MAAP #153: Amazon Deforestation Hotspots 2021

Amazon Base Map. Deforestation hotspots across the Amazon in 2021 (as of September 18). Data: UMD/GLAD, ACA/MAAP.

We present a first look at the major 2021 Amazon deforestation hotspots.*

The Amazon Base Map illustrates several key findings:p

  • We estimate the loss of over 1.9 million hectares (4.8 million acres) of primary forest loss across the nine countries of the Amazon biome in 2021.
    k
  • This matches the previous two years, bringing the total deforestation to 6 million hectares (15 million acres) since 2019, roughly the size of the state of West Virginia.
    p
  • In 2021, most of the deforestation occurred in Brazil (70%), followed by Bolivia (14%), Peru (7%), and Colombia (6%).
    p
  • In Brazil, hotspots are concentrated along the major road networks. Many of these areas were also burned following the deforestation.
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  • In Bolivia, fires once again impacted several important ecosystems, including the Chiquitano dry forests.
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  • In Peru, deforestation continues to impact the central region, most notably from large-scale clearing for a new Mennonite colony.
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  • In Colombia, there continues to be an arc of deforestation impacting numerous protected areas and indigenous territories.

Below, we zoom in on the four countries with the highest deforestation (Brazil, Bolivia, Peru, and Colombia), with additional maps and analysis.

Brazil Base Map. Deforestation hotspots in Brazilian Amazon. Data: UMD/GLAD, ACA/MAAP.

Brazilian Amazon

The Brazil Base Map shows the notable concentration of deforestation hotspots along the major roads (especially roads 163, 230, 319, and 364) in the states of Acre, Amazonas, Pará, and Rondônia.

 

 

 

 

 

 

 

 

 

 

 

Bolivia Base Map. Deforestation hotspots in Bolivian Amazon. Data: UMD/GLAD, ACA/MAAP.

Bolivian Amazon

The Bolivia Base Map shows the concentration of hotspots due to major fires in the Chiquitano dry forest biome, largely located in the department of Santa Cruz in the southeast section of the Amazon.

 

 

 

 

 

 

 

 

 

 

 

Peru Base Map. Deforestation hotspots in the Peruvian Amazon. Data: UMD/GLAD, ACA/MAAP.

Peruvian Amazon

The Peru Base Map shows the concentration of deforestation in the central Amazon (Ucayali region).

We highlight the rapid deforestation (365 hectares) for a new Mennonite colony in 2021, near the town of Padre Marquez (see MAAP #149).

Also, note some additional hotspots in the south (Madre de Dios region), but these are largely from expanding agriculture instead of the historical driver of gold mining.

Indeed, gold mining deforestation has been greatly reduced due to government actions, but this illegal activity still threatens several key areas and indigenous territories (MAAP #130).

 

 

 

 

 

 

 

Colombia Base Map. Deforestation hotspots in northwest Colombian Amazon. Data: UMD/GLAD, ACA/MAAP.

Colombian Amazon

As described in previous reports (see MAAP #120), the Colombia Base Map shows there continues to be an “arc of deforestation” in the northwest Colombian Amazon (Caqueta, Meta, and Guaviare departments).

This arc impacts numerous Protected Areas (particularly Tinigua and Chiribiquete National Parks) and Indigenous Reserves (particularly Yari-Yaguara II and Nukak Maku).

 

 

 

 

 

 

 

 

 

*Notes and Methodology

The analysis was based on 10-meter resolution primary forest loss alerts (GLAD+) produced by the University of Maryland and also presented by Global Forest Watch. These alerts are derived from the Sentinel-2 satellite operated by the European Space Agency.

We emphasize that this data represents a preliminary estimate and more definitive annual data will come later in the year.

We also note that this data does include forest loss caused by natural forces and burned areas.

Our geographic range for the Amazon is a hybrid between both the biogeographic boundary (as defined by RAISG) and watershed boundary, designed for maximum inclusion.

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 the 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)
Everything else was left to the default setting.

