropical forests.</p>



<hr> 

<div class="attribute" style="”padding-bottom:" 10px;”="">
 

Note: This blog investigates the JRC TMF map, which is a separate product from the JRC global map of forest cover for year 2020, released on December 7, 2023.

 

</div> 

 

<hr>

We explain key differences between two data sets that track forest change in the tropics: UMD tree cover loss and JRC Tropical Moist Forest.

Tree Cover Loss and Tropical Moist Forest Differences, Explained

logging

logging | Global Forest Watch Blog

policy

policy | Global Forest Watch Blog

Fred Stolle

Stientje van Veldhoven

<p>A recent analysis found that tall, mature forests — which are critical for storing carbon and safeguarding biodiversity — are declining significantly in some parts of Europe. This is primarily due to a rise in timber harvesting as well as natural disturbances, such as wildfires and pests, which are often exacerbated by climate change.</p>



<p>There was some good news as well.&nbsp;<a href="https://www.sciencedirect.com/science/article/pii/S0034425723003486" target="_blank" rel="noreferrer noopener">The study</a>, from the University of Maryland and WRI in partnership with European researchers, shows that Europe’s total tree cover increased slightly over the last two decades. But that’s not the full story: Some regions within Europe saw significant declines in forest area. And the total amount of&nbsp;<em>tall forests&nbsp;</em>(forests with trees taller than 15 meters) declined by 2.25 million hectares — an area half the size of Denmark. The decline was highest in Nordic countries, which saw a 20% reduction in tall forests, followed by areas in Southeastern Europe. While tall forests have often been replaced with new trees, these can take decades to mature to the point where they provide equivalent climate and ecosystem benefits, meaning overall forest health in these areas is being reduced.</p>



<p>These findings underscore the need for ambitious action on the part of EU countries to protect and maintain existing forests and the vital services they provide. Progress is underway, with a number of new laws aimed at curbing deforestation and forest degradation. But to be successful, these must be informed by timely, robust data on forest health and disturbances. The proposed <a href="https://ec.europa.eu/commission/presscorner/detail/en/ip_23_5909" target="_blank" rel="noreferrer noopener">EU Forest Monitoring Framework</a>, issued on November 22, 2023, should support these efforts by ensuring harmonized and improved forest monitoring in Europe — if it mandates comparable and consistent reporting on key forest health indicators throughout the EU.</p>



<h2 class="wp-block-heading">Europe Lost 2.25 Million Hectares of Tall Forests From 2001-2021</h2>



<p>Between 2001 and 2021, Europe experienced a small net gain in tree cover of around 1%, or 1.5 million hectares. With tree cover declining&nbsp;<a href="https://research.wri.org/gfr/forest-extent-indicators/forest-extent#is-global-tree-cover-increasing-or-decreasing" target="_blank" rel="noreferrer noopener">in almost all other areas</a>&nbsp;around the world, this is an important achievement. But despite this overall gain, the findings also show that Europe’s tall forests&nbsp;<em>declined&nbsp;</em>by 3%, or 2.25 million hectares, over the same period. Tall forests were disproportionately affected by an acceleration of forest disturbance in recent years, including both harvesting activities and natural disturbances.</p>



<p>The analysis shows strong variability between regions, with some experiencing significant losses in forest area while others saw more gains. The Nordic region (Norway, Sweden, Denmark and Finland) saw the biggest declines, losing 3.5% of its total forests and 20% of its tall forests over the last two decades.</p>



<figure class="wp-block-image size-large"><img decoding="async" loading="lazy" width="2048" height="1950" src="https://content.globalforestwatch.org/wp-content/uploads/2023/11/23-11-14-European-Forest-Decline_Insights-no-logo-1-2048x1950.png" alt="Map showing net change in tall tree cover (height greater than or equal to 15 meters) in Europe 2001-2021" class="wp-image-16502" srcset="https://content.globalforestwatch.org/wp-content/uploads/2023/11/23-11-14-European-Forest-Decline_Insights-no-logo-1-2048x1950.png 2048w, https://content.globalforestwatch.org/wp-content/uploads/2023/11/23-11-14-European-Forest-Decline_Insights-no-logo-1-1024x975.png 1024w, https://content.globalforestwatch.org/wp-content/uploads/2023/11/23-11-14-European-Forest-Decline_Insights-no-logo-1-768x731.png 768w, https://content.globalforestwatch.org/wp-content/uploads/2023/11/23-11-14-European-Forest-Decline_Insights-no-logo-1-1536x1463.png 1536w" sizes="(max-width: 2048px) 100vw, 2048px" /></figure>



<p>The vast majority (around 87%) of tree cover loss was due to intensive timber harvesting — which can take the form of direct felling or salvage logging after a disturbance — as well as natural disturbances like wildfires and insect outbreaks, which are increasing in extent and severity due to climate change.</p>



<p>Most tree cover loss will be temporary as new forest growth in Europe is largely compensating for forest loss in terms of area alone. But tall forests are being cleared at a faster rate than new forests can regrow, leading to a gradual decline in forest height and a reduction of forest services such as carbon storage over time. So while Europe isn’t losing tree cover overall, the health of its forests is declining.</p>



<p>This decline in Europe’s tall forests is a sign that timber harvesting may already exceed rates that can be sustained into the future. With global demand for timber&nbsp;<a href="https://www.fao.org/documents/card/en/c/cc2265en" target="_blank" rel="noreferrer noopener">expected to grow</a>&nbsp;in the coming decades, Europe should heed this warning and take action to avoid running down its precious forest assets.</p>



<h2 class="wp-block-heading">Why Are Tall Forests So Important?</h2>



<p>While most forests in Europe have been intensively managed by humans for centuries, these forests still provide immense value for people and nature.</p>



<p>For one, the carbon storage capacity of trees increases with height and age, meaning the loss of tall trees and a resulting shift toward shorter, younger trees reduces the carbon storage capacity of Europe’s forests. While the full carbon picture is complicated (for example, young forests absorb carbon from the atmosphere at a faster rate than older standing forests),&nbsp;<a href="https://www.wri.org/insights/forests-absorb-twice-much-carbon-they-emit-each-year" target="_blank" rel="noreferrer noopener">protecting mature forests</a>&nbsp;is critical for curbing climate change.</p>



<figure class="wp-block-image size-full"><img decoding="async" loading="lazy" width="760" height="477" src="https://content.globalforestwatch.org/wp-content/uploads/2023/11/20_01_21_Carbon_Flux_v2_Graphic_1.png" alt="Illustration: Forests act as both a source and a sink for carbon" class="wp-image-16503"/></figure>



<p>These tall forests also include many of Europe’s old growth forests, which take centuries to grow and cannot be replaced by young, regrowing forests. Old growth forests&nbsp;<a href="https://www.nature.com/articles/s41597-021-00988-7" target="_blank" rel="noreferrer noopener">play a key role</a>&nbsp;in climate change mitigation by storing large quantities of carbon both in their biomass and in their soil. They provide ecosystem services like protecting soil health and regulating water drainage, and act as a critical refuge for wildlife and biodiversity. They are also a valuable part of cultural heritage for European communities and nations.</p>



<p>Further, even though the last two decades saw a slight increase in tree cover in Europe overall, much of this increase is due to expansion of tree plantations — specifically plantations of non-native tree species such as eucalyptus, black locust and Sitka spruce. This likely has&nbsp;<a href="https://onlinelibrary.wiley.com/doi/full/10.1111/geb.13440" target="_blank" rel="noreferrer noopener">negative consequences</a>&nbsp;for ecosystems, such as reduced diversity and abundance of plants and animals, particularly where more diverse natural forests are replaced by monoculture plantations.</p>



<h2 class="wp-block-heading">New EU Regulations Could Curb Forest Degradation, but Improved Monitoring Is Needed</h2>



<p>Europe is working to improve forest management and address its contribution to forest loss worldwide through a number of new and developing laws and strategies. These include:</p>



<ul>
<li><strong>The&nbsp;<a href="https://environment.ec.europa.eu/strategy/forest-strategy_en" target="_blank" rel="noreferrer noopener">EU Forest Strategy for 2030</a>:</strong>&nbsp;A strategy to improve the quantity and quality of EU forests and strengthen their protection, restoration and resilience.</li>



<li><strong>The&nbsp;<a href="https://environment.ec.europa.eu/strategy/biodiversity-strategy-2030_en" target="_blank" rel="noreferrer noopener">EU Biodiversity Strategy for 2030</a>:</strong>&nbsp;A comprehensive long-term plan to protect nature and reverse ecosystem degradation in the EU.</li>



<li><strong>The proposed&nbsp;<a href="https://ec.europa.eu/commission/presscorner/detail/en/IP_23_5662" target="_blank" rel="noreferrer noopener">Nature Restoration Law</a>:</strong>&nbsp;A binding regulation to restore nature, including putting restoration measures in place for at least 20% of the EU’s land areas and 20% of its seas by 2030.</li>



<li><strong>The&nbsp;<a href="https://environment.ec.europa.eu/topics/forests/deforestation/regulation-deforestation-free-products_en" target="_blank" rel="noreferrer noopener">EU Deforestation Regulation</a>:</strong>&nbsp;A binding regulation to ensure that certain commodities exported to or placed on the EU market are <a href="https://www.globalforestwatch.org/blog/commodities/satellite-data-eu-regulation-deforestation-free-supply-chains/">deforestation free</a>.</li>
</ul>



