MAAP, an initiative of Amazon Conservation, specializes in satellite-based, real-time deforestation monitoring of the Amazon. Our geographic focus covers five countries: Bolivia, Brazil, Colombia, Ecuador, and Peru (see Base Map).

We found that, since 2001, this vast area lost 65.8 million acres (26.6 million hectares) of primary forest, an area equivalent to the size of the United Kingdom (or the U.S. state of Colorado).

Base Map. Amazon Deforestation, 2001-2019. Data: UMD/GLAD, Hansen/UMD/Google/USGS/NASA, MAAP. Click to see image in high resolution.

In 2019, we published 18 high-impact reports on the most urgent cases of deforestation. 2019 highlights include:

• Fires in the Brazilian Amazon actually burned freshly deforested areas (MAAP #113);
• Effective illegal gold mining crackdown in the Peruvian Amazon as a result of the government’s Operation Mercury (MAAP #104);
• Illegal invasion of protected areas in the Colombian Amazon (MAAP #106);
• Construction of oil-drilling platforms in the mega-diverse Yasuni National Park of the Ecuadorian Amazon (MAAP #114).

Here, in our annual Synthesis Report, we go beyond these emblematic cases and look at the bigger picture for 2019, describing the most important deforestation trends and hotspots across the Amazon.

*Note: to download a PDF, click the “Print” button below the title.

Synthesis Key Findings

• Possible major deforestation decrease in the Colombian Amazon following a dramatic increase over the previous three years;
• Likely major deforestation increase in the Bolivian Amazon due to forest fires;
• Downward deforestation trend continues in the Peruvian Amazon, but still historically high;
• Deforestation of 2.4 million acres in the Brazilian Amazon, but the trend depends on the data source.

Deforestation Trends 2001-2019

The following GIF shows deforestation trends for each country between 2001 and 2019 (see descriptive notes below). Click here for static versions of each graph.

Three important points about the data: First, as a baseline, we use annual forest loss from the University of Maryland to have a consistent source across all five countries (thus it may differ from official national data). Second, we applied a filter to only include loss of primary forest (see Methodology). Third, the 2019 data represents a preliminary estimate based on early warning alerts.

1. Deforestation in the Ecuadorian Amazon is relatively low, reaching a maximum of 18,800 hectares (46,500 acres) in 2017. The estimate for 2019 is 11,400 hectares (28,000 acres).
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2. In the Bolivian Amazon, deforestation decreased in 2018 to 58,000 hectares (143,000 acres) after a peak in 2016 of 122,000 hectares (302,000 acres). However, with the recent widespread forest fires, deforestation increased again in 2019, to 135,400 hectares (334,465 acres).
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3. The Colombian Amazon experienced a deforestation boom starting in 2016 (coinciding with the FARC peace accords), reaching an historical high of 153,800 hectares (380,000 acres) in 2018. However, the deforestation estimate for 2019 is back to pre-boom levels at 53,800 hectares (133,000 acres).
   .
4. Deforestation in the Peruvian Amazon declined in 2018 (compared to 2017) to 140,000 hectares (346,325 acres), but remained relatively high compared to historical data. The official deforestation data from the Peruvian government for 2018 is slightly higher at 154,700 hectares (382,272 acres), but also represents an important reduction compared to 2017. The deforestation estimate for 2019 indicates the continued downward trend to 134,600 hectares (332,670 acres).
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5. Deforestation in the Brazilian Amazon is on another level compared to the other four countries. The 2019 deforestation estimate of 985,000 hectares (2.4 million acres) is consistent with the official data of the Brazilian government. The trend, however, is quite different; we show a decrease in deforestation compared to the previous three years, but the official data indicates an increase. To better understand the differences between data sources (including spatial resolution, inclusion of burned areas, and timeframe), consult this blog by Global Forest Watch.

Deforestation Hotspots 2019

Base Map shows the most intense deforestation hotspots during 2019.

Base Map. Amazon Deforestation, 2001-2019. Data: UMD/GLAD, Hansen/UMD/Google/USGS/NASA, MAAP. Click to see image in high resolution.

