Peru

MAAP #217: Carbon across the Amazon (part 2): Peak Carbon Areas

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Figure 1. Example of peak carbon areas in southern Peru and adjacent western Brazil. Data: Planet.

In part 1 of this series (MAAP #215), we introduced a critical new resource (Planet Forest Carbon Diligence) that provides wall-to-wall estimates for aboveground carbon density at an unprecedented 30-meter resolution. This data uniquely merges machine learning, satellite imagery, airborne lasers, and a global biomass dataset from GEDI, a NASA mission.4

In that report, we showed that the Amazon contains 56.8 billion metric tons of aboveground carbon (as of 2022), and described key patterns across all nine countries of the Amazon biome over the past decade.

Here, in part 2, we focus on the peak carbon areas of the Amazon that are home to the highest aboveground carbon levels.

These peak carbon areas correspond to the upper one-third of aboveground carbon density levels (>140 metric tons per hectare).1

They likely have experienced minimal degradation (such as selective logging, fire, and edge/fragmentation effects)2 and are thus a good proxy for high-integrity forests.

Figure 1 shows an important example of peak carbon areas in southern Peru and adjacent western Brazil.

The peak carbon areas are often found in the remote primary forests of protected areas and Indigenous territories, but some are located in forestry concessions (specifically, logging concessions) or undesignated lands (also referred to as undesignated public forests).

Our goal in this report is to leverage unprecedented aboveground carbon data to reinforce the importance of these designated areas and draw attention to the remaining undesignated lands.

For example, peak carbon areas would be excellent candidates for the High Integrity Forest (HIFOR) initiative, a new financing instrument that uniquely focuses on maintaining intact tropical forests.3 HIFOR rewards the climate services that intact tropical forests provide, including ongoing net carbon removal from the atmosphere, and complements existing instruments to reduce emissions from deforestation and degradation (REDD+) by focusing on tropical forests that are largely undegraded.

Below, we detail the major findings and then zoom in on the peak carbon areas in the northeast and southwest Amazon.

Peak Carbon Areas in the Amazon   

The Base Map below illustrates our major findings.

The peak carbon areas (>140 metric tons per hectare; indicated in pink) are concentrated in the southwest and northeast Amazon, covering 27.8 million hectares (11 million ha in the southwest and 16.8 million ha in the northeast).
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Base Map. Planet Forest Carbon Diligence across the Amazon biome for the year 2022. Data: Planet.

In the southwest Amazon, peak carbon levels are found in southern & central Peru, and adjacent western Brazil.

In the northeast Amazon, peak carbon levels are found in northeast Brazil, much of French Guiana, and parts of Suriname.

By country, Brazil and Peru have the largest area of peak carbon (10.9 million and 10.1 million hectares respectively), followed by French Guiana (4.7 million ha), and Suriname (2.1 million ha).

Protected areas and Indigenous territories cover much (61%) of the peak carbon area (16.9 million hectares).

The remaining 39% remains unprotected, and arguably threatened, in undesignated lands (9.4 million hectares) and forestry concessions (1.5 million ha), respectively.

In addition, high carbon areas (>70 metric tons per hectare; indicated by the greenish-yellow coloration in the Base Map) are found in all nine countries of the Amazon biome, notably Colombia, Ecuador, Bolivia, Venezuela, and Guyana.

Southwest Amazon

­Southern Peru

Figure 2a. Peak carbon area in the southern Peruvian Amazon. Data: Planet, SERNANP, RAISG.

Figure 2a zooms in on the peak carbon area covering 7.9 million hectares in southern Peru (regions of Madre de Dios, Cusco, and Ucayali) and adjacent southwest Brazil (Acre).

Several protected areas (such as Manu and Alto Purús National Parks, and Machiguenga Communal Reserve) anchor this area.

It is also home to numerous Indigenous territories (such as Mashco Piro, Madre de Dios, and Kugapakori, Nahua, Nanti & Others Indigenous Reserves).

 

 

 

 

 

 

 

 

 

 

Figure 2b highlights the major land designations within the peak carbon area of southern Peru.

Figure 2b. Peak carbon areas (outlined in pink), categorized by land designation in southern Peru and adjacent western Brazil. Data: Planet, NICFI, SERNANP, SERFOR, RAISG.

Protected areas and Indigenous territories cover 77% of this area (green and brown, respectively).

The remaining 23% could be considered threatened, as they are located in forestry concessions or undesignated lands (orange and red, respectively). Thus, these areas are ideal candidates for increased protection to maintain their peak carbon levels.

 

 

 

 

 

 

 

 

 

 

 

Central Peru

Figure 3a. Peak carbon area in the central Peruvian Amazon. Data: Planet, SERNANP, RAISG.

Figure 3a zooms in on the peak carbon area in the central Peruvian Amazon, which covers 3.1 million hectares in the regions of Ucayali, Loreto, Huánuco, Pasco, and San Martin.

Several protected areas (including Sierra del Divisor, Cordillera Azul, Rio Abiseo, and Yanachaga–Chemillén National Parks, and El Sira Communal Reserve) anchor this area.

It is also home to numerous Indigenous territories (such as Kakataibo, Isconahua, and Yavarí Tapiche Indigenous Reserves).

 

 

 

 

 

 

 

 

 

 

Figure 3b. Peak carbon areas (outlined in pink), categorized by land designation in central Peru. Data: Planet, NICFI, SERNANP, SERFOR, RAISG.

Figure 3b highlights the major land designations within the peak carbon area of central Peru.

Protected areas and Indigenous territories cover 69% of this area (green and brown, respectively).

The remaining 31% could be considered threatened, as they are located in forestry concessions or undesignated lands (orange and red, respectively), and are ideal candidates for increased protection.

 

 

 

 

 

 

 

 

 

 

 

 

 

Northeast Amazon

Figure 4a. Peak carbon area in the tri-border region of the northeast Amazon. Data: Planet, RAISG.

Figure 4a zooms in on the peak carbon area in the tri-border region of the northeast Amazon, which covers 16.8 million hectares in northern Brazil, French Guiana, and Suriname.

Several protected areas (including Montanhas do Tumucumaque National Park in northeast Brazil, Amazonien de Guyane National Park in French Guiana, and Central Suriname Nature Reserve) anchor this area.

It is also home to numerous Indigenous territories (such as Tumucumaque, Rio Paru de Este, and Wayãpi in northeast Brazil).

 

 

 

 

 

 

Figure 4b. Peak carbon areas (outlined in pink), categorized by land designation in northeast Amazon. Data: Planet, NICFI, RAISG.

Figure 4b highlights the major land designations within the peak carbon area of the northeast Amazon.

Protected areas and Indigenous territories cover just over half (51%) of this area (green and brown, respectively).

The remaining 49% could be considered threatened, as they are located in undesignated lands, and are ideal candidates for increased protection.

 

 

 

 

 

 

 

 

 

Notes

1 We selected this value (upper 33%) to capture the highest aboveground carbon areas and include a range of high carbon areas. Additional analyses could target different values, such as the highest 10% or 20% of aboveground carbon.

2  A recent paper documented a strong relationship between selective logging and aboveground carbon loss (Csillik et al. 2024, PNAS). The link between forest edges and carbon is presented in Silva Junior et al, Science Advances.

3 High Integrity Forest (HIFOR) units are a new tradable asset that recognizes and rewards the essential climate services and biodiversity conservation that intact tropical forests provide, including ongoing net removal of CO2 from the atmosphere. For more information see https://www.wcs.org/our-work/climate-change/forests-and-climate-change/hifor

4 For more information, see the “What is Forest Carbon Diligence?” section in this recent blog from Planet.

Citation

Finer M, Mamani N, Anderson C, Rosenthal A (2024) Carbon across the Amazon (part 2): Peak Carbon Areas. MAAP #217.

MAAP #218: Killing of Environmental Defenders in the Peruvian Amazon

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Peruvian environmental defender Edwin Chota was murdered by illegal loggers in 2014 for attempting to protect his Indigenous community from Exploitation. See Illegal Logging section. Photo: NYT/Tomas Munita.

 

 

 

 

 

 

 

 

 

 

 

 

 

Amazon Conservation’s MAAP program specializes in reporting on the most urgent deforestation threats facing the Amazon and producing big-picture analyses of key Amazon-wide issues.

This report uniquely presents a view into the complicated but critical issue of murders of environmental defenders, examining the relationship between the location of these killings and deforestation in the Peruvian Amazon to provide a better understanding of the context of their deaths.