<p>These initiatives show progress is moving in the right direction, but they must be supported by improved monitoring and transparency to be most effective. This is the aim of the proposed <a href="https://ec.europa.eu/commission/presscorner/detail/en/ip_23_5909" target="_blank" rel="noreferrer noopener">Forest Monitoring Framework</a> — a regulatory initiative to ensure that European member states provide detailed, robust and timely information on the condition and management of EU forests, including indicators on their health, quality and trends over time.</p>



<p>With better monitoring, Europe will be able to assess whether its forests are managed sustainably, evaluate the ability of forests to contribute to climate change mitigation and identify priority forests to protect. Monitoring efforts under the framework must be harmonized to allow comparison and understanding across the EU, meaning countries should be responsible for reporting on the same set of indicators. They should also be transparent to encourage public accountability and timely to enable data-based decision making on appropriate time scales.</p>



<p>Forests are crucial to fighting climate change and to protecting ecosystems and biodiversity. To maximize their potential, Europe should look deeper into its forests. Satellite monitoring and data products, like the ones used in this study or through the open-source&nbsp;<a href="https://www.globalforestwatch.org/">Global Forest Watch</a>, combined with ground-based measurements can support implementation of the Forest Monitoring Framework Regulation and help ensure all of Europe’s forests are on the right track.</p>



<hr> 

<div class="attribute" style="”padding-bottom:" 10px;”="">
 

Originally appeared on <a href="https://www.wri.org/insights/european-tall-forest-decline" target="_blank" rel="noopener noreferrer">WRI Insights</a>. 
 

</div> 

 

<hr>



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

Timber Harvesting and Climate Change Are Depleting Europe’s Mature Forests

<p>A recent analysis found that tall, mature forests — which are critical for storing carbon and safeguarding biodiversity — are declining significantly in some parts of Europe. This is primarily due to a rise in timber harvesting as well as natural disturbances, such as wildfires and pests, which are often exacerbated by climate change.</p>



<p>There was some good news as well.&nbsp;<a href="https://www.sciencedirect.com/science/article/pii/S0034425723003486" target="_blank" rel="noreferrer noopener">The study</a>, from the University of Maryland and WRI in partnership with European researchers, shows that Europe’s total tree cover increased slightly over the last two decades. But that’s not the full story: Some regions within Europe saw significant declines in forest area. And the total amount of&nbsp;<em>tall forests&nbsp;</em>(forests with trees taller than 15 meters) declined by 2.25 million hectares — an area half the size of Denmark. The decline was highest in Nordic countries, which saw a 20% reduction in tall forests, followed by areas in Southeastern Europe. While tall forests have often been replaced with new trees, these can take decades to mature to the point where they provide equivalent climate and ecosystem benefits, meaning overall forest health in these areas is being reduced.</p>



<p>These findings underscore the need for ambitious action on the part of EU countries to protect and maintain existing forests and the vital services they provide. Progress is underway, with a number of new laws aimed at curbing deforestation and forest degradation. But to be successful, these must be informed by timely, robust data on forest health and disturbances. The proposed <a href="https://ec.europa.eu/commission/presscorner/detail/en/ip_23_5909" target="_blank" rel="noreferrer noopener">EU Forest Monitoring Framework</a>, issued on November 22, 2023, should support these efforts by ensuring harmonized and improved forest monitoring in Europe — if it mandates comparable and consistent reporting on key forest health indicators throughout the EU.</p>



<h2 class="wp-block-heading">Europe Lost 2.25 Million Hectares of Tall Forests From 2001-2021</h2>



<p>Between 2001 and 2021, Europe experienced a small net gain in tree cover of around 1%, or 1.5 million hectares. With tree cover declining&nbsp;<a href="https://research.wri.org/gfr/forest-extent-indicators/forest-extent#is-global-tree-cover-increasing-or-decreasing" target="_blank" rel="noreferrer noopener">in almost all other areas</a>&nbsp;around the world, this is an important achievement. But despite this overall gain, the findings also show that Europe’s tall forests&nbsp;<em>declined&nbsp;</em>by 3%, or 2.25 million hectares, over the same period. Tall forests were disproportionately affected by an acceleration of forest disturbance in recent years, including both harvesting activities and natural disturbances.</p>



<p>The analysis shows strong variability between regions, with some experiencing significant losses in forest area while others saw more gains. The Nordic region (Norway, Sweden, Denmark and Finland) saw the biggest declines, losing 3.5% of its total forests and 20% of its tall forests over the last two decades.</p>



<figure class="wp-block-image size-large"><img src="https://content.globalforestwatch.org/wp-content/uploads/2023/11/23-11-14-European-Forest-Decline_Insights-no-logo-1-2048x1950.png" alt="Map showing net change in tall tree cover (height greater than or equal to 15 meters) in Europe 2001-2021" class="wp-image-16502"/></figure>



<p>The vast majority (around 87%) of tree cover loss was due to intensive timber harvesting — which can take the form of direct felling or salvage logging after a disturbance — as well as natural disturbances like wildfires and insect outbreaks, which are increasing in extent and severity due to climate change.</p>



<p>Most tree cover loss will be temporary as new forest growth in Europe is largely compensating for forest loss in terms of area alone. But tall forests are being cleared at a faster rate than new forests can regrow, leading to a gradual decline in forest height and a reduction of forest services such as carbon storage over time. So while Europe isn’t losing tree cover overall, the health of its forests is declining.</p>



<p>This decline in Europe’s tall forests is a sign that timber harvesting may already exceed rates that can be sustained into the future. With global demand for timber&nbsp;<a href="https://www.fao.org/documents/card/en/c/cc2265en" target="_blank" rel="noreferrer noopener">expected to grow</a>&nbsp;in the coming decades, Europe should heed this warning and take action to avoid running down its precious forest assets.</p>



<h2 class="wp-block-heading">Why Are Tall Forests So Important?</h2>



<p>While most forests in Europe have been intensively managed by humans for centuries, these forests still provide immense value for people and nature.</p>



<p>For one, the carbon storage capacity of trees increases with height and age, meaning the loss of tall trees and a resulting shift toward shorter, younger trees reduces the carbon storage capacity of Europe’s forests. While the full carbon picture is complicated (for example, young forests absorb carbon from the atmosphere at a faster rate than older standing forests),&nbsp;<a href="https://www.wri.org/insights/forests-absorb-twice-much-carbon-they-emit-each-year" target="_blank" rel="noreferrer noopener">protecting mature forests</a>&nbsp;is critical for curbing climate change.</p>



<figure class="wp-block-image size-full"><img src="https://content.globalforestwatch.org/wp-content/uploads/2023/11/20_01_21_Carbon_Flux_v2_Graphic_1.png" alt="Illustration: Forests act as both a source and a sink for carbon" class="wp-image-16503"/></figure>



<p>These tall forests also include many of Europe’s old growth forests, which take centuries to grow and cannot be replaced by young, regrowing forests. Old growth forests&nbsp;<a href="https://www.nature.com/articles/s41597-021-00988-7" target="_blank" rel="noreferrer noopener">play a key role</a>&nbsp;in climate change mitigation by storing large quantities of carbon both in their biomass and in their soil. They provide ecosystem services like protecting soil health and regulating water drainage, and act as a critical refuge for wildlife and biodiversity. They are also a valuable part of cultural heritage for European communities and nations.</p>



<p>Further, even though the last two decades saw a slight increase in tree cover in Europe overall, much of this increase is due to expansion of tree plantations — specifically plantations of non-native tree species such as eucalyptus, black locust and Sitka spruce. This likely has&nbsp;<a href="https://onlinelibrary.wiley.com/doi/full/10.1111/geb.13440" target="_blank" rel="noreferrer noopener">negative consequences</a>&nbsp;for ecosystems, such as reduced diversity and abundance of plants and animals, particularly where more diverse natural forests are replaced by monoculture plantations.</p>



<h2 class="wp-block-heading">New EU Regulations Could Curb Forest Degradation, but Improved Monitoring Is Needed</h2>



<p>Europe is working to improve forest management and address its contribution to forest loss worldwide through a number of new and developing laws and strategies. These include:</p>



<ul>
<li><strong>The&nbsp;<a href="https://environment.ec.europa.eu/strategy/forest-strategy_en" target="_blank" rel="noreferrer noopener">EU Forest Strategy for 2030</a>:</strong>&nbsp;A strategy to improve the quantity and quality of EU forests and strengthen their protection, restoration and resilience.</li>



<li><strong>The&nbsp;<a href="https://environment.ec.europa.eu/strategy/biodiversity-strategy-2030_en" target="_blank" rel="noreferrer noopener">EU Biodiversity Strategy for 2030</a>:</strong>&nbsp;A comprehensive long-term plan to protect nature and reverse ecosystem degradation in the EU.</li>



<li><strong>The proposed&nbsp;<a href="https://ec.europa.eu/commission/presscorner/detail/en/IP_23_5662" target="_blank" rel="noreferrer noopener">Nature Restoration Law</a>:</strong>&nbsp;A binding regulation to restore nature, including putting restoration measures in place for at least 20% of the EU's land areas and 20% of its seas by 2030.</li>



<li><strong>The&nbsp;<a href="https://environment.ec.europa.eu/topics/forests/deforestation/regulation-deforestation-free-products_en" target="_blank" rel="noreferrer noopener">EU Deforestation Regulation</a>:</strong>&nbsp;A binding regulation to ensure that certain commodities exported to or placed on the EU market are <a href="https://www.globalforestwatch.org/blog/commodities/satellite-data-eu-regulation-deforestation-free-supply-chains/">deforestation free</a>.</li>
</ul>