Many of the major deforestation hotspots were in Brazil. The letters A indicate areas deforested between March and July, and then burned starting in August, covering over 735,000 acres in the states of Rondônia, Amazonas, Mato Grosso, Acre, and Pará (MAAP #113). They also indicate areas where fire escaped into the surrounding primary forest, impacting an additional 395,000 acres. There is a concentration of these hotspots along the Trans-Amazonian Highway. The letter B indicates uncontrolled forest fires earlier in the year (March) in the state of Roraima (MAAP #109).

Bolivia also had an intense 2019 fire season. Letter C indicates the area where fires in Amazonian savanna ecosystems escaped to the surrounding forests.

In Colombia, the letter D indicates an area of high deforestation surrounding and within four protected areas: Tinigua, Chiribiquete, and Macarena National Parks, and the Nukak National Reserve (MAAP #106).

In Peru, there are several key areas to highlight. Letter E indicates a new Mennonite colony that has caused the deforestation of 2,500 acres in 2019, near the town of Tierra Blanca in the Loreto region (MAAP #112). Letter F indicates an area of high concentration of small-scale deforestation in the central Amazon (Ucayali and Huánuco regions), with cattle ranching as one of the main causes (MAAP #37). Letter G indicates an area of high concentration of deforestation along the Ene River (Junín and Ayacucho regions). In the south (Madre de Dios region), letter H indicates expanding agricultural activity around the town of Iberia (MAAP #98) and letter I indicates deforestation caused by a combination of gold mining and agricultural activity.

Methodology

As noted above, there are three important considerations about the data in our analysis: First, as a baseline, we use annual forest loss from the University of Maryland to have a consistent source across all five countries. Thus, the values may differ from official national data. Second, we applied a filter to only include loss of primary forest in order to better approximate the official methodology and data. Third, the 2019 data represents a preliminary estimate based on early warning alerts.

The baseline forest loss data presented in this report were generated by the Global Land Analysis and Discovery (GLAD) laboratory at the University of Maryland (Hansen et al 2013) and presented by Global Forest Watch. Our study area is strictly what is highlighted in the Base Map.

Specifically, for our estimate of forest cover loss, we multiplied the annual “forest cover loss” data by the density percentage of the “tree cover” from the year 2001 (values >30%).

For our estimate of primary forest loss, we intersected the forest cover loss data with the additional dataset “primary humid tropical forests” as of 2001 (Turubanova et al 2018). For more details on this part of the methodology, see the Technical Blog from Global Forest Watch (Goldman and Weisse 2019).

All data were processed under the geographical coordinate system WGS 1984. To calculate the areas in metric units the UTM (Universal Transversal Mercator) projection was used: Peru and Ecuador 18 South, Colombia 18 North, Western Brazil 19 South and Bolivia 20 South.

Lastly, to identify the deforestation hotspots, we conducted a kernel density estimate. This type of analysis calculates the magnitude per unit area of a particular phenomenon, in this case forest cover loss. We conducted this analysis using the Kernel Density tool from Spatial Analyst Tool Box of ArcGIS. We used the following parameters:

Search Radius: 15000 layer units (meters)
Kernel Density Function: Quartic kernel function
Cell Size in the map: 200 x 200 meters (4 hectares, 9.88 acres)
Everything else was left to the default setting.

For the Base Map, we used the following concentration percentages: Medium: 10%-20%; High: 21%-35%; Very High: >35%.

References

Goldman L, Weisse M (2019) Explicación de la Actualización de Datos de 2018 de Global Forest Watch. https://blog.globalforestwatch.org/data-and-research/blog-tecnico-explicacion-de-la-actualizacion-de-datos-de-2018-de-global-forest-watch

Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, and J. R. G. Townshend. 2013. “High-Resolution Global Maps of 21st-Century Forest Cover Change.” Science 342 (15 November): 850–53. Data available on-line from: http://earthenginepartners.appspot.com/science-2013-global-forest.

Planet Team (2017). Planet Application Program Interface: In Space for Life on Earth. San Francisco, CA. https://api.planet.com

Turubanova S., Potapov P., Tyukavina, A., and Hansen M. (2018) Ongoing primary forest loss in Brazil, Democratic Republic of the Congo, and Indonesia. Environmental Research Letters  https://doi.org/10.1088/1748-9326/aacd1c 

Acknowledgements

Agradecemos a S. Novoa (ACCA), R. Botero (FCDS), A. Condor (ACCA) y G. Palacios por sus útiles comentarios a este reporte.