Between 2010 and 2022, an estimated 29 Peruvian environmentalists and Indigenous leaders were killed while defending various parts of Peru’s Amazon from invaders seeking to exploit its resources (RAISG 2022).

Importantly, the frequency of these murders has increased in recent years, with nearly half (14 out of 29) occurring since 2020.

Our findings indicate that these murders are connected to five major issues in the Peruvian Amazon:
Illegal gold mining, Illegal logging, Illicit crops (coca), Land trafficking, and Protesting.

This report focuses on the first three (Illegal gold mining, Illegal logging, and Illicit crops).

Base Map

Base Map. Location of the 29 environmental defenders murdered in Peru and the suspected causes related to major environmental threats in the region 2010-2022. Sources: IBC, MINJUS, SERNANP, Conservación Amazónica-ACCA.

The Base Map shows the location of the 29 documented environmental defenders killed in Peru between 2010-2022.

It also indicates the environmental threat related to each death as the suspected or confirmed motive for the crime: Illegal Gold Mining, Illegal Logging, Illicit Crops (coca), Land Trafficking, and Protest.

Note that many of the murders occurred in geographic clusters that coincide with the major environmental conflict of that specific area.

For example, gold mining is a major cause of conflict in the southern Peruvian Amazon, while illegal logging and illicit crops are more common threats in the central Peruvian Amazon.

Murders related to Illegal Gold Mining

Illegal gold mining has long been, and continues to be, a major issue in the southern Peruvian Amazon (Madre de Dios region), particularly in Indigenous territories and protected area buffer zones (MAAP#208).

For example, Figure 1 illustrates the extensive gold mining deforestation (indicated in orange) in the Tambopata National Reserve buffer zone and surrounding Indigenous territories.

Figure 1. Three cases of environmental defender deaths related to illegal mining. Sources: IBC, MINJUS, SERNANP, Conservación Amazónica-ACCA.

Since 2015, three environmental defenders have been killed within or near the Tambopata National Reserve buffer zone (see yellow dots in Figure 1). All three cases involved forestry concessionaires trying to defend their concession from illegal mining invasion.

In 2015, Alfredo Vracko Neuenschwander was killed near the critical mining area known as “La Pampa” located in the core of the buffer zone. Note that during the two years prior to his death, more than 1,700 hectares were deforested in La Pampa due to illegal gold mining (MAAP #1). Vracko, who was president of the Madre de Dios Federation of Forestry and Reforestation Concessionaires at the time, is believed to have been killed by illegal miners who were scheduled to be evicted from his forestry concession on the same day. However, his murder remains officially unsolved.

In 2020, Roberto Carlos Pacheco Villanueva was killed just outside the Tambopata buffer zone. Villanueva owned a forestry concession that had been illegally deforested and burned by invaders linked to illegal mining. Having filed legal complaints about the illegal use of his land, Villanueva faced numerous threats against his life in the years leading up to his murder. While still unsolved, it is believed that his murder was committed by the same miners who invaded his concession.

More recently, in 2022, Juan Julio Fernández Hanco was murdered just off the Interoceanic Highway near the edge of the Tambopata buffer zone. During this period (2021-2023), nearly 24,000 hectares were deforested due to gold mining in this area (MAAP #195). The investigation is ongoing, with the suspects being illegal miners who invaded Juan Julio’s reforestation concessions.

Murders related to Illegal Logging

Illegal logging has been a significant problem across the Peruvian Amazon for years. A recent report revealed that over 20% of timber harvested in Peru in 2021 came from illegal origins (OSINFOR, 2024). Loreto, Madre de Dios, Amazonas, and Ucayali were identified as the regions with the highest levels of unauthorized timber extraction.

Figure 2. Four environmental defender deaths related to illegal logging. Sources: IBC, MINJUS, DEVIDA, SERNANP, ACCA.

In 2014, illegal loggers murdered four men from the community of Alto Tamaya-Saweto, in one of the most well-known murder cases of Peruvian environmental defenders. These defenders (Edwin Chota Valera, Francisco Pinedo Ramírez, Jorge Ríos Pérez, and Leoncio Quintisima Meléndez) were killed along the Peru-Brazil border (see orange dots in Figure 2), following a decade of complaints from Chota about the presence of criminal logging groups in their community. Ten years later, in April 2024, a group of loggers were found guilty of the murders and sentenced to nearly 30 years in prison. This case has since been appealed with the expectation of going to Peru’s supreme court.

Murders related to Illicit Crops (Coca)

Official data indicates that the surface area of coca production in Peru continues to increase, particularly in the central Peruvian Amazon along the Andes Mountains (in the regions of Ucayali and Huánuco). Since 2010, ten environmental defenders have been killed in this area related to their fight against coca-related activities (see red dots in Figure 3).

Figure 3. Ten cases of environmental defender deaths related to illegal coca production. Sources: IBC, MINJUS, DEVIDA, SERNANP, Conservación Amazónica-ACCA.

Three environmental defenders (Santiago Vega Chota, Yenes Ríos Bonsano, and Herasmo García Grau) were killed in 2020 and 2021 within or near their communities of Sinchi Roca and Puerto Nuevo in the region of Ucayali, following their attempts to monitor their communities’ territories for coca production. Both communities are located within a coca production zone known as Aguaytía, which experienced a 158% increase in coca cultivation between 2018 and 2022 (DEVIDA 2022).

Between 2010 and 2020, four environmental defenders (Segundo José Reategui, Manuel Tapullima, Justo Gonzales Sangama, and Arbildo Melendez) were murdered in or near the Unipacuyacu Indigenous community. These four deaths have been linked to illegal coca production by outsiders on community lands that have not yet been officially titled by the government, which has facilitated these invasions. Unipacuyacu is located within the Pichis-Palcazu-Pachitea coca production zone spanning the Huánuco and Pasco regions, where coca cultivation increased by more than 450% between 2018 and 2022 (DEVIDA 2022).

Finally, three other environmental defenders (Jesús Berti Antaihua Quispe, Gemerson Pizango Narvaes, and Nusat Parisada Benavides de la Cruz) were killed in 2022 in their communities of Santa Teresa and Cleyton. These two indigenous communities are located within and just outside of the in an area outside of the El Sira Communal Reserve buffer zone. During the four years leading up to their deaths, coca production in El Sira and its buffer zone increased by over 500% (DEVIDA 2022). While unconfirmed, it is believed that these murders were committed by mafias tied to drug trafficking and illegal mining.

Regulatory Basis

Peru ranks among the countries with the highest number of environmental defender deaths worldwide (Global Witness 2023).

Peru’s National Plan for Human Rights 2018-2021, defines an environmental defender as someone who: As an individual or collective, carries out a legitimate activity, paid or not, consisting of demanding and promoting, within the legally permitted framework, in a peaceful and nonviolent manner, the effectiveness of violated rights. Their efforts are usually manifested publicly through demands and raised through regular process channels, conforming with the framework devoted to these fundamental rights.

To address the vulnerability of environmental defenders, the Peruvian government, specifically the Ministry of Justice and Human Rights (MINJUSDH), has developed regulations to ensure their protection. The most important of these are:

Regulation Title Importance
 

Supreme Decree N 002-2018-JUS

  

National Plan for Human Rights 2018-2021

 Establishes that environmental defenders are a group of special protection and requests that the state adopts measures to protect them.
 

Supreme Decree 004-2021-JUS

  

Intersectoral Mechanism for the Protection of Human Rights Defenders

 Establishes the principles, measures, and proceedings to guarantee the prevention, protection, and access to justice for human rights defenders prior to risk situations, being the highest ranking standard in the country.
 

Ministerial Resolution 255-2020-JUS

  

Registry on Risk Situations for Human Rights Defenders

 

 Recognizes, analyzes, and manages information about the risks that human rights defenders face, and adopts actions to prevent threats.

 

Peru has also taken an intersectoral approach by coordinating participation among eight ministries: Ministry of Justice and Human Rights, Ministry of the Interior, Ministry of the Environment, Ministry of Culture, Ministry of Woman and Vulnerable Populations, Ministry of External Relations, Ministry of Energy and Mines, and Ministry of Agriculture and Irrigation Development. A public implementing agency, the National Commission for Development and Life Without Drugs (DEVIDA), also cooperates with this effort.

Despite these efforts, defenders continue to face criminalization, legal harassment, and threats of violence and murder. This shows the urgent need to strengthen their protection and institutional support in Peru.