For the Base Map, we used the following concentration percentages: Medium: 5-7%; High: 7-14%; Very High: >14%.

Acknowledgements

This work was supported by NORAD (Norwegian Agency for Development Cooperation) and ICFC (International Conservation Fund of Canada).

Citation

Finer M, Mamani N, Spore J (2022) Amazon Deforestation Hotspots 2021. MAAP: 153.

MAAP #149: Mennonite Colonies Continue Major Deforestation in Peruvian Amazon

Recent deforestation associated with the newest Mennonite colony “Padre Marquez”. Data: Planet

The Mennonites, a religious group often associated with agricultural activity, have become one of the major deforestation drivers in the Peruvian Amazon.

In October 2020, we reported the deforestation of over 3,400 hectares across three new colonies established.

Here, we show that in 2021 the Mennonites have established a fourth colony (over 400 hectares) and continued expansion of the first three colonies.

In total, we have now documented the deforestation of 3,968 hectares (9,805 acres) across four new colonies established in the Peruvian Amazon since 2017, making it the new leading cause of large-scale deforestation in Peru.

Moreover, there are strong indications that much of this deforestation is illegal (see MAAP #127).

Below, we present the following:

  • An updated Base Map showing the location of the four new Mennonite colonies in the Peruvian Amazon.
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  • A series of satellite images showing the most recent deforestation in the newest colony (referred to here as “Padre Marquez”).
Updated Base Map showing the location of the four major new Mennonite Colonies in the Peruvian Amazon. Data: MAAP.

Base Map

The Base Map shows the location of the four major Mennonite colonies in the Peruvian Amazon.

The newest colony is referred to here as “Padre Marquez,” named for a nearby town. Note that it is located about halfway between the other colonies (Tierra Blanca to the north and Masisea to the south.

Of the total deforestation (3,968 hectares):

  • 66% (2,628 ha) is in the Tierra Blanca colonies in Loreto;
  • 23% (918 ha) is in Masisea colony in Ucayali;
  • 11% (421) is in the new Padre Marquez colony along the Ucayali/Loreto border.
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  • 12% occurred in 2021 (495 ha). In addition to the establishment of Padre Marquez, we also detected expansion in the Tierra Blanca and Masisea colonies.

Deforestation 2021

The following image shows the large-scale deforestation of 366 hectares between January (left panel) and November (right panel) 2021 associated with the main section of the new Padre Marquez colony. The red arrows serve as reference points between the two panels. Click to enlarge.

Deforestation between January (left panel) and November 2021 (right panel), associated with the new Padre Marquez colony. Data: Planet, MAAP. Click to enlarge.

Satellite Images of Each Mennonite Colony

Tierra Blanca 1

The following image shows the deforestation of 2,200 hectares (5,436 acres) since 2017 in the Tierra Blanca 1 colony (Loreto region). In 2021, this deforestation mostly stopped (only 8 ha).

Tierra Blanca 2

The following image shows the additional deforestation of 428 hectares (1,058 acres) in the nearby Tierra Blanca s colony (Loreto region). In 2021, this deforestation also mostly stopped (15 ha).

Masisea

The following image shows the deforestation of 918 hectares (2,268 acres) in the Masisea colony (Ucayali region). In 2021, there was a major expansion to the east (with 47 ha of new deforestation).

Padre Marquez

The following image shows the deforestation of 421 hectares (1,040 acres) in the Padre Marquez colony (Ucayali region), all of which occured in 2021.

Very High-Resolution Images of Padre Marquez colony

Below, we present a series of very high resolution (0.5 meter) satellite images of the Padre Marquez colony, thanks to the company Planet and their Skysat fleet. The image allows enhanced visualization of some details of the deforested area, such as roads, buildings, and cleared land for likely agricultural activities. Click to enlarge.