Acknowledgements

We thank S. Novoa (ACCA), R. Botero (FCDS), A. Condor (ACCA), A. Folhadella (Amazon Conservation), M. Cohen, and G. Palacios for helpful comments to earlier versions of this report.

This work was supported by the following major funders: NASA/USAID (SERVIR), Norwegian Agency for Development Cooperation (NORAD), Gordon and Betty Moore Foundation, International Conservation Fund of Canada (ICFC), Metabolic Studio, Erol Foundation, MacArthur Foundation, and Global Forest Watch Small Grants Fund (WRI).

Citation

Finer M, Mamani N (2020) MAAP Synthesis: 2019 Amazon Deforestation Trends and Hotspots. MAAP Synthesis #4.

For the 100th MAAP report, we present our first large-scale western Amazon analysis: Colombia, Peru, Ecuador, Bolivia, and western Brazil (see Base Map).

We use the new 2018 data for forest cover loss, generated by the  University of Maryland (Hansen et al 2013) and presented by Global Forest Watch.

These data indicate 2.5 million acres of forest cover loss in the western Amazon in 2018.*

We conducted an additional analysis that indicates, of this total, 1.9 million acres were primary forest.*

Base Map. Deforestation Hotspots in the western Amazon. Data: Hansen/UMD/Google/USGS/NASA, GFW, SERNANP, SNAP, SINAP, SERNAP, RAISG

To identify deforestation hotspots consistently across this vast landscape, we conducted a kernel density analysis (see Methodology).

The Base Map shows the hotspots in yellow, orange and red, indicating areas with medium, high, and very high forest loss concentrations, respectively.

Next, we focus on five zones of interest (Zooms A-E) in Colombia, Brazil, Bolivia, and Peru. For all images, please click to enlarge.

*Forest Cover Loss: 5 acres per minute. Almost half (49%) occurred in Brazil, followed by Peru (20%), Colombia (20%), Bolivia (8%), and Ecuador (3%). see Annex.

**Primary Forest Loss: 3.5 acres per minute. Over half (53%) occurred in Brazil, followed by Peru (20%), Colombia (18%), Bolivia (7%), and Ecuador (2%). see Annex.

Colombia

The largest concentration of 2018 forest loss is in the northeast Colombian Amazon (494,000 acres). Out of this total, 11% (56,800 acres) occurred in national parks. National experts indicate that land grabbing has emerged as a leading direct driver of deforestation (Arenas 2018). See MAAP #97 for more information.

Zoom A shows the forest loss expanding towards western Chiribiquete National Park, including distinct deforestation in this protected area during 2018.

Zoom B shows the extensive 2018 deforestation (30,000 acres) within Tinigua National Park. A recent news report indicates that cattle ranching is one of the factors related to this deforestation.

Zoom A. Colombia-Chiribiquete. Data: Hansen/UMD/Google/USGS/NASA, SINAP, Planet, ESA

Zoom B. Colombia – Tinigua. Data: Hansen/UMD/Google/USGS/NASA, SINAP, Planet, ESA

Brazil (border with Bolivia)

Another important result is the contrast between northern Bolivia (Pando department) and adjacent side Brazil (states of Acre, Amazonas, and Rondônia). Zoom C shows several deforestation hotspots on the Brazilian side, while the Bolivian side is much more intact.

Zoom C. Brazil, Bolivia border. Data: Hansen/UMD/Google/USGS/NASA, ESA, RAISG

Bolivia

In Bolivia, the major forest loss hotspots are further south. Zoom D shows the recent deforestation (5,000 acres in 2018) due to agricultural activity associated with one of the first major Mennonite settlements in Beni department (Kopp 2015). The other Mennonite settlements are located further south.

Zoom D. Bolivia, Black River Mennonite settlement. Data: Hansen/UMD/Google/USGS/NASA, SERNAP, Planet

Peru

The Hansen data indicates over 200,000 acres of forest loss during 2018 in the Peruvian Amazon. One of the most important deforestation drivers, especially in southern Peru, is gold mining. We estimate 23,000 acres of gold mining deforestation during 2018 in the southern Peruvian Amazon (see MAAP #96).