<p>These initiatives show progress is moving in the right direction, but they must be supported by improved monitoring and transparency to be most effective. This is the aim of the proposed <a href="https://ec.europa.eu/commission/presscorner/detail/en/ip_23_5909" target="_blank" rel="noreferrer noopener">Forest Monitoring Framework</a> — a regulatory initiative to ensure that European member states provide detailed, robust and timely information on the condition and management of EU forests, including indicators on their health, quality and trends over time.</p>



<p>With better monitoring, Europe will be able to assess whether its forests are managed sustainably, evaluate the ability of forests to contribute to climate change mitigation and identify priority forests to protect. Monitoring efforts under the framework must be harmonized to allow comparison and understanding across the EU, meaning countries should be responsible for reporting on the same set of indicators. They should also be transparent to encourage public accountability and timely to enable data-based decision making on appropriate time scales.</p>



<p>Forests are crucial to fighting climate change and to protecting ecosystems and biodiversity. To maximize their potential, Europe should look deeper into its forests. Satellite monitoring and data products, like the ones used in this study or through the open-source&nbsp;<a href="https://www.globalforestwatch.org/">Global Forest Watch</a>, combined with ground-based measurements can support implementation of the Forest Monitoring Framework Regulation and help ensure all of Europe’s forests are on the right track.</p>



<hr> 

<div class="attribute" style="”padding-bottom:" 10px;”="">
 

Originally appeared on <a href="https://www.wri.org/insights/european-tall-forest-decline" target="_blank" rel="noopener noreferrer">WRI Insights</a>. 
 

</div> 

 

<hr>

Timber Harvesting and Climate Change Are Depleting Europe's Mature Forests

A new study found that important tall, mature forests are declining in some parts of Europe due to timber harvesting and climate change.

Timber Harvesting and Climate Change Are Depleting Europe&#8217;s Mature Forests

People

Hear stories from the forest defenders working in the field.

People | Global Forest Watch Blog

indigenous peoples

indigenous peoples | Global Forest Watch Blog

Katie Reytar

Jessica Webb

Peter Veit

<p>The Saamaka, an Afro-descendent tribal community, reside deep in the heart of Suriname’s Amazonian rainforest. They’ve maintained their plots of land and small farms for generations, relying on the bounty of fruits, nuts and medicines the surrounding tropical forest provides. &nbsp;</p>



<p>But lately, their forested territory has seen unwelcome visitors.&nbsp;</p>



<p>A logging company began bulldozing a road right through the Saamaka’s forest in early 2023. While the Suriname government sanctioned the logging concession, it came without the Saamaka’s consent, despite a 2007 ruling from the Inter-American Court of Human Rights requiring their approval for such projects. The road is just the latest threat facing the Saamaka’s land, on top of flooding from hydropower dams and water pollution from nearby mining operations. &nbsp;</p>



<p>&nbsp;“We are losing our very way of life — our food, our water, our land,” said Hugo Jabini, a community leader and spokesperson for the Saamaka. “We can no longer afford to be invisible.”</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" loading="lazy" width="455" height="342" src="https://content.globalforestwatch.org/wp-content/uploads/2023/11/HugoPPT3.jpg" alt="Saamaka leader Hugo Jabini leads a kuutu, a meeting of Saamakan communities." class="wp-image-16456"/><figcaption class="wp-element-caption">Hugo Jabini leads a kuutu, a meeting of Saamakan communities.&nbsp;</figcaption></figure></div>


<p>The Saamaka’s story is a common one. Indigenous Peoples and local communities hold some of the most pristine and resource-rich lands in the world — areas highly coveted by mining and logging companies and other profiteers.&nbsp; Land grabs and other threats are especially severe in places where the government does not recognize communities’ land rights, or where anti-deforestation and other laws are weak or poorly enforced. It’s the reason many Indigenous Peoples and local communities often take land monitoring into their own hands — and some are now using digital tools to do it.&nbsp;</p>



<p>Freely available satellite imagery and data from sites like&nbsp;<a href="https://www.globalforestwatch.org/map/">Global Forest Watch</a>&nbsp;and&nbsp;<a href="https://www.landmarkmap.org/data/" target="_blank" rel="noreferrer noopener">LandMark</a>&nbsp;provide near-real-time information that tracks deforestation and land degradation. Indigenous and local communities are increasingly using tools like this to gather evidence that deforestation and degradation are happening on their lands, build their case against illegal activities and take legal action to prevent it from continuing.&nbsp;&nbsp;</p>



<p>Three examples from Suriname, Indonesia and Peru illustrate a growing trend in fighting land rights violations with data.&nbsp;&nbsp;</p>



<h2 class="wp-block-heading">In Suriname, Deforestation Data Reveals Threats to the Saamaka’s Land Rights &nbsp;</h2>



<p>In 2007, the Inter-American Court of Human Rights compelled the government of Suriname to recognize the traditional land rights of the Saamaka and other Indigenous and community groups in Suriname. &nbsp;Yet satellite data from Global Forest Watch shows that since the judgment in 2007, tree cover loss actually increased in the Saamaka’s lands, largely from logging and mining activities. Tree cover loss inside government-granted logging concessions in and surrounding the Saamaka territory totaled 44,700 hectares, a 5.5% loss in tree cover from 2001-2022.&nbsp;&nbsp;</p>



<div class="flourish-embed flourish-chart" data-src="visualisation/15824378?240776"><script src="https://public.flourish.studio/resources/embed.js"></script></div>



<p>Monthly satellite images from March 2023 to October 2023 show the gradual construction of a road being carved through the heart of the Saamaka territory and leading to a government-granted logging concession. The Saamaka say the road was constructed without their knowledge or consent.&nbsp;</p>



<figure class="wp-block-image size-full"><img decoding="async" loading="lazy" width="1226" height="531" src="https://content.globalforestwatch.org/wp-content/uploads/2023/11/Suriname-logging-road.gif" alt="Gif of road construction progress through the Saamaka’s forested territory. March-October 2023" class="wp-image-16455"/><figcaption class="wp-element-caption">Road construction progresses through the Saamaka’s forested territory. Source: Planet imagery on Global Forest Watch.</figcaption></figure>



<p>Armed with this data and imagery, Jabini and seven other representatives from Suriname’s Indigenous and local communities traveled more than 2,500 miles to Washington, D.C., presenting their evidence to the Inter-American Commission on Human Rights in November 2023. Jabini hopes the commission will reopen its court case against the Suriname government to strengthen traditional land rights.&nbsp;&nbsp;</p>



<p>“We are not here to fight the government; we are just fighting for our rights,” Jabini said.</p>



<h2 class="wp-block-heading">In Indonesia, Indigenous Peoples Use Satellite Data to Track and Report Illegal Timber &nbsp;</h2>



<p>In the eastern-most edges of Indonesia lies an archipelago of 832 islands containing some of the country’s most pristine remaining rainforests. The Aru Islands are home to more than 60,000 Indigenous Aruese, who speak 14 different tribal languages. Their lives are deeply intertwined with the forests they call home, hunting deer, harvesting tree gum, and maintaining a strong spiritual connection with the forests believed to harbor the souls of their ancestors.</p>



<figure class="wp-block-image size-full"><img decoding="async" loading="lazy" width="965" height="651" src="https://content.globalforestwatch.org/wp-content/uploads/2023/11/aru-islands-2.jpg" alt="Indonesia’s Aru Islands" class="wp-image-16458" srcset="https://content.globalforestwatch.org/wp-content/uploads/2023/11/aru-islands-2.jpg 965w, https://content.globalforestwatch.org/wp-content/uploads/2023/11/aru-islands-2-768x518.jpg 768w" sizes="(max-width: 965px) 100vw, 965px" /><figcaption class="wp-element-caption">Indonesia’s Aru Islands hold some of the country’s most pristine rainforests and are home to more than 60,000 Indigenous Aruese. Photo by Forest Watch Indonesia.</figcaption></figure>



<p>As forests in more easily accessible areas of Indonesia such as Java and Borneo have been cleared, increasing pressure for valuable timber species and land for growing crops like sugar has reached the shores of the Aru Islands. Aru Indigenous Peoples and&nbsp;<a href="https://fwi.or.id/en/" rel="noreferrer noopener" target="_blank">Forest Watch Indonesia (FWI),</a>&nbsp;a civil society organization, have been working together to monitor, document and halt illegal logging using satellite data.&nbsp;&nbsp;</p>



<p>Using&nbsp;<a href="https://www.globalforestwatch.org/blog/data-and-research/early-warning-systems-for-deforestation-an-explainer/">deforestation alerts</a>&nbsp;from Global Forest Watch, FWI conducts desk analyses to identify priority locations for forest monitoring. They train Aru Forest Monitors on how to navigate to areas of forest where satellites detected recent clearings, using the&nbsp;<a href="https://forestwatcher.globalforestwatch.org/">Forest Watcher mobile app</a>. They also document evidence of deforestation with the app by taking photos and recording written or audio observations of the causes of the clearing.&nbsp;</p>



<p>Forest Monitors then continually track the extraction of timber from these deforestation sites, oftentimes following the wood to local ports, photographing identifiable information of ships containing illegally harvested timber, and transmitting this information to FWI. The organization then synthesizes the information and passes it to Indonesian authorities, who can then intercept the ships when they dock in Java before reaching international waters. In February 2019, the evidence that Indigenous Forest Monitors documented prompted the Indonesian Ministry of Environment and Forestry to seize 38 containers of illegally harvested timber. High-profile examples like this can serve as a deterrent for future illegal logging.</p>



