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<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

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.