Zoom E shows the most emblematic case of gold mining deforestation: the area known as La Pampa.

It is important to emphasize, however, that in February 2019 the Peruvian government launched “Operation Mercury 2019” (Operación Mercurio 2019), a multi-sectoral and comprehensive mega-operation aimed at eradicating illegal mining and associated crime in La Pampa, as well as promote development in the region.

Zoom D. Peru – La Pampa. Data: Hansen/UMD/Google/USGS/NASA, SERNAP, Planet

Annex

Annex. Forest cover and primary forest loss in the western Amazon.  Data: Hansen/UMD/Google/USGS/NASA, Global Forest Watch.

Methods

The 2018 forest loss data presented in this report were generated by the Global Land Analysis and Discovery (GLAD) laboratory at the University of Maryland (Hansen et al 2013) and presented by Global Forest Watch. Our study area is strictly what is presented in the Base Map: the areas within the Amazonian biogeographic boundary of the western Amazon.

Specifically, for our estimate of forest cover loss, we multiplied the annual “forest cover loss” data by the density percentage of the “tree cover” from the year 2000 (values >30%).

For our estimate of primary forest loss, we intersected the forest cover loss data with the additional dataset “primary humid tropical forests” as of 2001 (Turubanova et al 2018). For more details on this part of the methodology, see the Technical Blog from Global Forest Watch (Goldman and Weisse 2019).

All data were processed under the geographical coordinate system WGS 1984. To calculate the areas in metric units the UTM (Universal Transversal Mercator) projection was used: Peru and Ecuador 18 South, Colombia 18 North, Western Brazil 19 South and Bolivia 20 South.

Lastly, to identify the deforestation hotspots, we conducted a kernel density estimate. This type of analysis calculates the magnitude per unit area of a particular phenomenon, in this case forest cover loss. We conducted this analysis using the Kernel Density tool from Spatial Analyst Tool Box of ArcGIS. We used the following parameters:

Search Radius: 15000 layer units (meters)

Kernel Density Function: Quartic kernel function

Cell Size in the map: 200 x 200 meters (4 hectares / 9.88 acres)

Everything else was left to the default setting.

For the Base Map, we used the following concentration percentages: Medium: 10%-20%; High: 21%-35%; Very High: >35%.

References

Arenas M (2018) Acaparamiento de tierras: la herencia que recibe el nuevo gobierno de Colombia. Mongabay, 2 AGOSTO 2018. https://es.mongabay.com/2018/08/acaparamiento-de-tierras-colombia-estrategias-gobierno/

Goldman L, Weisse M (2019) Technical Blog: Global Forest Watch’s 2018 Data Update Explained. https://blog.globalforestwatch.org/data-and-research/blog-tecnico-explicacion-de-la-actualizacion-de-datos-de-2018-de-global-forest-watch

Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, and J. R. G. Townshend. 2013. “High-Resolution Global Maps of 21st-Century Forest Cover Change.” Science 342 (15 November): 850–53. Data available on-line from: http://earthenginepartners.appspot.com/science-2013-global-forest.

Kopp Ad (2015) Las colonias menonitas en Bolivia. Tierra. http://www.ftierra.org/index.php/publicacion/libro/147-las-colonias-menonitas-en-bolivia

Planet Team (2017). Planet Application Program Interface: In Space for Life on Earth. San Francisco, CA. https://api.planet.com

Turubanova S., Potapov P., Tyukavina, A., and Hansen M. (2018) Ongoing primary forest loss in Brazil, Democratic Republic of the Congo, and Indonesia. Environmental Research Letters  https://doi.org/10.1088/1748-9326/aacd1c 

Acknowledgements

We thank M. Terán (ACEAA), M. Weisse (GFW/WRI), A. Thieme (UMD), R. Catpo (ACCA) and A. Cóndor (ACCA) for helpful comments to this report.

Citation

Finer M, Mamani N (2019) Western Amazon – Deforestation Hotspots 2018 (a regional perspective). MAAP: 100.