<h2 class="wp-block-heading">Indigenous Communities in Peru Deploy Technology to Reduce Illegal Deforestation and Strengthen Land Rights</h2>



<p>A&nbsp;<a href="https://www.globalforestwatch.org/blog/people/indigenous-forest-monitors-reduce-deforestation/">two-year study</a>&nbsp;in the Northeastern Amazon region of Peru found that communities who used satellite-based forest monitoring technologies and data significantly reduced deforestation on their lands.</p>



<p>Equipped with deforestation alerts accessed from Forest Watcher and Global Forest Watch, forest monitors representing 36 local communities patrolled their ancestral lands. They documented evidence of encroachment from illicit coca plantations and illegal logging, using satellite imagery, photos, written documentation and drone footage. The monitors presented this information in community assemblies to collectively determine what action to take. Depending on the situation, they then either asked the invaders to leave by showing evidence that they had crossed over into community lands, or submitted documentation to Peruvian law enforcement, who then followed up with official field investigations.&nbsp;</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" loading="lazy" width="455" height="607" src="https://content.globalforestwatch.org/wp-content/uploads/2023/11/p_paisa_20150105_113737-scaled-1.jpg" alt="" class="wp-image-16459"/><figcaption class="wp-element-caption">A community monitor in Remanso del Amazonas identifies early warning signs of deforestation. Photo by Beder Olortegui.</figcaption></figure></div>


<p>Ultimately, the communities that used forest monitoring technologies reduced deforestation in their territories by 52% in the first year and an additional 21% in the second year, as compared to a similar number of communities in a control group. The communities using monitoring technologies also reported higher satisfaction with forest governance.</p>



<p>Since the study concluded, communities with experience using monitoring technologies are now training communities in the control group to do the same. The communities who succeeded in reducing deforestation have also received direct payments from the&nbsp;<a href="https://rainforestfoundation.org/our-work/approaches/rainforest-alert/" rel="noreferrer noopener" target="_blank">Rainforest Foundation US’s Rainforest Alert program</a>, a payment system for keeping forests conserved.</p>



<p>Most recently, some communities allocated that funding towards strengthening and expanding legal recognition of their ancestral lands. Community land titling in Peru is a slow and bureaucratic process. With the funds, communities were able to georeference the limits of their lands; contract soil analysts, lawyers and Geographic Information System (GIS) specialists; and petition the government for land titles. They succeeded in obtaining titles to their territories in just 10 months – a process that normally takes years or even decades.</p>



<h2 class="wp-block-heading">Open Data Supports Communities, but More Secure Land Rights Are Essential&nbsp;</h2>



<p>Satellite data and imagery are critical tools because they provide transparent, independent evidence of suspected violations. They allow communities to rapidly monitor and document forest disturbances over large areas and long periods of time at low cost, thus reducing expensive field patrols. Moreover, much of the monitoring and documentation can be done remotely from the safety of a laptop, without risking face-to-face confrontation with encroachers. This is especially important because environmental defenders face growing threats. In 2022, at least&nbsp;<a href="https://www.globalwitness.org/en/campaigns/environmental-activists/standing-firm/" target="_blank" rel="noreferrer noopener">177 environmental defenders were killed</a>, 36% of whom were Indigenous.&nbsp;</p>



<p>Given the power of satellite data to help communities protect their land rights, data creators and managers need to ensure that communities continue to have access to open data and technology. Communities also need support in data use, including tailored&nbsp;<a href="https://www.globalforestwatch.org/grants-and-fellowships/about/">training resources</a>,&nbsp;<a href="https://www.globalforestwatch.org/grants-and-fellowships/about/" target="_blank" rel="noreferrer noopener">financial support</a>&nbsp;and facilitating the&nbsp;<a href="https://www.globalforestwatch.org/help/map/webinars/webinar-strengthening-the-role-of-indigenous-youth-in-forest-protection-perspectives-from-latin-america/">sharing of experiences</a>.</p>



<p>However, while satellite data helps communities document and take action on illegal deforestation and related infractions, governments ultimately need to recognize and enforce Indigenous Peoples’ and communities’ land rights. Stronger and more secure land rights — with higher penalties for infractions — are more likely to deter illegal activity from occurring in the first place, or at least ensure a swift and decisive end to violations.</p>



<p>Indigenous Peoples and local communities have stewarded their lands and natural resources for centuries. Though more secure land rights are ultimately needed, satellite data can help them manage threats to their lands now and conserve their homes for generations to come.</p>



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Originally appeared on <a href="https://www.wri.org/insights/indigenous-peoples-local-communities-use-satellite-data-deforestation" target="_blank" rel="noopener noreferrer">WRI Insights</a>. 
 

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Indigenous Peoples and Local Communities Are Using Satellite Data to Fight Deforestation

<p>The Saamaka, an Afro-descendent tribal community, reside deep in the heart of Suriname’s Amazonian rainforest. They’ve maintained their plots of land and small farms for generations, relying on the bounty of fruits, nuts and medicines the surrounding tropical forest provides. &nbsp;</p>



<p>But lately, their forested territory has seen unwelcome visitors.&nbsp;</p>



<p>A logging company began bulldozing a road right through the Saamaka’s forest in early 2023. While the Suriname government sanctioned the logging concession, it came without the Saamaka’s consent, despite a 2007 ruling from the Inter-American Court of Human Rights requiring their approval for such projects. The road is just the latest threat facing the Saamaka’s land, on top of flooding from hydropower dams and water pollution from nearby mining operations. &nbsp;</p>



<p>&nbsp;“We are losing our very way of life — our food, our water, our land,” said Hugo Jabini, a community leader and spokesperson for the Saamaka. “We can no longer afford to be invisible.”</p>



<figure class="wp-block-image aligncenter size-full"><img src="https://content.globalforestwatch.org/wp-content/uploads/2023/11/HugoPPT3.jpg" alt="Saamaka leader Hugo Jabini leads a kuutu, a meeting of Saamakan communities." class="wp-image-16456"/><figcaption class="wp-element-caption">Hugo Jabini leads a kuutu, a meeting of Saamakan communities.&nbsp;</figcaption></figure>



<p>The Saamaka’s story is a common one. Indigenous Peoples and local communities hold some of the most pristine and resource-rich lands in the world — areas highly coveted by mining and logging companies and other profiteers.&nbsp; Land grabs and other threats are especially severe in places where the government does not recognize communities’ land rights, or where anti-deforestation and other laws are weak or poorly enforced. It’s the reason many Indigenous Peoples and local communities often take land monitoring into their own hands — and some are now using digital tools to do it.&nbsp;</p>



<p>Freely available satellite imagery and data from sites like&nbsp;<a href="https://www.globalforestwatch.org/map/">Global Forest Watch</a>&nbsp;and&nbsp;<a href="https://www.landmarkmap.org/data/" target="_blank" rel="noreferrer noopener">LandMark</a>&nbsp;provide near-real-time information that tracks deforestation and land degradation. Indigenous and local communities are increasingly using tools like this to gather evidence that deforestation and degradation are happening on their lands, build their case against illegal activities and take legal action to prevent it from continuing.&nbsp;&nbsp;</p>



<p>Three examples from Suriname, Indonesia and Peru illustrate a growing trend in fighting land rights violations with data.&nbsp;&nbsp;</p>



<h2 class="wp-block-heading">In Suriname, Deforestation Data Reveals Threats to the Saamaka’s Land Rights &nbsp;</h2>



<p>In 2007, the Inter-American Court of Human Rights compelled the government of Suriname to recognize the traditional land rights of the Saamaka and other Indigenous and community groups in Suriname. &nbsp;Yet satellite data from Global Forest Watch shows that since the judgment in 2007, tree cover loss actually increased in the Saamaka’s lands, largely from logging and mining activities. Tree cover loss inside government-granted logging concessions in and surrounding the Saamaka territory totaled 44,700 hectares, a 5.5% loss in tree cover from 2001-2022.&nbsp;&nbsp;</p>



<div class="flourish-embed flourish-chart" data-src="visualisation/15824378?240776"><script src="https://public.flourish.studio/resources/embed.js"></script></div>



<p>Monthly satellite images from March 2023 to October 2023 show the gradual construction of a road being carved through the heart of the Saamaka territory and leading to a government-granted logging concession. The Saamaka say the road was constructed without their knowledge or consent.&nbsp;</p>



<figure class="wp-block-image size-full"><img src="https://content.globalforestwatch.org/wp-content/uploads/2023/11/Suriname-logging-road.gif" alt="Gif of road construction progress through the Saamaka’s forested territory. March-October 2023" class="wp-image-16455"/><figcaption class="wp-element-caption">Road construction progresses through the Saamaka’s forested territory. Source: Planet imagery on Global Forest Watch.</figcaption></figure>



<p>Armed with this data and imagery, Jabini and seven other representatives from Suriname’s Indigenous and local communities traveled more than 2,500 miles to Washington, D.C., presenting their evidence to the Inter-American Commission on Human Rights in November 2023. Jabini hopes the commission will reopen its court case against the Suriname government to strengthen traditional land rights.&nbsp;&nbsp;</p>



<p>“We are not here to fight the government; we are just fighting for our rights,” Jabini said.</p>



<h2 class="wp-block-heading">In Indonesia, Indigenous Peoples Use Satellite Data to Track and Report Illegal Timber &nbsp;</h2>