In response, the Peruvian Congress has recently enacted three new laws to further protect human rights defenders. These include (i) Bill 4686/2022-CR, a law that recognizes and protects defenders of environmental rights, and (ii) Bill 2069/2021-PE, a law for the protection and assistance of communal and/or Indigenous or native leaders at risk. Moving forward, how the ongoing Alto Tamaya-Saweto case proceeds through Peru’s Supreme Court will be crucial to future efforts to protect environmental and human rights defenders.

References

Comisión Nacional Para El Desarrollo y Vida Sin Drogas (DEVIDA). 2023. Perú: Monitoreo de cultivos de coca 2022.

Global Witness 2023. Casi 2.000 personas defensoras de la tierra y el medioambiente asesinadas entre 2012 y 2022 por proteger el planeta.

Organismo de Supervisión de los Recursos Forestales y de Fauna Silvestre (OSINFOR). 2024. Estimación del índice y porcentaje de tala y comercio ilegal de madera en el Perú 2021.

Red Amazónica de Información Socioambiental Georreferenciada (RAISG). 2022. Presiones, amenazas y violencia en la Amazonía peruana.

Acknowledgments

This report was prepared with support from the Instituto de Bien Común (IBC).

Citation

Montoya M, Bonilla A, Novoa S, Tipula P, Salisbury D, Quispe M, Finer M, Folhadella A, Cohen M (2024) Killing of Environmental Defenders in the Peruvian Amazon. MAAP:218.

MAAP #215: Unprecedented Look at Carbon across the Amazon (part 1)

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Figure 1. Example of Planet Forest Carbon Diligence, focused on southern Peru and adjacent western Brazil.

The Amazon biome has long been one of the world’s largest carbon sinks, helping stabilize the global climate.

Precisely estimating this carbon, however, has been a challenge. Fortunately, new satellite-based technologies are providing major advances, most notably NASA’s GEDI mission (see MAAP #213) and, most recently, Planet Forest Carbon Diligence.1

Here, we focus on the latter, analyzing Planet’s cutting-edge new dataset, featuring a 10-year historical time series (2013 – 2022) with wall-to-wall estimates for aboveground carbon density at 30-meter resolution.

As a result, we can produce high-resolution aboveground carbon maps and estimates for anywhere and everywhere across the vast Amazon (see Figure 1).

Through a generous sharing agreement with Planet, we have been granted access to this data across the entire Amazon biome for the analysis presented in the following three-part series:

  1. Estimate and illustrate total aboveground forest carbon across the Amazon biome in unprecedented detail (see results of this first report, below).
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  2. Highlight which parts of the Amazon are home to the highest aboveground carbon levels, including protected areas and Indigenous territories (see second report, MAAP #217).
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  3. Present emblematic deforestation cases that have resulted in the highest aboveground carbon emissions across the Amazon (see third report, MAAP #220).

Major Results

Carbon across the Amazon

Based on our analysis of Planet Forest Carbon Diligence, we estimate that the Amazon contained 56.8 billion metric tons of aboveground carbon, as of 2022 (see Base Map). Applying a standard root-to-shoot ratio conversion (26%), this estimate increases to 71.5 billion metric tons of above and belowground carbon. This total is equivalent to nearly two years of global carbon dioxide emissions at the peak 2022 level (37.15 billion metric tons).5

The peak carbon levels are largely concentrated in the southwest Amazon (southern Peru and adjacent western Brazil) and northeast Amazon (northeast Brazil, French Guiana, and Suriname).

Base Map. Planet Forest Carbon Diligence across the Amazon biome.

Total Carbon by Country

As shown in Graph 1, countries with the most aboveground carbon are 1) Brazil (57%; 32.1 billion metric tons), 2) Peru (15%; 8.3 billion metric tons), 3) Colombia (7%; 4 billion metric tons), 4) Venezuela (6%; 3.3 billion metric tons), and 5) Bolivia (6%; 3.2 billion metric tons). These countries are followed by Guyana (3%; 2 billion metric tons), Suriname (3%; 1.6 billion metric tons), Ecuador (2%; 1.2 billion metric tons), and French Guiana (2%; 1.1 billion metric tons).

Overall, we documented the total gain of 64.7 million metric tons of aboveground carbon across the Amazon during the ten years between 2013 and 2022.2 In other words, the Amazon is still functioning as a critical carbon sink.

The countries with the most aboveground carbon gain over the past ten years are 1) Brazil, 2) Colombia, 3) Suriname, 4) Guyana, and 5) French Guiana. Note that we show Brazil as a carbon sink (gain of 102.8 million metric tons), despite other recent studies showing it as a carbon source.3 Also note the important gains in aboveground carbon across several key High Forest cover, Low Deforestation (HFLD) countries, namely Colombia, Suriname, Guyana, and French Guiana.4

In contrast, the countries with the most aboveground carbon loss over the past ten years are 1) Bolivia, 2) Venezuela, 3) Peru, and 4) Ecuador.

Graph 1. Planet Forest Carbon Diligence data across the Amazon biome, comparing 2013-14 with 2021-22. Note that a “+” symbol indicates that the country gained aboveground carbon, while a “-“ symbol indicates that the country lost aboveground carbon.

Carbon Density by Country

Standardizing for area, Graph 2 shows that countries with the highest aboveground carbon density (that is, aboveground carbon per hectare as of 2021-22) are located in the northeast Amazon: French Guiana (134 metric tons/hectare), Suriname (122 metric tons/hectare), and Guyana (85 metric tons/hectare). Ecuador is also high (94 metric tons/hectare).

Note that countries in the northeast Amazon (French Guiana, Suriname, and Guyana) have lower total aboveground carbon due to their smaller size (Graph 1), but high aboveground carbon density per hectare (Graph 2). This also applies to Ecuador.

Graph 2. Planet Forest Carbon Diligence data for aboveground carbon density by country across the Amazon, comparing 2013-14 with 2021-22. Note that a “+” symbol indicates that the country gained aboveground carbon, while a “-“ symbol indicates that the country lost aboveground carbon.

Notes & Citations

1 Anderson C (2024) Forest Carbon Diligence: Breaking Down The Validation And Intercomparison Report. https://www.planet.com/pulse/forest-carbon-diligence-breaking-down-the-validation-and-intercomparison-report/

2 In terms of uncertainty, the data contains pixel-level estimates, but not yet at national levels. To minimize annual uncertainty at the country level, we averaged 2013 and 2014 for the baseline and 2021 and 2022 for the current state.

3 Recently, in MAAP #144, we showed Brazil as a carbon source, based on data from 2001 to 2020. In contrast, Planet Forest Carbon Diligence is based on data from 2013 to 2022. Thus, one interpretation of the difference is that most carbon loss occurred in the first decade of the 2000s, which is consistent with historical deforestation data showing peaks in the early 2000s. It also highlights the likely importance of the interplay between forest loss/degradation (carbon loss) and forest regeneration (carbon gain) in terms of whether a country is a carbon source or sink during a given timeframe.

4 HFDL, or “High Forest cover, Low Deforestation” describes countries with both a) high forest cover (>50%) and low deforestation rates (<0.22% per year). For more information on HFDL, see https://www.conservation.org/blog/what-on-earth-is-hfld-hint-its-about-forests

5 Annual carbon dioxide (CO₂) emissions worldwide from 1940 to 2023

Citation

Finer M, Mamani N, Anderson C, Rosenthal A (2024) Unprecedented Look at Carbon across the Amazon. MAAP  #215.

 

MAAP #213: Estimating Carbon in Amazon Protected Areas & Indigenous Territories

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Intro Image. Screenshot of OBI-WAN forest carbon reporting app.

In a recent report (MAAP #199), we presented the updated version of NASA’s GEDI data,1 which uses lasers aboard the International Space Station to provide cutting-edge estimates of aboveground carbon globally, including our focal area, the Amazon.

These lasers, however, have not yet achieved full coverage, leaving considerable gaps in the data and resulting maps.

Here, we feature two new tools that allow us to fill in these gaps and provide detailed wall-to-wall estimates of aboveground biomass for specific areas, which can then be converted to aboveground carbon estimates.

The first is the OBI-WAN forest carbon reporting app (see Intro Image), which uses statistical inference to produce mean, total, and uncertainty estimates for biomass baselines at any given scale (from local to worldwide).2

The second is a fused product from GEDI and TanDEM-X missions.3 The combination of lidar (GEDI) and radar (TanDEM-X) has started to produce unmatched maps that combine the ability of lidar to retrieve forest structure and the ability of radar to offer wall-to-wall coverage at multiple resolutions (see Figures 1-5 below for examples at 25m resolution).