 

Declaration from the Peruvian Ministry of Environment (MINAM):

La destrucción de cientos de hectáreas de bosques en Loreto y en Ucayali causada por las ocupaciones irregulares de colonias menonitas, ha sido priorizada por el MINAM a través de las siguientes acciones:

1. Denuncias penales por afectación de las formaciones boscosas, contra los dirigentes de las colonias menonitas.   Cuatro denuncias en Ucayali y una denuncia penal en Loreto.
2. Medidas cautelares, en el marco de las denuncias penales, para que la autoridad judicial disponga la suspensión de las acciones destructivas y predatorias del bosque.
3. Solicitudes a las entidades de control institucional para la supervisión sobre el ejercicio funcional de las autoridades regionales a cargo del otorgamiento de permisos que afectan el bosque.
4. Además, el MINAM ha venido ejecutando y coordinando diversas acciones con la finalidad que las entidades competentes investiguen, sancionen y paralicen las actividades irregulares de estas personas extranjeras que no solamente han ingresado sin las autorizaciones respectivas para ejecutar actividades económicas, sino que además están dañando ostensiblemente el patrimonio natural peruano.

Acknowledgements

We thank M.E. Gutierrez, E. Ortiz, S. Novoa, R. Catpo, D. Suarez and G. Palacios for helpful comments to earlier versions of this report.

This work was supported by the following major funders: Erol Foundation, Norwegian Agency for Development Cooperation (NORAD), and International Conservation Fund of Canada (ICFC).

Citation

Finer M, Mamani N, Spore J, Suarez D (2021)Mennonite Colonies Continue Major Deforestation in Peruvian Amazon. MAAP: 149.

MAAP #148: Carbon loss & protection in the Peruvian Amazon

Base Map. Data: MINAM/PNCB, Asner et al 2014. Forest loss data exaggerated for visual display.

Tropical forests store massive amounts of carbon. However, when these forests are cleared (and often subsequently burned), the stored carbon is released into the atmosphere, further driving global climate change.

The Amazon is the world’s largest tropical forest, with Peru forming the second-largest piece, directly to the west of Brazil (the largest).

The Peruvian Amazon is unique in having a high-resolution estimate of aboveground carbon dating back to 2013 (Asner et al 2014).

Here, we analyze this dataset in relation to recent deforestation data (see Base Map), seeking to identify the major carbon-related trends between 2013 and 2020.

Our key findings include:

  • We estimate the loss of over 100 million metric tons of carbon (101,498,000 MgC) in the Peruvian Amazon between 2013 and 2020, mostly due to deforestation from agriculture and mining. 
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  • In contrast, we estimate that protected areas and indigenous lands have safeguarded 3.2 billion metric tons of carbon (56% and 44%, respectively) in the Peruvian Amazon between 2013 and 2020.

The carbon loss noted above is equivalent to greenhouse gas emissions from nearly 80 million passenger vehicles driven for one year, or CO2 emissions from 92 coal-fired power plants in one year (EPA).

The carbon protection noted above is equivalent to greenhouse gas emissions from 2.5 billion passenger vehicles driven for one year, or CO2 emissions from nearly 3,000 coal-fired power plants in one year (EPA).

Reference Map. Location of zooms A-E.

Reference Map

Below, we present a series of zoom images of several key areas.

Zooms A-C highlight recent carbon loss due to deforestation (agriculture and mining) in high carbon density Amazon moist forests.

In contrast, Zooms D-E show how protected areas and indigenous lands are protecting massive amounts of carbon.

These letters (A-E) correspond to the reference map here.

Areas of Recent Carbon Loss

A. United Cacao

Zoom A shows the loss of nearly 300,000 metric tons of carbon for a large-scale cacao project (United Cacao) in the northern Peruvian Amazon (Loreto region).

Zoom A. United Cacao. Data: Asner et al 2014.

B. Mennonite Colony

Zoom B shows the recent deforestation and associated carbon loss for a new Mennonite colony in the central Peruvian Amazon (near the town of Tierra Blanca).

Zoom B. Mennonite Colony – Tierra Blanca. Data: MINAM/PNCB, Asner et al 2014.