<p>In the eastern-most edges of Indonesia lies an archipelago of 832 islands containing some of the country’s most pristine remaining rainforests. The Aru Islands are home to more than 60,000 Indigenous Aruese, who speak 14 different tribal languages. Their lives are deeply intertwined with the forests they call home, hunting deer, harvesting tree gum, and maintaining a strong spiritual connection with the forests believed to harbor the souls of their ancestors.</p>



<figure class="wp-block-image size-full"><img src="https://content.globalforestwatch.org/wp-content/uploads/2023/11/aru-islands-2.jpg" alt="Indonesia’s Aru Islands" class="wp-image-16458"/><figcaption class="wp-element-caption">Indonesia’s Aru Islands hold some of the country’s most pristine rainforests and are home to more than 60,000 Indigenous Aruese. Photo by Forest Watch Indonesia.</figcaption></figure>



<p>As forests in more easily accessible areas of Indonesia such as Java and Borneo have been cleared, increasing pressure for valuable timber species and land for growing crops like sugar has reached the shores of the Aru Islands. Aru Indigenous Peoples and&nbsp;<a href="https://fwi.or.id/en/" rel="noreferrer noopener" target="_blank">Forest Watch Indonesia (FWI),</a>&nbsp;a civil society organization, have been working together to monitor, document and halt illegal logging using satellite data.&nbsp;&nbsp;</p>



<p>Using&nbsp;<a href="https://www.globalforestwatch.org/blog/data-and-research/early-warning-systems-for-deforestation-an-explainer/">deforestation alerts</a>&nbsp;from Global Forest Watch, FWI conducts desk analyses to identify priority locations for forest monitoring. They train Aru Forest Monitors on how to navigate to areas of forest where satellites detected recent clearings, using the&nbsp;<a href="https://forestwatcher.globalforestwatch.org/">Forest Watcher mobile app</a>. They also document evidence of deforestation with the app by taking photos and recording written or audio observations of the causes of the clearing.&nbsp;</p>



<p>Forest Monitors then continually track the extraction of timber from these deforestation sites, oftentimes following the wood to local ports, photographing identifiable information of ships containing illegally harvested timber, and transmitting this information to FWI. The organization then synthesizes the information and passes it to Indonesian authorities, who can then intercept the ships when they dock in Java before reaching international waters. In February 2019, the evidence that Indigenous Forest Monitors documented prompted the Indonesian Ministry of Environment and Forestry to seize 38 containers of illegally harvested timber. High-profile examples like this can serve as a deterrent for future illegal logging.</p>



<h2 class="wp-block-heading">Indigenous Communities in Peru Deploy Technology to Reduce Illegal Deforestation and Strengthen Land Rights</h2>



<p>A&nbsp;<a href="https://www.globalforestwatch.org/blog/people/indigenous-forest-monitors-reduce-deforestation/">two-year study</a>&nbsp;in the Northeastern Amazon region of Peru found that communities who used satellite-based forest monitoring technologies and data significantly reduced deforestation on their lands.</p>



<p>Equipped with deforestation alerts accessed from Forest Watcher and Global Forest Watch, forest monitors representing 36 local communities patrolled their ancestral lands. They documented evidence of encroachment from illicit coca plantations and illegal logging, using satellite imagery, photos, written documentation and drone footage. The monitors presented this information in community assemblies to collectively determine what action to take. Depending on the situation, they then either asked the invaders to leave by showing evidence that they had crossed over into community lands, or submitted documentation to Peruvian law enforcement, who then followed up with official field investigations.&nbsp;</p>



<figure class="wp-block-image aligncenter size-full"><img src="https://content.globalforestwatch.org/wp-content/uploads/2023/11/p_paisa_20150105_113737-scaled-1.jpg" alt="" class="wp-image-16459"/><figcaption class="wp-element-caption">A community monitor in Remanso del Amazonas identifies early warning signs of deforestation. Photo by Beder Olortegui.</figcaption></figure>



<p>Ultimately, the communities that used forest monitoring technologies reduced deforestation in their territories by 52% in the first year and an additional 21% in the second year, as compared to a similar number of communities in a control group. The communities using monitoring technologies also reported higher satisfaction with forest governance.</p>



<p>Since the study concluded, communities with experience using monitoring technologies are now training communities in the control group to do the same. The communities who succeeded in reducing deforestation have also received direct payments from the&nbsp;<a href="https://rainforestfoundation.org/our-work/approaches/rainforest-alert/" rel="noreferrer noopener" target="_blank">Rainforest Foundation US’s Rainforest Alert program</a>, a payment system for keeping forests conserved.</p>



<p>Most recently, some communities allocated that funding towards strengthening and expanding legal recognition of their ancestral lands. Community land titling in Peru is a slow and bureaucratic process. With the funds, communities were able to georeference the limits of their lands; contract soil analysts, lawyers and Geographic Information System (GIS) specialists; and petition the government for land titles. They succeeded in obtaining titles to their territories in just 10 months – a process that normally takes years or even decades.</p>



<h2 class="wp-block-heading">Open Data Supports Communities, but More Secure Land Rights Are Essential&nbsp;</h2>



<p>Satellite data and imagery are critical tools because they provide transparent, independent evidence of suspected violations. They allow communities to rapidly monitor and document forest disturbances over large areas and long periods of time at low cost, thus reducing expensive field patrols. Moreover, much of the monitoring and documentation can be done remotely from the safety of a laptop, without risking face-to-face confrontation with encroachers. This is especially important because environmental defenders face growing threats. In 2022, at least&nbsp;<a href="https://www.globalwitness.org/en/campaigns/environmental-activists/standing-firm/" target="_blank" rel="noreferrer noopener">177 environmental defenders were killed</a>, 36% of whom were Indigenous.&nbsp;</p>



<p>Given the power of satellite data to help communities protect their land rights, data creators and managers need to ensure that communities continue to have access to open data and technology. Communities also need support in data use, including tailored&nbsp;<a href="https://www.globalforestwatch.org/grants-and-fellowships/about/">training resources</a>,&nbsp;<a href="https://www.globalforestwatch.org/grants-and-fellowships/about/" target="_blank" rel="noreferrer noopener">financial support</a>&nbsp;and facilitating the&nbsp;<a href="https://www.globalforestwatch.org/help/map/webinars/webinar-strengthening-the-role-of-indigenous-youth-in-forest-protection-perspectives-from-latin-america/">sharing of experiences</a>.</p>



<p>However, while satellite data helps communities document and take action on illegal deforestation and related infractions, governments ultimately need to recognize and enforce Indigenous Peoples’ and communities’ land rights. Stronger and more secure land rights — with higher penalties for infractions — are more likely to deter illegal activity from occurring in the first place, or at least ensure a swift and decisive end to violations.</p>



<p>Indigenous Peoples and local communities have stewarded their lands and natural resources for centuries. Though more secure land rights are ultimately needed, satellite data can help them manage threats to their lands now and conserve their homes for generations to come.</p>



<hr> 

<div class="attribute" style="”padding-bottom:" 10px;”="">
 

Originally appeared on <a href="https://www.wri.org/insights/indigenous-peoples-local-communities-use-satellite-data-deforestation" target="_blank" rel="noopener noreferrer">WRI Insights</a>. 
 

</div> 

 

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Communities are increasingly using tools like GFW to gather evidence of deforestation and degradation on their lands and take legal action.  

Communities Are Using Satellite Data to Fight Deforestation

An aerial shot shows the contrast between forest and agricultural landscapes near Rio Branco, Acre, Brazil.

Tropical Primary Forest Loss Worsened in 2022, Despite International Commitments to End Deforestation

La perte de forêts primaires tropicales s’est aggravée en 2022, malgré les engagements internationaux visant à mettre fin à la déforestation

Perda de florestas tropicais primárias piora em 2022 apesar dos compromissos internacionais para acabar com o desmatamento

Empeoró La Pérdida De Bosques Tropicales Primarios en 2022, A Pesar De Los Compromisos Internacionales Contra La Deforestación

Tingkat Kehilangan Hutan Primer Tropis pada tahun 2022 Memburuk, Terlepas dari Komitmen Global untuk Mengakhiri Deforestasi

Tropical primary forest loss was 10% higher in 2022 than in 2021 despite international commitments, according to new data on GFW.