Employing these two tools, we focus on estimating aboveground carbon for select examples of two critical land designations in the Amazon: protected areas and indigenous territories. Both are critical to the long-term conservation of the core Amazon (MAAP #183). We hope that providing precise carbon data will provide additional incentives for their long-term conservation.

We select 5 focal areas (3 National Parks and 2 Indigenous Territories; see list below) across the Amazon to demonstrate the power of these datasets. Together, these five areas are currently home to over 1.4 billion metric tons of aboveground carbon.

  • Protected Areas (National Parks)
    Chirbiquete National Park (Colombian Amazon)
    Manu National Park (Peruvian Amazon)
    Madidi National Park (Bolivian Amazon)
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  • Indigenous Territories
    Kayapó Indigenous Territory (Brazilian Amazon)
    Barranco Chico Indigenous Territory (Peruvian Amazon)

Focal Areas

As noted above, the aboveground carbon estimates below are based on the aboveground biomass estimates from the OBI-WAN forest carbon reporting app and GEDI-TanDEM-X data. Figures 1 – 5 are based on GEDI-TanDEM-X, at 25 meter resolution.

National Parks

Chirbiquete National Park (Colombian Amazon)

Chirbiquete National Park covers over 4.2 million hectares in the heart of the Colombian Amazon (Guaviare and Caqueta departments). Both datasets converge in the estimate of around 600 metric tons of aboveground biomass, equating to over 300 million metric tons of aboveground carbon across the park (80.5 tons of carbon per hectare). Figure 1 shows the detailed spatial distribution of this biomass across Chirbiquete National Park. Note that the GEDI-TanDEM-X data misses the western tip of the park.

Figure 1. Aboveground biomass across Chiribiquete National Park (Colombian Amazon). Data: GEDI-TanDEM-X

 

Manu National Park (Peruvian Amazon)

Figure 2. Aboveground biomass across Manu National Park (Peruvian Amazon). Data: GEDI-TanDEM-X

Manu National Park covers over 1.7 million hectares in the southern Peruvian Amazon (Madre de Dios and Cusco regions).

Both datasets converge in the estimate of over 450 metric tons of aboveground biomass, equating to over 215 million metric tons of aboveground carbon across the territory (126.8 tons of carbon per hectare).

Figure 2 shows the detailed spatial distribution of this biomass across Manu National Park.

 

 

 

 

 

 

 

 

 

 

 

Madidi National Park (Bolivian Amazon)

Figure 3. Aboveground biomass across Madidi National Park (Bolivian Amazon). Data: GEDI-TanDEM-X

Madidi National Park and Integrated Management Area covers over 1.8 million hectares in the western Bolivian Amazon (La Paz department).

Both datasets converge in the estimate of over 350 metric tons of aboveground biomass, equating to over 160 million metric tons of aboveground carbon across the park (85.3 tons of carbon per hectare).

Figure 3 shows the detailed spatial distribution of this biomass across Madidi National Park. Note that the GEDI-TanDEM-X data misses the southern tip of the park.

 

 

 

 

 

 

 

 

 

 

Indigenous Territories

Kayapó Indigenous Territory (Brazilian Amazon)

Kayapó Indigenous Territory covers over 3.2 million hectares in the eastern Brazilian Amazon (Pará state). Both datasets converge in the estimate of over 413,000 metric tons of aboveground biomass, equating to over 198 million metric tons of aboveground carbon across the territory. Figure 4 shows the detailed spatial distribution of this biomass across Kayapó and four neighboring Indigenous Territories. Totaling across these five territories (10.4 million hectares), the data sets converge on over 1.5 billion metric tons of aboveground biomass, and 730 million metric tons of aboveground carbon (70 tons per hectare).

Figure 4. Aboveground biomass across Kayapó and neighboring Indigenous Territories (Brazilian Amazon). Data: GEDI-TanDEM-X

Barranco Chico Indigenous Territory (Peruvian Amazon)

Barranco Chico Indigenous Territory covers over 12,600 hectares in the southern Peruvian Amazon (Madre de Dios region). Both datasets converge in the estimate of over 2 million metric tons of aboveground biomass, equating to over 1 million metric tons of aboveground carbon. Figure 5 shows the detailed spatial distribution of this biomass across Barranco Chico and two neighboring Indigenous Territories (Puerto Luz and San Jose de Karene). Totaling across these three territories (nearly 90,000 hectares), the data sets converge on over 19 million metric tons of aboveground biomass, and over 9 million metric tons of aboveground carbon (102 tons per hectare).

Figure 5. Aboveground biomass across Barranco Chico and neighboring Indigenous Territories (Peruvian Amazon). Data: GEDI-TanDEM-X

Notes

1 GEDI L4B Gridded Aboveground Biomass Density, Version 2.1. This data is measured in megagrams of aboveground biomass per hectare (Mg/ha) at a 1-kilometer resolution, with the period of April 2019 – March 2023. This serves as our estimate for aboveground carbon reserves, with the science-based assumption that 48% of recorded biomass is carbon.

2 The approach relies on the foundational paper from Patterson et al., (2019) and it is used by the GEDI mission to estimate mean and total biomass worldwide (Dubayh et al., 2022, Armston et al., 2023). The method considers the spatial distribution of GEDI tracks within a given user-specify boundary to infer the sampling error component of the total uncertainty that also includes the error from the GEDI L4A models used to predict biomass from canopy height estimates (Keller et al., 2022). For more information on the OBI-WAN app, see Healey and Yang 2022.

3 GEDI-TanDEM-X (GTDX) is a fusion of GEDI Version 2 and TanDEM-X (TDX) Interferometric Synthetic Aperture Radar (InSAR) images (from Jan 2011 to December 2020). It also incorporates annual forest loss data to account for deforestation during this time. The GTDX aboveground biomass maps were produced based on a generalized hierarchical model-based (GHMB) framework that utilizes GEDI biomass as training data to establish models for estimating biomass based on the GTDX canopy height. The combination of lidar (GEDI) and radar (TanDEM-X) has started to produce unmatched maps that combine the ability of lidar to retrieve forest structure and the ability of radar to offer wall-to-wall coverage (Qi et al.,2023, Dubayah et a;., 2023). This fused product is a wall-to-wall gap-free map that was produced at multiple resolutions: 25m, 100m and 1ha. Ongoing processing over the Pantropic region will be made available over the next months but some geographies have been already mapped such as most of the Amazon Basin (Dubayah et al., 2023). The data we used is publicly available.

References

Armston, J., Dubayah, R. O., Healey, S. P., Yang, Z., Patterson, P. L., Saarela, S., Stahl, G., Duncanson, L., Kellner, J. R., Pascual, A., & Bruening, J. (2023). Global Ecosystem Dynamics Investigation (GEDI)GEDI L4B Country-level Summaries of Aboveground Biomass [CSV]. 0 MB. https://doi.org/10.3334/ORNLDAAC/2321

Dubayah, R. O., Armston, J., Healey, S. P., Yang, Z., Patterson, P. L., Saarela, S., Stahl, G., Duncanson, L., Kellner, J. R., Bruening, J., & Pascual, A. (2023). Global Ecosystem Dynamics Investigation (GEDI)GEDI L4B Gridded Aboveground Biomass Density, Version 2.1 [COG]. 0 MB. https://doi.org/10.3334/ORNLDAAC/2299

Dubayah, R., Armston, J., Healey, S. P., Bruening, J. M., Patterson, P. L., Kellner, J. R., Duncanson, L., Saarela, S., Ståhl, G., Yang, Z., Tang, H., Blair, J. B., Fatoyinbo, L., Goetz, S., Hancock, S., Hansen, M., Hofton, M., Hurtt, G., & Luthcke, S. (2022). GEDI launches a new era of biomass inference from space. Environmental Research Letters, 17(9), 095001. https://doi.org/10.1088/1748-9326/ac8694

Dubayah, R., Blair, J. B., Goetz, S., Fatoyinbo, L., Hansen, M., Healey, S., Hofton, M., Hurtt, G., Kellner, J., Luthcke, S., Armston, J., Tang, H., Duncanson, L., Hancock, S., Jantz, P., Marselis, S., Patterson, P. L., Qi, W., & Silva, C. (2020). The Global Ecosystem Dynamics Investigation: High-resolution laser ranging of the Earth’s forests and topography. Science of Remote Sensing, 1, 100002. https://doi.org/10.1016/j.srs.2020.100002