C. Gold mining

Zoom C shows the loss of over 800,000 metric tons of carbon due to gold mining in the southern Peruvian Amazon (Madre de Dios region).

Zoom C. Gold mining in Madre de Dios region. Data: Asner et al 2014, MINAM/PNCB

Areas of Carbon Protection

D. Yaguas National Park

Zoom D shows how three protected areas, including the new Yaguas National Park, are effectively safeguarding over 200 million metric tons of carbon in the northeastern Peruvian Amazon.

Zoom D. Protected Areas in northeast Peru. Data: Asner et al 2014, MINAM/PNCB

E. Manu National Park

Zoom E shows how a group of protected areas (Manu National Park and Amarakaeri Communal Reserve) and the country’s first Conservation Concession (Los Amigos), is effectively safeguarding over 210 million metric tons of carbon in the southern Peruvian Amazon.

Zoom E. Protected Areas in southeast Peru. Data: Asner et al 2014, MINAM/PNCB

Methodology

This report combined two major datasets: 1) aboveground carbon from Asner et al 2014 and 2) annual forest loss identified by the Peruvian Environment Ministry’s National Forest Conservation Program (Geobosques) from the years 2013 to 2020.

The aboveground carbon data served as a baseline for 2013, and then we subsequently extracted the carbon data from the areas of forest loss from 2013-2020.

This process allowed us to obtain the carbon density (per hectare) in relation to the area of forest loss and then to estimate the total aboveground carbon stocks lost between 2013 and 2020.

The forest loss data values include some natural forest loss. Overall, however, they should be considered underestimates because they do not include forest degradation (for example, selective logging).

References

Asner GP et al (2014). The High-Resolution Carbon Geography of Perú. Carnegie Institution for Science.

EPA. Greenhouse Gas Equivalencies Calculator. https://www.epa.gov/energy/greenhouse-gas-equivalencies-calculator

Acknowledgements

We thank A. Folhadella, M. Hyde, ME Gutierrez, and G. Palacios for their helpful comments on this report.

This work was supported by NORAD (Norwegian Agency for Development Cooperation) and ICFC (International Conservation Fund of Canada).

Citation

Finer M, Mamani N (2021). Carbon loss & protection in the Peruvian Amazon. MAAP: 148.

 

 

MAAP #147: Amazon Deforestation Hotspots 2021 (1st Look)

Base Map. Deforestation hotspots across the Amazon in 2021 (as of September 18). Data: UMD/GLAD, ACA/MAAP.

We present a first look at the major deforestation hotspots across all nine countries of the Amazon in 2021 (as of September 18).*

The Base Map illustrates several key findings thus far in 2021:p

  • We estimate the loss of over 860,000 hectares (2.1 million acres) of primary forest loss across the nine countries of the Amazon.
    p
  • Amazon deforestation has been concentrated in three countries: Brazil (79%), Peru (7%), Colombia (6%).
    p
  • The vast majority of deforestation (79%) occurred in the Brazilian Amazon, where massive hotspots stretched across the major road networks. Many of these areas were also burned following the deforestation.
    p
  • There continues to be an arc of deforestation in the northwestern Colombian Amazon, impacting numerous protected areas and indigenous territories.
    p
  • In the Peruvian Amazon, deforestation continues to impact the central region, most notably from a new Mennonite colony and large-scale rice plantation.
    p
  • In Bolivia, fires are once again impacting several important ecosystems, including the Beni grasslands and Chiquitano dry forests of the Amazon, and Chaco scrub forest outside the Amazon.

Below, we zoom in on the three countries with the highest deforestation (Brazil, Colombia, and Peru) and show a series of high-resolution satellite images that illustrate some of the major 2021 deforestation events.

Widespread Deforestation in the Brazilian Amazon

The Brazil Base Map shows the notable concentration of deforestation hotspots along the major roads (especially roads 163, 230, 319, and 364). Zooms A-C show high-resolution examples of this deforestation, which largely appears to be associated with clearing rainforests for pasture.