Tropical Primary Forest Loss Worsened in 2022 | GFW Blog

Nancy Harris

Crystal Davis

Jan Hooijmans

<p>Today, we have more data about forests than ever before, but we still can’t seem to agree on where, when and why forests are changing around the world. Even two prominent global data sources appear to disagree, at least on the surface. “Deforestation continues globally, if at a slower pace” was <a href="https://www.fao.org/in-action/boosting-transparency-forest-data/news/detail/en/c/1293766/" target="_blank" rel="noreferrer noopener">the headline</a> of the <a href="https://www.fao.org/forest-resources-assessment/2020/en/" target="_blank" rel="noreferrer noopener">2020 Global Forest Resources Assessment (FRA)</a> published by the United Nations Food and Agriculture Organization (FAO). At the same time, Global Forest Watch (GFW) <a href="https://www.globalforestwatch.org/blog/data-and-research/global-tree-cover-loss-data-2020/">reported that</a> “primary rainforest destruction increased 12% from 2019 to 2020.”</p>



<p>What gives? Unfortunately, the answer is not simple. Both GFW and FRA provide valuable information on the state of global forests, but they differ substantially in terms of purpose, scope and approach. By answering questions on how and why these two global data sources differ, we can begin to see them as complementary rather than contradictory. Ultimately, our knowledge of global forests remains incomplete, and we need all the information we can get.</p>



<div class="textboxright"><strong>WHAT ARE GLOBAL FOREST WATCH (GFW) AND THE GLOBAL FOREST RESOURCES ASSESSMENT (FRA)?</strong> <br><br>GFW is an independent online forest monitoring platform launched in 2014 by a consortium of partners led by World Resources Institute. GFW seeks to empower forest managers, law enforcement officers and other forest stakeholders with free access to timely and high-resolution data about the current status of forests and recent forest change. GFW uses satellite technology to monitor tree cover loss worldwide with weekly and annual updates, as well as to provide 20-year tree cover gain and net change data. Gain, net change and annual loss data are GFW’s core data sets and are provided by the University of Maryland. Other data sets on GFW provide useful contextual information related to forests and forest change.<br><br>

The FRA, which the FAO has published at 5- to 10-year intervals since 1946, seeks to provide a consistent and comprehensive approach to describing the world’s forests and how they are changing. Countries provide reports to FRA based on data from National Forest Inventories, satellite data and extrapolation based on past data. The FAO combines the data submitted by countries into global reports and fills in any gaps where data is not available from the countries. The most recent edition of the FRA in 2020 included national-level statistics on more than 60 ecological and socio-economic variables reported by 236 countries and territories. </div>



<h2 class="wp-block-heading">What is considered a “forest”?</h2>



<p>GFW and FRA both talk about “forests,” but what are they actually measuring and monitoring? There are more than&nbsp;800 definitions&nbsp;of “forest” in use, which only adds to the confusion.</p>



<p>Every five years, FRA publishes forest area globally and per country. These area measurements are based on a <a href="http://www.fao.org/docrep/006/ad665e/ad665e03.htm" target="_blank" rel="noreferrer noopener">standardized&nbsp;definition</a>&nbsp;of “forest” adopted by the FAO in 2000, which takes into account biophysical and land use criteria. The biophysical criterion establishes minimum thresholds for the height, canopy cover and extent of trees. The land use criterion requires that land be officially or legally designated for a “forest use,” such as conservation or harvest. Land that contains trees but is designated for agricultural or urban uses — for example, an oil palm plantation, shade grown cocoa (agroforestry) or a city park — would not be considered a forest. At the same time, land that is temporarily devoid of trees — for example, recently logged or burned areas — would still be classified as forest if the official land use stipulates that trees will be allowed to regenerate in the future.</p>



<p>GFW provides data on “tree cover,” which is derived from satellite data and therefore cannot discern intended land use. Thus, GFW’s monitoring systems rely entirely on biophysical criteria — related to height, canopy cover and extent of trees. GFW does not adopt a specific definition of forest, but rather monitors all forms of tree cover including natural forests and tree plantations. Using GFW’s interactive online platform, users can filter this data based on their preferred definition of forest. Users can select by canopy cover percent, as well as tree height. Users can also view other data sets that give additional context on the land use such <a href="https://gfw.global/3jyrlta">primary forests</a> and <a href="https://gfw.global/2Qbv7fM">planted trees</a>.</p>



<div class="wp-block-image"><figure class="aligncenter size-large"><img decoding="async" loading="lazy" width="2048" height="1867" src="https://content.globalforestwatch.org/wp-content/uploads/2023/07/23_GFW_vs_FAO_graphics_What-is-considered-a-forest-1-2048x1867.png" alt="What is considered a "Forest" by GFW and FRA?" class="wp-image-16209" srcset="https://content.globalforestwatch.org/wp-content/uploads/2023/07/23_GFW_vs_FAO_graphics_What-is-considered-a-forest-1-2048x1867.png 2048w, https://content.globalforestwatch.org/wp-content/uploads/2023/07/23_GFW_vs_FAO_graphics_What-is-considered-a-forest-1-1024x934.png 1024w, https://content.globalforestwatch.org/wp-content/uploads/2023/07/23_GFW_vs_FAO_graphics_What-is-considered-a-forest-1-768x700.png 768w, https://content.globalforestwatch.org/wp-content/uploads/2023/07/23_GFW_vs_FAO_graphics_What-is-considered-a-forest-1-1536x1401.png 1536w" sizes="(max-width: 2048px) 100vw, 2048px" /></figure></div>



<h2 class="wp-block-heading">How is “forest change” reported?</h2>



<p>Both FRA and GFW aggregate monitoring data into global statistics about forest change. Like the different ways they measure forests, GFW and FRA apply different lenses to monitor <em>changes to</em> forests, which subsequently influence how both forest expansion and deforestation are reported. GFW reports annual gross loss of tree cover, as well as gross gain and net change for a 20-year period. FRA reports on deforestation, net change and forest expansion as separate statistics, though many countries only report forest area, from which net change can be derived.</p>



<h3 class="wp-block-heading">Deforestation and tree cover loss</h3>



<p>Using its land use criterion, the FAO’s definition of deforestation requires permanent land use change to occur. Losses of tree cover considered to be temporary (e.g., forests that have been clear cut but will be left to regrow) are not counted as deforestation.</p>



<p>Conversely, GFW detects and reports all instances of tree cover loss, regardless of whether the loss will be temporary or permanent (e.g., clear cut harvest followed by agriculture). As with forests, GFW does not seek to define deforestation but rather allows users to filter tree cover loss data based on their own preferred definition.</p>



<p>Though GFW data includes all forms of tree cover loss, data on certain drivers of loss is available on GFW, such as <a href="https://gfw.global/3eO7ZjW">tree cover loss due to fires</a> and <a href="https://gfw.global/39qbPdC">tree cover loss by dominant driver,</a> the latter of which can be used to better align with the definition of deforestation used by FRA. GFW uses the tree cover loss by dominant driver data to create a “<a href="https://research.wri.org/gfr/data-methods#forestchange1" target="_blank" rel="noreferrer noopener">deforestation proxy</a>” consisting of tree cover loss due to shifting agricultural expansion into primary forests, commodity-driven deforestation and urbanization.</p>



<p>FRA deforestation data is available for the 5- or 10-year reporting periods, while GFW tree cover loss data is available annually.</p>



<h3 class="wp-block-heading">Forest expansion, tree cover gain and reforestation</h3>



<p>As with the deforestation data, information on forest expansion is available for the FRA reporting periods of 5 or 10 years. In FRA, forest expansion can be due to afforestation or a natural expansion of forest area.</p>



<p>GFW data on tree cover gain is available for a 20-year time period, 2000-2020. Like with the tree cover data, GFW gain data includes regrowth in plantations following harvesting, which would not be included in forest expansion according to FRA.</p>



<p>FRA also provides reforestation data, which does not influence forest area or their net change figure. FRA defines reforestation as the planting of trees in areas already considered as forests by FAO’s land use criterion.</p>



<h3 class="wp-block-heading">Forest area and tree cover net change</h3>



<p>FRA and GFW report net change in forest and tree cover extent respectively. As with the tree cover gain data, the GFW net change data currently only compares 2000 to 2020. FRA data is available for their 5- or 10-year reporting periods.</p>



<div class="wp-block-image"><figure class="aligncenter size-large"><img decoding="async" loading="lazy" width="1275" height="1650" src="https://content.globalforestwatch.org/wp-content/uploads/2023/07/23_Forest_types_table-1.png" alt="What is forest area change for GFW and FRA?" class="wp-image-16210" srcset="https://content.globalforestwatch.org/wp-content/uploads/2023/07/23_Forest_types_table-1.png 1275w, https://content.globalforestwatch.org/wp-content/uploads/2023/07/23_Forest_types_table-1-791x1024.png 791w, https://content.globalforestwatch.org/wp-content/uploads/2023/07/23_Forest_types_table-1-768x994.png 768w, https://content.globalforestwatch.org/wp-content/uploads/2023/07/23_Forest_types_table-1-1187x1536.png 1187w" sizes="(max-width: 1275px) 100vw, 1275px" /></figure></div>



<h2 class="wp-block-heading">Where is the data from?</h2>



<p>FRA compiles official government statistics on forest-related information. This data is self-reported by countries and can come from different sources using a variety of methods, including national forest inventories (NFIs), academic studies, government registries or district forest offices. Remote sensing (RS) is becoming more frequently used as an input into some nationally reported data. Although FAO provides guidelines on what and how to report, in reality, many countries employ their own definitions and methods.</p>



<p>GFW features data that is based on satellite data, providing an independent, transparent and globally consistent record of Earth’s land surface and how it is changing. This record enables consistent comparisons across countries and over time.</p>



<div class="wp-block-image"><figure class="aligncenter size-large"><img decoding="async" loading="lazy" width="2048" height="1612" src="https://content.globalforestwatch.org/wp-content/uploads/2023/07/23_GFW_vs_FAO_graphics_Where-is-data-from-1-2048x1612.png" alt="Where is the data from for GFW and FRA?" class="wp-image-16211" srcset="https://content.globalforestwatch.org/wp-content/uploads/2023/07/23_GFW_vs_FAO_graphics_Where-is-data-from-1-2048x1612.png 2048w, https://content.globalforestwatch.org/wp-content/uploads/2023/07/23_GFW_vs_FAO_graphics_Where-is-data-from-1-1024x806.png 1024w, https://content.globalforestwatch.org/wp-content/uploads/2023/07/23_GFW_vs_FAO_graphics_Where-is-data-from-1-768x605.png 768w, https://content.globalforestwatch.org/wp-content/uploads/2023/07/23_GFW_vs_FAO_graphics_Where-is-data-from-1-1536x1209.png 1536w" sizes="(max-width: 2048px) 100vw, 2048px" /></figure></div>