Healey S, Yang Z (2022) The OBIWAN App: Estimating Property-Level Carbon Storage Using NASA’s GEDI Lidar. https://www.fs.usda.gov/research/rmrs/understory/obiwan-app-estimating-property-level-carbon-storage-using-nasas-gedi-lidar

Kellner, J. R., Armston, J., & Duncanson, L. (2022). Algorithm Theoretical Basis Document for GEDI Footprint Aboveground Biomass Density. Earth and Space Science, 10(4), e2022EA002516. https://doi.org/10.1029/2022EA002516

Dubayah, R.O., W. Qi, J. Armston, T. Fatoyinbo, K. Papathanassiou, M. Pardini, A. Stovall, C. Choi, and V. Cazcarra-Bes. 2023. Pantropical Forest Height and Biomass from GEDI and TanDEM-X Data Fusion. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/2298

Qi, W., J. Armston, C. Choi, A. Stovall, S. Saarela, M. Pardini, L. Fatoyinbo, K. Papathanasiou, and R. Dubayah. 2023. Mapping large-scale pantropical forest canopy height by integrating GEDI lidar and TanDEM-X InSAR data. Research Square. https://doi.org/10.21203/rs.3.rs-3306982/v1

Krieger, G., M. Zink, M. Bachmann, B. Bräutigam, D. Schulze, M. Martone, P. Rizzoli, U. Steinbrecher, J. Walter Antony, F. De Zan, I. Hajnsek, K. Papathanassiou, F. Kugler, M. Rodriguez Cassola, M. Younis, S. Baumgartner, P. López-Dekker, P. Prats, and A. Moreira. 2013. TanDEM-X: A radar interferometer with two formation-flying satellites. Acta Astronautica 89:83–98. https://doi.org/10.1016/j.actaastro.2013.03.008

Acknowledgments

We greatly thank the University of Maryland’s GEDI team for data access and reviewing this report. In particular, we thank Ralph Dubayah, Matheus Nunes, and Sean Healey.

Citation

Mamani N, Pascual A, Finer M (2024) Estimating Carbon in Amazon Protected Areas & Indigenous Territories. MAAP: 213

MAAP #212: Machine learning to detect mining deforestation across the Amazon

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Amazon Mining Watch. Screen shot of the interactive mining deforestation map, displaying data for 2023.

Gold Mining is one of the major deforestation drivers across the Amazon.*

It often targets remote areas, thus impacting carbon-rich primary forests. Moreover, in most cases, this mining is illegal given that it is occurring in protected areas and indigenous territories.

Given the vastness of the Amazon, however, it has been a challenge to accurately monitor mining deforestation across the entire biome in a timely manner.

Here we present, for the first time, the results of a new machine learning based tool (known as Amazon Mining Watch)  that analyzes satellite imagery archives to detect mining deforestation across the entire Amazon.

Specifically, the tool produces 10-meter resolution mining deforestation alerts based on the European Space Agency’s Sentinel-2 satellite imagery. The alerts currently cover each year annually from 2018 to 2023.

This data reveals that gold mining is actively causing deforestation in all nine countries of the Amazon Biome (see Base Map below). The countries with the most overall mining deforestation are 1) Brazil, 2) Guyana, 3) Suriname, 4) Venezuela, and 5) Peru.

*Note that in this report we focus on mining activity that is causing deforestation. Additional critical gold mining areas in rivers (such as in northern Peru, southeast Colombia, and northwest Brazil; see MAAP #197), are not included in this report or detected/displayed in Amazon Mining Watch.

Major Findings

The Base Map below presents the mining deforestation data across the entire Amazon. Note that yellow indicates the historical mining footprint as of 2018, while red indicates the more recent mining deforestation between 2019 and 2023.

Although the alerts are pixels and not designed for precise area measurements, they can be used to give general estimates. For example, we estimate that as of 2018, there was a historical mining deforestation footprint of over 963,000 hectares across the entire Amazon. Between 2019 and 2023, we estimate that the mining deforestation footprint grew by over 944,000 hectares (2.3 million acres).

Thus, of the total accumulated mining deforestation footprint of over 1.9 million hectares (4.7 million acres), about half has occurred in just the past five years (see Annex).

Graph 1 shows, of the total accumulated mining, over half has occurred in Brazil (55%, covering over 1 million hectares), followed by Guyana (15%), Suriname (12%), Venezuela (7%), and Peru (7%, covering 135,625 hectares).

Base Map. Mining deforestation across the Amazon, based on data from Amazon Mining Watch, for the years 2018-2023. Data: AMW, ACA/MAAP.
Graph 1. Mining deforestation across the Amazon, by country. Data: AMW, ACA/MAAP.

Case Studies

In this section, we show a number of case studies highlighting the power of this data to see the evolution of mining deforestation in the following critical areas (see Insets A-E on Base Map). In these examples, note that yellow indicates the historical mining footprint as of 2018, purple indicates the expansion from 2019-2021, and red indicates the more recent mining deforestation between 2022 and 2023.

A. Southern Peruvian Amazon
B. Brazilian Amazon – Yanomami Indigenous Territory
C. Brazilian Amazon – Kayapó Indigenous Territory
D. Venezuelan Amazon – Yapacana National Park
E. Ecuadorian Amazon – Punino zone

A. Southern Peruvian Amazon

In southern Peru is one of the largest, and likely most emblematic, mining sites in the Amazon (see Inset A in Base Map). Figure 1 shows the dynamic evolution in this area, from several large core mining zones as of 2018, with more recent concentration in the designated Mining Corridor (large area where small-scale mining is permitted by the government as part of a formalization process).

Overall, we recorded over 135,000 hectares (333,590 acres) of mining deforestation in this area. Of this total, 62% (84,000 ha) was present as of 2018, while 38% (51,000 ha) has occurred in just the past five years (2019-2023).

We also highlight that of the total mining deforestation (135,000 ha), 59% has occurred within the Mining Corridor, while 41% (55,000 hectares) is outside the corridor and likely illegal. Note how mining deforestation threatens several protected areas, especially Tambopata National Reserve and Amarakaeri Communal Reserve.

See MAAP #208 for more information about mining deforestation at this site, and how illegal mining also threatens Native Communities.

Figure 1. Evolution of mining deforestation in the southern Peruvian Amazon. Data: AMW, ACA/MAAP.

B. Brazilian Amazon – Yanomami Indigenous Territory

In the northern Brazilian Amazon, the national government recently launched a series of raids against illegal gold mining in Yanomami Indigenous Territory (see Inset B in Base Map). Figure 2 shows a major escalation and expansion of gold mining deforestation since 2018, especially along the Uraricoera and Mucajai Rivers.

Specifically, we documented the total mining deforestation of over 19,000 hectares (47,000 acres) in Yanomami Indigenous Territory. It is critical to emphasize that the vast majority (93%) has occurred in just the past five years (2019-2023).

See MAAP #181 for more information about mining deforestation at this site.

Figure 2. Evolution of mining deforestation in Yanomami Indigenous Territory in Brazil. Data: AMW, ACA/MAAP.

C. Brazilian Amazon – Kayapó Indigenous Territory

In the eastern Brazilian Amazon, the Kayapó Indigenous Territory is also facing ongoing illegal mining (see Inset C in Base Map). Figure 3 shows the continuing expansion of mining deforestation, mostly in the eastern section of the territory.

We documented the total mining deforestation of nearly 50,000 hectares (123,550 acres) in Kayapó Indigenous Territory. Of this total, 60% (30,000 has) has occurred in just the past five years (2019-2023).

See MAAP #116 for more information about mining deforestation at this site, along with nearby Munduruku Indigenous Territory.

Figure 3. Evolution of mining deforestation in Kayapo Indigenous Territory in Brazil. Data: AMW, ACA/MAAP.

D. Venezuelan Amazon – Yapacana National Park

In Venezuela, we see the continued expansion of mining deforestation in Yapacana National Park (see Inset D in Base Map). Indeed, Figure 4 shows the steady expansion of gold mining deforestation at several sites in the southern section of the protected area.

We documented the total mining deforestation of over 6,000 hectares (14,800 acres) in Yapacana National Park. Of this total, just over half (52%; 3,000 has) has occurred in just the past five years (2019-2023).

See MAAP #173 and MAAP #207 for more information about mining deforestation at this site.

Figure 4. Evolution of mining deforestation in Yapacana National Park in Venezuela. Data: AMW, ACA/MAAP.