Brazil Base Map. Deforestation hotspots in Brazilian Amazon (as of September 18). Data: UMD/GLAD, ACA/MAAP.
Zoom A. Deforestation in the Brazilian Amazon near road 230 (TransAmazian Highway) between February (left panel) and September (right panel) of 2021. Data: Planet.
Zoom B. Deforestation in the Brazilian Amazon along road 319 in Amazonas state between May (left panel) and September (right panel) of 2021. Data: Planet, ESA.
Zoom C. Deforestation in the Brazilian Amazon along road 163 between November 2020 (left panel) and September 2021 (right panel). Data: Planet, ESA.
Colombia Base Map. Deforestation hotspots in northwest Colombian Amazon (as of September 18). Data: UMD/GLAD, ACA/MAAP.

Arc of Deforestation in the Colombian Amazon

As described in previous reports (see MAAP #120), the Colombia Base Map shows there continues to be an “arc of deforestation” in the northwest Colombian Amazon (Caqueta, Meta, and Guaviare departments).

This arc impacts numerous protected areas (particularly Tinigua and Chiribiquete National Parks) and Indigenous Reserves (particularly Yari-Yaguara II and Nukak Maku).

Zooms D & E show high-resolution examples of this deforestation, which largely appears to be associated with clearing rainforests for pasture.

Zoom D. Deforestation in the Colombian Amazon (Caqueta) between December 2020 (left panel) and September 2021 (right panel). Data: Planet.
Zoom E. Deforestation in the Colombian Amazon between January (left panel) and September (right panel) of 2021. Data: Planet, ESA.
Peru Base Map. Deforestation hotspots in the Peruvian Amazon (as of September 18). Data: UMD/GLAD, ACA/MAAP.

Deforestation in the central Peruvian Amazon

The Peru Base Map shows the concentration of deforestation in the central Peruvian Amazon (Ucayali, Huanuco, and southern Loreto regions).

Zooms F & G show two notable examples of this deforestation: the rapid deforestation in 2021 for a new Mennonite colony (299 hectares) and large-scale rice plantation (382 hectares), respectively.

Also note some additional hotspots in the south (Madre de Dios region) from gold mining and medium-scale agriculture.

The hotspot in the north (Loreto region) is natural forest loss from a windstorm.

Zoom F. Deforestation (299 hectares) in the Peruvian Amazon for a new Mennonite colony between January (left panel) and September (right panel) of 2021 in southern Loreto region. Data: Planet.
Zoom G. Deforestation (382 ha) in the Peruvian Amazon for a new large-scale rice plantation between January (left panel) and September (right panel) of 2021 in Ucayali region. Data: Planet.

*Notes and Methodology

The analysis was based on 10-meter resolution primary forest loss alerts (GLAD+) produced by the University of Maryland and also presented by Global Forest Watch. These alerts are derived from the Sentinel-2 satellite operated by the European Space Agency.

We emphasize that this data represents a preliminary estimate and more definitive annual data will come later next year.

We also note that this data does include forest loss caused by natural forces and burned areas.

Our geographic range for the Amazon is a hybrid between both the biogeographic boundary (as defined by RAISG) and watershed  boundary, designed for maximum inclusion.

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)
Everything else was left to the default setting.

For the Base Map, we used the following concentration percentages: Medium: 7-10%; High: 11-20%; Very High: >20%.

Acknowledgements

We thank E. Ortiz and A. Ariñez for their helpful comments on this report.

This work was supported by NORAD (Norwegian Agency for Development Cooperation) and ICFC (International Conservation Fund of Canada).

Citation

Finer M, Mamani N, Spore J (2020) Amazon Deforestation Hotspots 2021. MAAP: 147.

Amazon Fire Tracker 2021: August update

Major fire burning recently deforested area in the Brazilian Amazon (#17, Mato Grosso). Data: MAAP, Planet.

Following the intense Amazon fire seasons of both 2019 and 2020, we are closely tracking 2021 with  our unique real-time Amazon fire monitoring app.*

We have documented 246 major fires across the Amazon thus far this year, as of August 1 (see Base Map below).