<h2 class="wp-block-heading">When is the data collected and reported?</h2>



<p>FRA reports are released every 5 years based on countries’ reported information. Some countries update their forest information systems frequently, while others update them only every 10-20 years, meaning some FRA reports are based on older data. When country reports are unavailable, the FAO fills in gaps using available literature and expert estimates. <a href="https://iopscience.iop.org/article/10.1088/1748-9326/abd81b/meta" target="_blank" rel="noreferrer noopener">A study examining the 2020 FRA data sources</a> showed the most recent years in which RS and NFI data were collected and found that although many countries use data that are only a few years old, there are a number of countries using data over 30 years old.</p>



<p>GFW’s tree cover loss data set is updated each year with the previous year’s data. GFW’s net change and gain data covers the 20-year period from 2000 to 2020, with plans underway for more frequent updates.</p>



<div class="wp-block-image"><figure class="aligncenter size-large"><img decoding="async" loading="lazy" width="2048" height="1187" src="https://content.globalforestwatch.org/wp-content/uploads/2023/07/23_GFW_vs_FAO_graphics_When-is-data-reported-1-2048x1187.png" alt="When is the data reported for GFW and FRA?" class="wp-image-16212" srcset="https://content.globalforestwatch.org/wp-content/uploads/2023/07/23_GFW_vs_FAO_graphics_When-is-data-reported-1-2048x1187.png 2048w, https://content.globalforestwatch.org/wp-content/uploads/2023/07/23_GFW_vs_FAO_graphics_When-is-data-reported-1-1024x594.png 1024w, https://content.globalforestwatch.org/wp-content/uploads/2023/07/23_GFW_vs_FAO_graphics_When-is-data-reported-1-768x445.png 768w, https://content.globalforestwatch.org/wp-content/uploads/2023/07/23_GFW_vs_FAO_graphics_When-is-data-reported-1-1536x891.png 1536w" sizes="(max-width: 2048px) 100vw, 2048px" /></figure></div>



<h2 class="wp-block-heading">What is the unit of analysis?</h2>



<p>FRA collects statistics at the national scale, which are aggregated to provide insights about forest change dynamics regionally and globally.</p>



<p>Satellite-based data on GFW records changes in forest area by dividing Earth’s land surface into pixels. These pixels — which for most data on forest area and change are 30 m by 30 m in size — can then be aggregated to show changes over larger areas of interest. This modular format means that in addition to understanding forest dynamics at global, regional and national scales (as with the FRA), users can also monitor changes within custom areas of interest, such as a specific national park in their country, a provincial district, an Indigenous territory or even their own backyards.</p>



<div class="wp-block-image"><figure class="aligncenter size-large"><img decoding="async" loading="lazy" width="1275" height="1223" src="https://content.globalforestwatch.org/wp-content/uploads/2023/07/GFW_vs_FAO_graphics_final-05.png" alt="What is the unit of analysis for GFW vs FRA?" class="wp-image-16213" srcset="https://content.globalforestwatch.org/wp-content/uploads/2023/07/GFW_vs_FAO_graphics_final-05.png 1275w, https://content.globalforestwatch.org/wp-content/uploads/2023/07/GFW_vs_FAO_graphics_final-05-1024x982.png 1024w, https://content.globalforestwatch.org/wp-content/uploads/2023/07/GFW_vs_FAO_graphics_final-05-768x737.png 768w" sizes="(max-width: 1275px) 100vw, 1275px" /></figure></div>



<h2 class="wp-block-heading">What does it all mean?</h2>



<p>How one defines forest, deforestation, reforestation and forest expansion is at the heart of the confusion and controversies surrounding these two data sources. Critics of FRA point out that country-reported data may be outdated, inconsistent, incomplete or based on non-transparent methods. In addition, FAO’s net forest change statistic (which is the only forest change variable presented for many countries) provides an overly optimistic view of global forest trends since by their definition, the loss of natural forests — rich in biodiversity and carbon — can be offset by expansion of tree plantation monocultures. The same applies for GFW’s net change information when viewed without the contextual data sets.</p>



<p>Meanwhile, critics of GFW claim that satellite-based monitoring has fundamental limitations on what can be observed from satellites, and that tree cover loss creates an overly pessimistic view since these data lump together permanent and temporary loss of tree cover within natural forests and tree plantations. In the case of FRA, temporary loss is not included in deforestation information.</p>



<p>Ultimately, neither GFW nor FRA is perfect or complete, but they both have important, and complementary, applications.</p>



<h2 class="wp-block-heading">When might I use GFW or FRA?</h2>



<p>Bottom-up approaches like FRA benefit from locally appropriate methodologies, customization of data and use of country definitions — although many countries follow the FAO’s standard definitions. FRA is more comprehensive in scope, ranging from biophysical to socio-economic and legislative variables. FRA’s data will be relevant for those that have a broad interest in the state of forests in a country and how they are being managed.</p>



<p>However, FRA’s data is only reported on a national level and cannot be used for assessing regional differences within countries. GFW’s spatially precise updates on tree cover loss allow users to track where changes in tree cover are happening on a sub-national level. GFW also offers more consistency in methods and definitions across geographies for making comparisons across countries.</p>



<p>GFW currently provides more frequent tree cover loss information (annually) than FRA does on deforestation, while FRA currently provides more frequent updates on forest expansion than GFW does on tree cover gain — though GFW will eventually provide annual tree cover gain data. FRA’s figures also reflect tree planting initiatives that are too recent to be picked up by satellite data, although not all of these projects are successful.</p>



<p>In the end, the differences between GFW and FRA reveal strengths and shortcomings of both sources that make them appropriate for different applications, meaning that both are useful to understand what is happening with the world’s forests.</p>



<p></p>



<p><em>Rachael Petersen and Octavia Payne contributed to a previous version of this blog.</em></p>



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Global Forest Watch and the Forest Resources Assessment, Explained in 5 Graphics

<p>Today, we have more data about forests than ever before, but we still can’t seem to agree on where, when and why forests are changing around the world. Even two prominent global data sources appear to disagree, at least on the surface. “Deforestation continues globally, if at a slower pace” was <a href="https://www.fao.org/in-action/boosting-transparency-forest-data/news/detail/en/c/1293766/" target="_blank" rel="noreferrer noopener">the headline</a> of the <a href="https://www.fao.org/forest-resources-assessment/2020/en/" target="_blank" rel="noreferrer noopener">2020 Global Forest Resources Assessment (FRA)</a> published by the United Nations Food and Agriculture Organization (FAO). At the same time, Global Forest Watch (GFW) <a href="https://www.globalforestwatch.org/blog/data-and-research/global-tree-cover-loss-data-2020/">reported that</a> “primary rainforest destruction increased 12% from 2019 to 2020.”</p>



<p>What gives? Unfortunately, the answer is not simple. Both GFW and FRA provide valuable information on the state of global forests, but they differ substantially in terms of purpose, scope and approach. By answering questions on how and why these two global data sources differ, we can begin to see them as complementary rather than contradictory. Ultimately, our knowledge of global forests remains incomplete, and we need all the information we can get.</p>



<div class="textboxright"><strong>WHAT ARE GLOBAL FOREST WATCH (GFW) AND THE GLOBAL FOREST RESOURCES ASSESSMENT (FRA)?</strong> <br><br>GFW is an independent online forest monitoring platform launched in 2014 by a consortium of partners led by World Resources Institute. GFW seeks to empower forest managers, law enforcement officers and other forest stakeholders with free access to timely and high-resolution data about the current status of forests and recent forest change. GFW uses satellite technology to monitor tree cover loss worldwide with weekly and annual updates, as well as to provide 20-year tree cover gain and net change data. Gain, net change and annual loss data are GFW’s core data sets and are provided by the University of Maryland. Other data sets on GFW provide useful contextual information related to forests and forest change.<br><br>

The FRA, which the FAO has published at 5- to 10-year intervals since 1946, seeks to provide a consistent and comprehensive approach to describing the world’s forests and how they are changing. Countries provide reports to FRA based on data from National Forest Inventories, satellite data and extrapolation based on past data. The FAO combines the data submitted by countries into global reports and fills in any gaps where data is not available from the countries. The most recent edition of the FRA in 2020 included national-level statistics on more than 60 ecological and socio-economic variables reported by 236 countries and territories. </div>



<h2>What is considered a “forest”?</h2>



<p>GFW and FRA both talk about “forests,” but what are they actually measuring and monitoring? There are more than&nbsp;800 definitions&nbsp;of “forest” in use, which only adds to the confusion.</p>



<p>Every five years, FRA publishes forest area globally and per country. These area measurements are based on a <a href="http://www.fao.org/docrep/006/ad665e/ad665e03.htm" target="_blank" rel="noreferrer noopener">standardized&nbsp;definition</a>&nbsp;of “forest” adopted by the FAO in 2000, which takes into account biophysical and land use criteria. The biophysical criterion establishes minimum thresholds for the height, canopy cover and extent of trees. The land use criterion requires that land be officially or legally designated for a “forest use,” such as conservation or harvest. Land that contains trees but is designated for agricultural or urban uses — for example, an oil palm plantation, shade grown cocoa (agroforestry) or a city park — would not be considered a forest. At the same time, land that is temporarily devoid of trees — for example, recently logged or burned areas — would still be classified as forest if the official land use stipulates that trees will be allowed to regenerate in the future.</p>