E. Ecuadorian Amazon – Punino River

In a series of reports, we have been showing the rapid increase in mining deforestation in the Ecuadorian Amazon (see MAAP #182). One of the main sites is around the Punino River in northern Ecuador (see Inset E in Base Map). Figure 5 shows the sudden emergence of gold mining deforestation near the river.

We documented the total mining deforestation of over 500 hectares (1,235 acres) in the Punino River area. Of this total, 100% is new, all starting in 2023.

See MAAP #206 for more information about mining deforestation at this site.

Figure 5. Evolution of mining deforestation in along the Punino River in Ecuador. Data: AMW, ACA/MAAP.

Annex

As noted above, of the total accumulated mining deforestation footprint of over 1.9 million hectares (4.7 million acres), about half has occurred in just the past five years.

Methods

All data for this report were obtained from Amazon Mining Watch. We only utilized patches with greater than 0.6 mean score. We used the 2018 data as our baseline. For 2019, we masked the previously reported 2018 data to only highlight the new mining that year. We then repeated this process for each subsequent year. For example, the 2023 data masked the 2018-2022 data, indicating only new mining deforestation that year.

Citation

Finer M, Ariñez A (2024) Machine learning to detect mining deforestation across the Amazon. MAAP: #212.

MAAP #196: Mining Impacts Calculator: Analysis in 3 Indigenous Communities of the Southern Peruvian Amazon

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Website of the Gold Mining Impact Calculator developed by CSF.

Illegal gold mining has generated massive deforestation in the southern Peruvian Amazon (MAAP #208). This activity also affects several of the main rivers (such as the Madre de Dios, Inambari, Tambopata, Malinowski and Colorado), and also their tributaries and secondary bodies of water. All of them are contaminated by excess sediment and the presence of toxic substances such as mercury and arsenic, which are dumped during the mineral extraction process.

Thus, illegal mining activity generates large economic losses due to the direct impact on ecosystem services and other more sustainable economic activities.

Quantifying these impacts in monetary terms has been a challenge for national authorities lacking adequate instruments capable of establishing economic values of the impact generated by illegal mining activity in the Amazon. In this context, in 2021 the Mining Impacts Calculator was presented, a digital economic valuation tool developed by the organization Conservation Strategy Fund (CSF). This tool allows users to calculate the social and environmental impact of illegal gold mining in the Amazon1, in order to improve decision-making, and establish changes and/or improvements in the regulatory framework around this activity.

This report shows the results of the application of the Calculator in recent (2022 and 2023) illegal mining areas within 3 native communities, all located in the buffer zone of the Amarakaeri Communal Reserve in southern Peru. This is an effort to show from a comprehensive perspective (economic and environmental) the implications of deforestation due to illegal mining in the Peruvian Amazon.

The economic calculations of the socio-environmental impacts were carried out using the Gold Mining Impact Calculator. The results show that from the beginning of 2022 to August 2023, there was a total economic loss amounting to 593 million dollars ($593,786,943) for the socio-environmental impacts, generated by deforestation, sedimentation and contamination of rivers by mercury in three indigenous communities of Madre de Dios. The details about the data that was entered into this tool to obtain the results mentioned in the report are explained in the methodology section.

Base Map

The Base Map shows the location of the case studies of this report, which is focused on quantifying the impact of illegal mining, through economic valuation, in 3 native communities in the buffer zone of the Amarakaeri Communal Reserve: San José de Karene, Puerto Luz, and Barranco Chico, all located in the province of Manu, department of Madre de Dios. Additionally, on the map, you can see historical, recent, and current deforestation.

Base Map. Location of the 3 native communities of the Amarakaeri Communal Reserve that are part of the study. Data: ACA/ACCA.

Impact in the San José de Karene Native Community

The native community of San José de Karene has lost 914 hectares from 2022 to August 2023 (See Map 2). In 2022, they lost 312 hectares and so far in 2023, until the month of August, 602 new hectares have been lost. It should be noted that the community currently has mining rights that overlap with its communal territory. When applying the Gold Mining Impact Calculator, it can be seen that the total socio-environmental impacts for 2022 were 86 million dollars ($86,258,492). On the other hand, so far in 2023, this figure increased significantly, reaching 166 million dollars ($166,657,897), as can be seen in Figure 1.

Map 2. Location of areas deforested by illegal mining in the San José de Karene native community (for 2022 and 2023, until August). Data: ACA.
Figure 1. Results of the Gold Mining Impact Calculator in the San José de Karene native community for the year 2022 and 2023 (until August). Source: Screenshot of the Gold Mining Impact Calculator.

Impact in the Puerto Luz Native Community

The native community of Puerto Luz has lost 270.6 hectares between 2022 and August 2023 (See Map 3). In 2022, they lost 100 hectares and so far from 2023 until the month of August they have lost 170.6 new hectares. The community currently has mining rights that overlap with its communal territory. Applying the tool, it is estimated that the total socio-environmental impacts for 2022 were 24 million dollars ($24,947,385), while so far in 2023 it was 44 million dollars ($44,205,548).

Map 3. Location of areas deforested by illegal mining in the Puerto Luz native community (for 2022 and 2023, until August). Data: ACA.

Figure 2. Results of the Calculator at the Puerto Luz native community for the year 2022 and the year 2023 (until August). Source: Screenshot of the Gold Mining Impact Calculator.

Impact in the Barranco Chico Native Community

The native community of Barranco Chico has lost 1093.3 hectares from 2022 to August 2023 (See Map 4). In 2022, they lost 277.3 hectares and so far from 2023 until the month of August they have lost 816 new hectares. The community currently has mining rights that overlap with its communal territory. Applying the Gold Mining Impact Calculator, it is observed that the total socio-environmental impacts for 2022 were 75 million dollars ($75,347,270), while so far in 2023 (August) it was 196 million dollars ( $196,370,351).

Map 4. Location of areas deforested by illegal mining in the native community Barranco Chico, Data: ACA.
Figure 3. Results of the Calculator for the Barranco Chico native community for the year 2022 and the year 2023 (until August). Source: Screenshot of the Gold Mining Impact Calculator.

Metodology

See the Spanish version of this report for full methodology and notes. The inputs to the calculator were as follows:

Acknowledgments

This report was prepared with the technical support of USAID through the Prevent Project. Prevent (Proyecto Prevenir in Spanish) works with the Government of Peru, civil society, and the private sector to prevent and combat environmental crimes for the conservation of the Peruvian Amazon, particularly in the regions of Loreto, Madre de Dios, and Ucayali.

Disclaimer: This publication is made possible by the generous support of the American people through USAID. The contents are the sole responsibility of the authors and do not necessarily reflect the views of USAID or the United States Government.

The CSF Gold Mining Impact Calculator is a tool based on scientific evidence. While CSF provides peer-validated information, it is not responsible for the consequences of using the calculator.

Citation

Mamani N, Huamán B, Novoa S, Morillo A, Torres M, Silva C, Finer M (2024) Gold Mining Impact Calculator: Analysis in 3 Indigenous Communities of the Southern Peruvian Amazon. MAAP: 196.

MAAP #208: Gold mining in the southern Peruvian Amazon, summary 2021-2024

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Figure 1. Recent expansion of illegal gold mining in the southern Peruvian Amazon. Data: Planet, NICFI

With the technical support of USAID (United States Agency for International Development) and Norad (Norwegian Agency for Development Cooperation),1 we have published a series of reports on the dynamic situation regarding gold mining in the southern Peruvian Amazon during recent years 2.

Illegal gold mining reached crisis levels between 2017 and 2018 in the area known as La Pampa (Madre de Dios region), eliminating thousands of hectares of primary forest in the buffer zone of the Tambopata National Reserve.

In early 2019, the Peruvian government implemented Operation Mercury, a multi-sectoral intervention against illegal mining, initially focusing on La Pampa. This operation was later replaced (in 2021) by the Restoration Plan, which included interventions in other critical mining areas of the Madre de Dios region in the southern Peruvian Amazon.

In this report, we offer a concise summary of the mining situation during the past three years (between January 2021 and March 2024) in the southern Peruvian Amazon, in the context of the Restoration Plan.

During this period, we recorded a total mining deforestation of 30,846 hectares (76,222 acres), equivalent to over 40,000 soccer fields.8

Of this total, three-quarters (74%) of the deforestation occurred within the official Mining Corridor, a large area (almost half a million hectares) where the government permits artisanal and small-scale mining to organize and promote this activity3. In other words, the vast majority of mining deforestation is not necessarily illegal, because it is in the corridor designated for this activity.