The vast majority have been in the Brazilian Amazon (75%), followed by Bolivia, Peru, and Colombia.

Our key findings include:

  • In the Brazilian Amazon, the majority (67%) of major fires have burned recently deforested areas. Thus, the critical pattern is Deforestation followed by Fire, as many major fires are actually burning the remains of freshly cut areas. These fires have burned over 44,000 hectares (109,000 acres), highlighting the current high deforestation in Brazil.
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  • We have also documented a number of major fires in the natural grasslands embedded in the eastern Brazilian Amazon. Most of these fires have occurred in Indigenous Territories, such as Xingu andKayapó.
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  • The Brazilian government issued a ban on unauthorized outdoor fires on June 27, thus we assume that most of the 160 major fires following that date have been illegal.
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  • In the Bolivian Amazon, we have detected 35 major fires, mostly in the departments of Beni and Santa Cruz. In Beni, these fires have impacted 19,000 hectares (48,000 acres) of natural savanna ecosystems.
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  • In the Peruvian Amazon, most of the major fires have been in the higher elevation grasslands, impacting over 2,600 hectares (6,500 acres) in the upper reaches of the watershed.
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  • In the Colombian Amazon, we detected several major fires during that region’s peak season of February-March.

Below, we present our updated major Amazon fires Base Map, along with more detailed information for the Brazilian Amazon.

*In a new and unique approach, the app combines data from both the atmosphere (aerosol emissions in smoke) and the ground (heat anomaly alerts) to quickly and precisely detect major Amazon fires (see App Background below).

Base Map: Major Amazon Fires 2021

The Base Map shows the location of this year’s major fires (orange dots), as visualized in the app’s “Major Amazon Fires 2021” layer. Of the 209 major fires in the Amazon this year, the vast majority have been in Brazil (75%), followed by Bolivia (14%), Peru (9%), and Colombia (2%).

Base Map. “Major Amazon Fires 2021” layer, as visualized in the app. Data: MAAP, Amazon Conservation.

 

Fires in the Brazilian Amazon

Major fire burning recently deforested area in the Brazilian Amazon. Data: MAAP, Planet.

In the Brazilian Amazon, we have documented 184 major fires thus far in 2021.

This marks an increase from the start of the intense 2020 fire season, when we had detected 87 major fires by this same date (we ultimately documented over 2,250 major fires by the end of the year).

As noted above, the majority (67%) of major fires have burned recently deforested areas (that is, areas where the forest was previously cleared between 2017 and 2021 prior to burning). These fires have burned over 44,000 hectares (109,000 acres), highlighting the current high deforestation in Brazil.

Most of the remaining fires have occurred in either natural savannah grasslands (impacting 35,000 ha) or older croplands. Many of the grassland fires have occurred in Indigenous Territories, such as Xingu and Kayapó.

It is worth highlighting that we have also documented the first several “Forest Fires” of the season, defined here as human-caused fires in standing forest. The impact of these fires has been relatively small so far (400 hectares), but this number is expected to spike as the dry season intensifies in August and September.

The Brazilian government issued a ban on unauthorized outdoor fires on June 27, thus we assume that most of the 160 major fires following that date have been illegal.

The state of Mato Grosso has had the most major fires (43%), followed by Amazonas (29%), Pará (14%), Rondônia (12%), and Acre (2%).

*App Background

We launched a new and improved version of the Amazon real-time fire monitoring app in May 2021. The app is hosted by Google Earth Engine and updated every day by the organization Conservación Amazónica, based in Peru.

The app displays aerosol emissions as detected by the European Space Agency’s Sentinel-5 satellite. Elevated aerosol levels indicate the burning of large amounts of biomass, defined here as a “major fire”. In a novel approach, the app combines data from the atmosphere (aerosol emissions in smoke) and the ground (heat anomaly alerts) to effectively detect and visualize major Amazon fires.