<p>GFW provides data on “tree cover,” which is derived from satellite data and therefore cannot discern intended land use. Thus, GFW’s monitoring systems rely entirely on biophysical criteria — related to height, canopy cover and extent of trees. GFW does not adopt a specific definition of forest, but rather monitors all forms of tree cover including natural forests and tree plantations. Using GFW’s interactive online platform, users can filter this data based on their preferred definition of forest. Users can select by canopy cover percent, as well as tree height. Users can also view other data sets that give additional context on the land use such <a href="https://gfw.global/3jyrlta">primary forests</a> and <a href="https://gfw.global/2Qbv7fM">planted trees</a>.</p>



<div class="wp-block-image"><figure class="aligncenter size-large"><img src="https://content.globalforestwatch.org/wp-content/uploads/2023/07/23_GFW_vs_FAO_graphics_What-is-considered-a-forest-1-2048x1867.png" alt="What is considered a &quot;Forest&quot; by GFW and FRA?" class="wp-image-16209"/></figure></div>



<h2>How is “forest change” reported?</h2>



<p>Both FRA and GFW aggregate monitoring data into global statistics about forest change. Like the different ways they measure forests, GFW and FRA apply different lenses to monitor <em>changes to</em> forests, which subsequently influence how both forest expansion and deforestation are reported. GFW reports annual gross loss of tree cover, as well as gross gain and net change for a 20-year period. FRA reports on deforestation, net change and forest expansion as separate statistics, though many countries only report forest area, from which net change can be derived.</p>



<h3>Deforestation and tree cover loss</h3>



<p>Using its land use criterion, the FAO’s definition of deforestation requires permanent land use change to occur. Losses of tree cover considered to be temporary (e.g., forests that have been clear cut but will be left to regrow) are not counted as deforestation.</p>



<p>Conversely, GFW detects and reports all instances of tree cover loss, regardless of whether the loss will be temporary or permanent (e.g., clear cut harvest followed by agriculture). As with forests, GFW does not seek to define deforestation but rather allows users to filter tree cover loss data based on their own preferred definition.</p>



<p>Though GFW data includes all forms of tree cover loss, data on certain drivers of loss is available on GFW, such as <a href="https://gfw.global/3eO7ZjW">tree cover loss due to fires</a> and <a href="https://gfw.global/39qbPdC">tree cover loss by dominant driver,</a> the latter of which can be used to better align with the definition of deforestation used by FRA. GFW uses the tree cover loss by dominant driver data to create a “<a href="https://research.wri.org/gfr/data-methods#forestchange1" target="_blank" rel="noreferrer noopener">deforestation proxy</a>” consisting of tree cover loss due to shifting agricultural expansion into primary forests, commodity-driven deforestation and urbanization.</p>



<p>FRA deforestation data is available for the 5- or 10-year reporting periods, while GFW tree cover loss data is available annually.</p>



<h3>Forest expansion, tree cover gain and reforestation</h3>



<p>As with the deforestation data, information on forest expansion is available for the FRA reporting periods of 5 or 10 years. In FRA, forest expansion can be due to afforestation or a natural expansion of forest area.</p>



<p>GFW data on tree cover gain is available for a 20-year time period, 2000-2020. Like with the tree cover data, GFW gain data includes regrowth in plantations following harvesting, which would not be included in forest expansion according to FRA.</p>



<p>FRA also provides reforestation data, which does not influence forest area or their net change figure. FRA defines reforestation as the planting of trees in areas already considered as forests by FAO’s land use criterion.</p>



<h3>Forest area and tree cover net change</h3>



<p>FRA and GFW report net change in forest and tree cover extent respectively. As with the tree cover gain data, the GFW net change data currently only compares 2000 to 2020. FRA data is available for their 5- or 10-year reporting periods.</p>



<div class="wp-block-image"><figure class="aligncenter size-large"><img src="https://content.globalforestwatch.org/wp-content/uploads/2023/07/23_Forest_types_table-1.png" alt="What is forest area change for GFW and FRA?" class="wp-image-16210"/></figure></div>



<h2>Where is the data from?</h2>



<p>FRA compiles official government statistics on forest-related information. This data is self-reported by countries and can come from different sources using a variety of methods, including national forest inventories (NFIs), academic studies, government registries or district forest offices. Remote sensing (RS) is becoming more frequently used as an input into some nationally reported data. Although FAO provides guidelines on what and how to report, in reality, many countries employ their own definitions and methods.</p>



<p>GFW features data that is based on satellite data, providing an independent, transparent and globally consistent record of Earth’s land surface and how it is changing. This record enables consistent comparisons across countries and over time.</p>



<div class="wp-block-image"><figure class="aligncenter size-large"><img src="https://content.globalforestwatch.org/wp-content/uploads/2023/07/23_GFW_vs_FAO_graphics_Where-is-data-from-1-2048x1612.png" alt="Where is the data from for GFW and FRA?" class="wp-image-16211"/></figure></div>



<h2>When is the data collected and reported?</h2>



<p>FRA reports are released every 5 years based on countries’ reported information. Some countries update their forest information systems frequently, while others update them only every 10-20 years, meaning some FRA reports are based on older data. When country reports are unavailable, the FAO fills in gaps using available literature and expert estimates. <a href="https://iopscience.iop.org/article/10.1088/1748-9326/abd81b/meta" target="_blank" rel="noreferrer noopener">A study examining the 2020 FRA data sources</a> showed the most recent years in which RS and NFI data were collected and found that although many countries use data that are only a few years old, there are a number of countries using data over 30 years old.</p>



<p>GFW’s tree cover loss data set is updated each year with the previous year’s data. GFW’s net change and gain data covers the 20-year period from 2000 to 2020, with plans underway for more frequent updates.</p>



<div class="wp-block-image"><figure class="aligncenter size-large"><img src="https://content.globalforestwatch.org/wp-content/uploads/2023/07/23_GFW_vs_FAO_graphics_When-is-data-reported-1-2048x1187.png" alt="When is the data reported for GFW and FRA?" class="wp-image-16212"/></figure></div>



<h2>What is the unit of analysis?</h2>



<p>FRA collects statistics at the national scale, which are aggregated to provide insights about forest change dynamics regionally and globally.</p>



<p>Satellite-based data on GFW records changes in forest area by dividing Earth’s land surface into pixels. These pixels — which for most data on forest area and change are 30 m by 30 m in size — can then be aggregated to show changes over larger areas of interest. This modular format means that in addition to understanding forest dynamics at global, regional and national scales (as with the FRA), users can also monitor changes within custom areas of interest, such as a specific national park in their country, a provincial district, an Indigenous territory or even their own backyards.</p>



<div class="wp-block-image"><figure class="aligncenter size-large"><img src="https://content.globalforestwatch.org/wp-content/uploads/2023/07/GFW_vs_FAO_graphics_final-05.png" alt="What is the unit of analysis for GFW vs FRA?" class="wp-image-16213"/></figure></div>



<h2>What does it all mean?</h2>



<p>How one defines forest, deforestation, reforestation and forest expansion is at the heart of the confusion and controversies surrounding these two data sources. Critics of FRA point out that country-reported data may be outdated, inconsistent, incomplete or based on non-transparent methods. In addition, FAO’s net forest change statistic (which is the only forest change variable presented for many countries) provides an overly optimistic view of global forest trends since by their definition, the loss of natural forests — rich in biodiversity and carbon — can be offset by expansion of tree plantation monocultures. The same applies for GFW’s net change information when viewed without the contextual data sets.</p>



<p>Meanwhile, critics of GFW claim that satellite-based monitoring has fundamental limitations on what can be observed from satellites, and that tree cover loss creates an overly pessimistic view since these data lump together permanent and temporary loss of tree cover within natural forests and tree plantations. In the case of FRA, temporary loss is not included in deforestation information.</p>



<p>Ultimately, neither GFW nor FRA is perfect or complete, but they both have important, and complementary, applications.</p>



<h2>When might I use GFW or FRA?</h2>



<p>Bottom-up approaches like FRA benefit from locally appropriate methodologies, customization of data and use of country definitions — although many countries follow the FAO’s standard definitions. FRA is more comprehensive in scope, ranging from biophysical to socio-economic and legislative variables. FRA's data will be relevant for those that have a broad interest in the state of forests in a country and how they are being managed.</p>



<p>However, FRA's data is only reported on a national level and cannot be used for assessing regional differences within countries. GFW’s spatially precise updates on tree cover loss allow users to track where changes in tree cover are happening on a sub-national level. GFW also offers more consistency in methods and definitions across geographies for making comparisons across countries.</p>



<p>GFW currently provides more frequent tree cover loss information (annually) than FRA does on deforestation, while FRA currently provides more frequent updates on forest expansion than GFW does on tree cover gain — though GFW will eventually provide annual tree cover gain data. FRA’s figures also reflect tree planting initiatives that are too recent to be picked up by satellite data, although not all of these projects are successful.</p>



<p>In the end, the differences between GFW and FRA reveal strengths and shortcomings of both sources that make them appropriate for different applications, meaning that both are useful to understand what is happening with the world’s forests.</p>



<p></p>



<p><em>Rachael Petersen and Octavia Payne contributed to a previous version of this blog.</em></p>



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Both GFW and FRA provide valuable information on the state of forests, and they both have important, and complementary, applications.

Global Forest Watch and Forest Resources Assessment | GFW Blog