The remaining one-quarter (26%) of the deforestation corresponds to probable illegal mining. That is, mining activities carried out in prohibited areas outside the Mining Corridor, such as protected areas, their buffer zones, territories of Native Communities, and bodies of water.4

Base Map: Mining deforestation in the southern Peruvian Amazon

We highlight several important findings illustrated in the Base Map and Table 1, both presented below. In both cases, we highlight recent mining deforestation (between January 2021 and March 2024). Red indicates deforested areas outside of the Mining Corridor (representing our estimate of illegal mining), while yellow indicates recently deforested areas within the Mining Corridor.

Base Map. Mining deforestation inside and outside the Madre de Dios Mining Corridor, in the southern Peruvian Amazon, between January 2021 and March 2024. Data: ACCA/MAAP.

We found that mining deforestation is concentrated within the Mining Corridor, representing 73.8% of the total (22,756 hectares). This is especially evident in the Guacamayo mining area and along the Madre Dios River.

The rest of the mining deforestation (26.2%) is outside the Mining Corridor. The majority of this deforestation (14.6%) is occurring in the 10 Native Communities of the area, covering a total of 4,494 hectares. The most affected communities are San José de Karene (1,099 ha), Barranco Chico (1,008 ha) and Tres Islas (827 ha), followed by Puerto Luz (305 ha), Boca Inambari (305 ha), Kotsimba (297 ha), San Jacinto (269 ha), Shiringayoc (267 ha), Arazaire (78 ha) and El Pilar (40 ha). However, there are different trends. For example, mining deforestation between 2021 and 2024 has decreased in Barranco Chico, while it has increased in San José de Karene, Tres Islas and Boca Inambari.

We also identified mining deforestation of 2,439 hectares (7.9%) in buffer zones of Protected Areas. The most affected are Tambopata National Reserve (such as the Mangote area, see Figure 1), Bahuaja Sonene National Park, and Amarakaeri Communal Reserve. However, it must be emphasized that mining within the actual Protected Areas has been effectively controlled by the Peruvian government, through the National Service of Protected Natural Areas (SERNANP).

In addition, we detected some mining deforestation (198 hectares) in Brazil nut forestry concessions located in the Pariamanu area.

Finally, it is important to mention that in the critical area known as La Pampa (noted above), the expansion of mining deforestation has been effectively stopped after Operation Mercury. A recent report (MAAP #193), however, showed a large increase in mining activity in previously deforested areas of La Pampa.

Table 1. Mining deforestation by category in the southern Peruvian Amazon, between January 2021 and March 2024. Data: ACA/MAAP.

Monitoring & Control of Native Communities by FENAMAD

As noted above, a large portion of the illegal mining deforestation in the southern Peruvian Amazon is occurring within the territory of the Native Communities. These Native Communities are part of an articulated federation known as FENAMAD, which is the regional representative organization of the indigenous peoples of the Madre de Dios River basin. FENAMAD defends the fundamental and collective rights of indigenous peoples and native communities, including indigenous peoples in situations of isolation and initial contact.

1. First, FENAMAD identifies priority communities threatened by illegal mining and requiring urgent monitoring.

2. Subsequently, Amazon Conservation leads real-time satellite monitoring in these prioritized communities and delivers confidential reports to FENAMAD.

3. FENAMAD then reviews the reports together with the territory monitors and the results are shared with the affected native communities who decide whether these cases require a legal process.

4. FENAMAD formulates the Environmental Legal Complaint files and delivers them to the corresponding government institutions (Prosecutor’s Office Specialized in Environmental Matters of Madre de Dios –FEMA, National Police of Peru –PNP, Ecological Police of Peru, among others).

5. Finally, in selected cases, the government organizes and directs an on-the-ground operation against illegal mining activity and associated equipment.

This process has led to the execution of 5 government-led operations between 2022 and 2024, in three communities: Barranco Chico, Kotsimba and San José de Karene (see Base Map).

Of these operations, 3 took place in the community of Barranco Chico,5 which has been especially affected by illegal mining deforestation (967 hectares in the last three years). Figure 2 indicates the location of these operations. It should be noted that mining deforestation in Barranco Chico has decreased between 2021 and 2024, likely due to these types of interventions.

Figure 2. Location of operations against illegal mining in the Barranco Chico Native Community.

The other operations occurred in the communities of Kotsimba6 and San José de Karene7.

It is worth noting that this collaboration between FENAMAD and Amazon Conservation, which is supported by the Norwegian Agency for Development Cooperation (NORAD), is currently expanding to additional native communities within the impacted region.

Notes

1 USAID Prevent works with the Government of Peru, civil society and the private sector to prevent and combat environmental crimes for the conservation of the Peruvian Amazon, particularly in the regions of Loreto, Madre de Dios and Ucayali. USAID’s Prevent Project also has support from the Norwegian Agency for Development Cooperation (NORAD).

2 Previous MAAP reports about gold mining in the southern Peruvian Amazon:

MAAP #195: GOLD MINING DEFORESTATION IN THE SOUTHERN PERUVIAN AMAZON, 2021-2023

MAAP #195: Gold Mining Deforestation in the Southern Peruvian Amazon, 2021-2023

November 2023

MAAP #185: GOLD MINING DEFORESTATION IN THE SOUTHERN PERUVIAN AMAZON: 2021-2022 UPDATE

MAAP #185: Gold Mining Deforestation in the Southern Peruvian Amazon: 2021-2022 Update

June 2023

MAAP #171: DEFORESTATION IN MINING CORRIDOR OF PERUVIAN AMAZON (2021-2022)

MAAP #171: Deforestation in Mining Corridor of Peruvian Amazon (2021-2022)

December 2022

MAAP #154: ILLEGAL GOLD MINING IN THE PERUVIAN AMAZON – 2022 UPDATE

MAAP #154: Illegal Gold Mining in the Peruvian Amazon – 2022 update

May 2022

3 The Mining Corridor, named by Legislative Decree No. 1100, as the “Zone of small mining and artisanal mining in the department of Madre Dios”, catalogs mining activities as:

– Formal: It is carried out with authorization for exploration and exploitation in a specific area, with conditions and operations regulated by the legal framework of the mining sector. It has approved environmental, administrative and operational permits.

– Informal: Artisanal and small-scale mining operates in permitted areas for mineral extraction and uses permitted machinery. Although it does not have authorization to carry out mining activity, it is in the formalization process in accordance with the provisions of Legislative Decree No. 1105, which establishes provisions for the formalization process of small-scale mining and artisanal mining activities. Therefore, it is considered an administrative infraction, but not a crime.

– Illegal: Exploration, extraction and exploitation of mineral resources in prohibited areas (such as Protected Areas and bodies of water) and using prohibited machinery, failing to comply with administrative, technical and environmental requirements established in Peruvian legislation. This is a crime stipulated in article 207-A of the Penal Code, which carries a custodial sentence.

4 Although keep in mind that there may be mining concessions within the Native Community territories.

5 FEMA operations in the Barranco Chico community occurred in April 2022 (América Televisión video), April 2023 (El Comercio) and June 2023. There was an initial operation before the project in 2021.

6 FEMA operation in the Kotsimba community occurred in October 2023.

7 FEMA operation in the community of San José de Karene occurred in April 2024.

8 Of this total (30,846 hectares), 28,292 hectares occurred during 2021-2023, while 2,554 hectares occurred in the first quarter of 2024.

9 Undesignated refers to areas without a formal designation and not included in any of the other categories.

Methodology

We used LandTrendR, a temporal segmentation algorithm that identifies changes in pixel values over time, to detect forest loss within the mining corridor between January 2021 and March 2024 using the Google Earth Engine platform. Importantly, this method was originally designed for moderate resolution Landsat imagery (30 meters)1, but we adapted it for higher spatial resolution (4.7 meters) NICFI-Planet monthly mosaics.2

In addition, we created a baseline for the period 2016 – 2020 to eliminate previously deforested areas (pre 2021), to account for rapid changes in the natural revegetation process.

Finally, we manually separated forest loss from mining vs other causes, to report specifically on direct mining-related impacts between 2021 and 2024. We used several resources to help this manual process, such as alerts with radar images (RAMI) from the SERVIR Amazonía program, historical data from the Amazon Scientific Innovation Center – CINCIA (from 1985 to 2021), and forest loss data from the Peruvian state (National Forest Conservation Program for Climate Change Mitigation) and the University of Maryland.