When fires burn, they emit gases and aerosols. A new satellite (Sentinel-5P from the European Space Agency) detects these aerosol emissions (aerosol definition: Suspension of fine solid particles or liquid droplets in air or another gas). Thus, the major feature of the app is detecting elevated aerosol emissions which in turn indicate the burning of large amounts of biomass. For example, the app distinguishes small fires clearing old fields (and burning little biomass) from larger fires burning recently deforested areas or standing forest (and burning lots of biomass). The spatial resolution of the aerosol data is 7.5 sq km. The high values in the aerosol indices (AI) may also be due to other reasons such as emissions of volcanic ash or desert dust so it is important to cross reference elevated emissions with heat data and optical imagery.

We define “major fire” as one showing elevated aerosol emission levels on the app, thus indicating the burning of elevated levels of biomass. This typically translates to an aerosol index of >1 (or cyan-green to red on the app). To identify the exact source of the elevated emissions, we reduce the intensity of aerosol data in order to see the underlying terrestrial heat-based fire alerts. Typically for major fires, there is a large cluster of alerts. The major fires are then confirmed, and burn areas estimated, using high-resolution satellite imagery from Planet Explorer.

We define burning “recently deforested areas” as any forested area cleared since 2017 and subsequently burned in 2021.

Since the data updates daily and is not impacted by clouds, real-time monitoring really is possible. Our goal is to upload each day’s new image in the late afternoon/early evening.

Acknowledgements

The app was developed and updated daily by Conservación Amazónica (ACCA). The data analysis is led by Amazon Conservation in collaboration with SERVIR Amazonia.

The Amazon Fire Tracker series is supported by NORAD (Norwegian Agency for Development Cooperation) and ICFC (International Conservation Fund of Canada).

Citation

Finer M, Costa H, Villa L (2021) Amazon Fire Tracker 2021: August Update. MAAP 2021, #3.

MAAP #141: Protected Areas & Indigenous Territories Effective Against Deforestation in the Western Amazon

Base Map. Primary forest loss across the western Amazon, with magnified visualization of the data. Click to enlarge. See Methodology for data sources.

As deforestation continues to threaten primary forest across the Amazon, key land use designations are one of the best hopes for the long-term conservation of critical remaining intact forests.

Here, we evaluate the impact of two of the most important land use designations: protected areas and indigenous territories.

Our study area focused on the four mega-diverse countries of the western Amazon (Bolivia, Colombia, Ecuador, & Peru), covering a vast area of over 229 million hectares (see Base Map).

We calculated primary forest loss over the past four years (2017-2020) across the western Amazon and analyzed the results across three major land use categories:

1) Protected Areas (national and state/department levels), which covered 43 million hectares as of 2020.

2) Indigenous Territories (official), which covered over 58 million hectares as of 2020.

3) Other (that is, all remaining areas outside protected areas and indigenous territories), which covered the remaining 127 million hectares as of 2020.

In addition, we took a deeper look at the Peruvian Amazon and also included long-term forestry lands.

In summary, we found that, averaged across all four years, protected areas had the lowest primary forest loss rate, closely followed by indigenous territories (see Figure 1). Outside of these critical areas, the primary forest loss rate was more than double.

Below, we describe the key results in greater detail, including a detailed look at each country.

 

Key Findings – Western Amazon

Figure 1. Primary forest loss rates in the western Amazon.

Overall, we documented the loss of over 2 million hectares of primary forests across the four countries of the western Amazon between 2017 and 2020. Of the four years, 2020 had the most forest loss (588,191 ha).

Of this total, 9% occurred in protected areas (179,000 ha) and 15% occurred in indigenous territories (320,000 ha), while the vast majority (76%) occurred outside key these land use designations (1.6 million ha).

To standardize these results for the varying area coverages, we calculated primary forest loss rates (loss/total area of each category). Figure 1 displays the combined results for these rates across all four countries.

From 2017-19, protected areas (green) had the lowest primary forest loss rates across the western Amazon (less than 0.10%).