  1. Kennedy, R.E., Yang, Z., Gorelick, N., Braaten, J., Cavalcante, L., Cohen, W.B., Healey, S. (2018). Implementation of the LandTrendr Algorithm on Google Earth Engine. Remote Sensing. 10, 691.
  2. Erik Lindquist, FAO, 2021

Acknowledgments

We especially thank FENAMAD for this important strategic collaboration.

This report was prepared with the technical support of USAID through the Prevent Project. Prevent (Proyecto Prevenir in Spanish) works with the Government of Peru, civil society, and the private sector to prevent and combat environmental crimes for the conservation of the Peruvian Amazon, particularly in the regions of Loreto, Madre de Dios, and Ucayali. USAID’s Prevent Project also has support from the Norwegian Agency for Development Cooperation (NORAD).

This publication is made possible by the generous support of the American people through USAID. The contents are the sole responsibility of the authors and do not necessarily reflect the views of USAID or the United States Government.

Citation

Finer M, Mamani N (2024) Gold mining in the southern Peruvian Amazon, summary 2021-2024. MAAP: 208.

 

MAAP #125: Detecting Illegal Logging with Very High Resolution Satellites

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Very high resolution satellite image showing illegal logging in the southern Peruvian Amazon. Data: Maxar. Analysis: MAAP/ACCA.

Illegal logging in the Peruvian Amazon is mainly selective and, until now, difficult to detect through satellite information.

In this report, we present the enormous potential of very high resolution satellite imagery (<70 cm) to identify illegal logging.

The leading entities that offer this type of data are Planet (Skysat) and Maxar (Worldview).

We emphasize that this technique has the potential to detect the illegal activity in real time, when preventive action is still possible.

This is an important advance because when an intervention normally occurs, such as detaining a boat or truck with illegal timber, the damage is done.

Below, we show a specific case of using very high resolution satellite imagery to detect and confirm probable illegal logging in the southern Peruvian Amazon (Madre de Dios region).

 

 

 

 

Case: Turbina SAC

The Base Map below shows the intensity of probable illegal logging activity* in the Turbina SAC forestry concession, from 2016 to the present. Specifically, it shows the exact points of illegal logging events (felled trees) and logging camps, as identified through our analysis of very high-resolution satellite images. Note that this forestry concession is adjacent to the Los Amigos Conservation Concession, an important long-term (20 years) biodiversity conservation area.

Base Map. Illegal logging activities in the Turbina SAC forestry concession. The size of the points is for reference only. Data: MAAP/Amazon Conservation.

Very High Resolution Satellite Imagery

Below, we show a series of very high-resolution satellite images, courtesy of the innovative satellite companies Planet and Maxar.

The first image shows the identification of probable illegal logging between June 2019 (left panel) and August 2020 (right panel). The red circle indicates the exact area (canopy) of the illegally logged tree.

The identification of illegal logging between June 2019 (left panel) and August 2020 (right panel). Click to enlarge. Data: Maxar, Planet, MAAP.

The following image shows the identification of illegal logging in March 2020. The red circle indicates the exact area of the illegally logged trees.

Identification of illegal logging. Data: Maxar, MAAP.

The following image shows the identification of a logging camp in March 2o20. The red circle indicates the area of the camp.

Satellite image of an illegal logging camp. Data: Maxar, MAAP.

*Statement on Legality

We determined that this logging activity is illegal from a detailed analysis of official information from the Peruvian Government (specifically, the Peruvian Forestry Service, SERFOR, and forestry oversight agency, OSINFOR). This information indicates that, although the concession is in force (Vigente), its status is classified as Inactive (Inactiva). In addition, 2013 was the last year that this concession had an approved logging plan (Plan Operativo de Aprovechamiento, or POA), and it was for a different sector of the concession from the newly detected logging activity.

To confirm our assumption of illegal activity, we requested the technical opinion from the corresponding regional forestry and wildlife authority, however, as of the date of publication of this report, we have not yet received a response.

Thus, with the information we had at the time of publication, we concluded the logging was illegal as it was not conducted within a current management plan.

Methodology

We carried out the analysis in two main steps:

The first step was the visual interpretation and digitization of new logging events and associated logging camps within the Turbina forestry concession. This analysis was based on the evaluation of submetric images obtained from the satellite companies Planet and Maxar, for the period 2019-20. It is worth noting that for Planet, we had the new ability to “task” new images for a specific area, rather than waiting for an image to appear by other means. Logging in the Peruvian Amazon is usually highly selective for high-value species, thus its detection requires a comparative analysis of images (before and after), in such a way that the trees cut during the study period (2019-20 in this case) can be identified.

The second step focused on an analysis of the legality of the identified logging events. The locations of the logged trees and camps were cross-referenced with spatial information on the state and status of forestry concessions provided by the GeoSERFOR (SERFOR) portal, as well as the areas delimited in the annual operational plans of the concessions, verified by OSINFOR and distributed through the SISFOR portal (WMS). We considered both spatial and temporal aspects to the forestry concession data.

Citation

Novoa S, Villa L, Finer M (2020) Detecting Illegal Logging with Very High Resolution Satellites. MAAP: 125.

Acknowledgments

We thank A. Felix (USAID Prevent), M.E. Gutierrez (ACCA), and G. Palacios for their helpful comments on this report.

This report was conducted with technical assistance from USAID, via the Prevent project. Prevent is an initiative that, over the next 5 years, will work with the Government of Peru, civil society, and the private sector to prevent and combat environmental crimes in Loreto, Ucayali and Madre de Dios, in order to conserve the Peruvian Amazon.

This publication is made possible with the support of the American people through USAID. Its content is the sole responsibility of the authors and does not necessarily reflect the views of USAID or the US government.

MAAP #58: Link between Peru’s Flooding and Warm Coastal Waters

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In previous articles MAAP #56 and MAAP #57, we presented a series of striking satellite images of the recent deadly floods in northern Peru. Satellites provide additional types of data critical to better understanding events such as extreme flooding. Here, we present two more types of satellite data related to the flooding: ocean water temperature and precipitation.


Warming Coastal Waters

Image 58a. Data: NOAA

Satellite data from NOAA (the U.S. National Oceanic and Atmospheric Administration) clearly shows the warming of the northern Peruvian coastal waters immediately before and during the heavy rains and flooding (1, 2). Specifically, Image 58a shows the sudden warming in January, followed by intensifying warming in February and March (white inset box indicates primary flooding zone). Peruvian experts have referred to this phenomenon as “coastal El Niño”.

Heavy Rains

Image 58b. Data: Senamhi, GPM/NASA

Image 58b shows the resulting accumulated monthly precipitation totals (white inset box indicates primary flooding zone). In January, as expected, the dry northern coast had much lower precipitation than the Amazon region to the east. In February and March, however, the northern coast experienced abnormally intense rainfall, even more than many parts of the Amazon.

Floods linked to Climate Change?

Questions have emerged regarding the link between the deadly Peruvian floods and climate change (3). As seen in the images above, the sudden appearance of warm coastal waters coincides with intense rains in the primary flooding zone. Additional analysis is needed to better understand the link between the Peruvian floods and climate change, but such events are consistent with predictions related to heavy rains fueled by ocean warming due to climate change (3). Climate change could also increase the frequency or intensity of El Niño events (4).

References

  1. Villa, L. (27 de marzo 2017). Radar Sentinel-1: Evaluación Preliminar del Impacto del Niño Costero en Perú (Parte II). [Mensaje en un blog]. Recuperado de: http://luciovilla.blogspot.com/2017/03/radar-sentinel-1-evaluacion-preliminar_27.html
  2. Villa, L. (17 de marzo 2017). Radar Sentinel-1: Evaluación Preliminar del Impacto del Niño Costero en Perú (Parte I). [Mensaje en un blog]. Recuperado de: http://luciovilla.blogspot.com/2017/03/radar-sentinel-1-evaluacion-preliminar.html
  3. Berwyn B (2017) Peru’s Floods Follow Climate Change’s Deadly Extreme Weather Trend. Inside Climate News. Link: https://insideclimatenews.org/news/24032017/peru-floods-extreme-weather-climate-global-warming-el-nino
  4. Fraser B (2017) Coastal El Niño catches Peru by surprise. EcoAmericas March 2017.

Citation

Finer M, Novoa S, Gacke S (2017) Link between Peru’s Flooding and Warm Coastal Waters. MAAP: 58.