Indigenous territories (brown) also had low primary forest loss rates from 2017-18 (less than 0.11%), but this rose in 2019 (0.18%) due to fires in Bolivia.

In the intense COVID pandemic year of 2020, this overall pattern flipped, with elevated primary forest loss in protected areas, again largely due to major fires in Bolivia. Thus, indigenous territories had the lowest primary forest loss rate followed by protected areas (0.15% and 0.19%, respectively) in 2020.

Averaged across all four years, protected areas had the lowest primary forest loss rate (0.11%), closely followed by indigenous territories (0.14%). Outside of these critical areas (red), the primary forest loss rate was more than double (0.30%). The lowest primary forest loss rates (less than 0.10%) occurred in the protected areas of Ecuador and Peru (0.01% and 0.03%, respectively), and indigenous territories of Colombia (0.07%).

Country Results

Figure 2. Primary forest loss rates in the Colombian Amazon.

Colombian Amazon

Colombia had, by far, the highest primary forest loss rates outside protected areas and indigenous territories (averaging 0.67% across all four years).

By contrast, Colombian indigenous territories had one of the lowest primary forest loss rates across the western Amazon (averaging 0.07% across all four years).

The primary forest loss rates for protected areas were on average nearly double that of indigenous territories (mostly due to the high deforestation in Tinigua National Park), but still much lower than non-protected areas.

 

 

 

 

 

Figure 3. Primary forest loss rates in the Ecuadorian Amazon.

Ecuadorian Amazon

Overall, Ecuador had the lowest primary forest loss rates across all three categories.

Protected areas had the lowest primary forest loss rate of any category across the western Amazon (averaging 0.01% across all four years).

Indigenous territories also had relatively low primary forest loss rates, averaging half that of outside protected areas and indigenous territories (0.10% vs 0.21%, respectively).

 

 

 

 

 

 

Figure 4. Primary forest loss rates in the Bolivian Amazon.

Bolivian Amazon

Bolivia had the most dynamic results, largely due to intense fire seasons in 2019 and 2020. Indigenous territories had the lowest primary forest loss rates, with 2019 being the only exception, due to large fires in the Santa Cruz department that affected the Monte Verde indigenous territory.

Protected areas had the lowest primary forest loss rate in 2019, but in extreme contrast, the highest the following year in 2020, also due to large fires in the Santa Cruz department that affected Noel Kempff Mercado National Park.

Overall, primary forest loss was highest outside protected areas and indigenous territories (averaging 0.33% across all four years).

 

 

 

Figure 5a. Primary forest loss rates in the Peruvian Amazon. Data: UMD.

Peruvian Amazon

Following Ecuador, Peru also had relatively low primary forest loss rates, particularly in protected areas (averaging 0.03% across all four years).

Primary forest loss in indigenous territories (that is, combined data for native communities and Territorial/Indigenous Reserves for groups in voluntary isolation) was surprisingly high, similar to that of areas outside protected areas across all four years. For example, in 2020, elevated primary forest loss was concentrated in several titled native communities in the regions of Amazonas, Ucayali, Huánuco, and Junín.

 

 

 

 

 

Figure 5b. Deforestation rates in the Peruvian Amazon. Data: MINAM/Geobosques.

As noted above, we conducted a deeper analysis for the Peruvian Amazon, using deforestation data produced by the Peruvian government and adding the additional category of long-term forestry lands (known as Permanent Production Forests, or BPP in Spanish) (see Annex map).

We also separated the data for indigenous territories into native communities and Territorial/Indigenous Reserves for groups in voluntary isolation, respectively.

These data also show that deforestation was lowest in the remote Territorial/Indigenous Reserves, closely followed by protected areas (0.01% vs 0.02% across all four years, respectively). Deforestation in titled native communities was 0.21% across all four years. Surprisingly, deforestation was higher in the forestry lands than areas outside protected areas and indigenous territories (0.30% vs 0.27% across all four years).

 

 

 

 

Annex – Peruvian Amazon

The following map shows added detail for Peru, most notably the inclusion of long-term forestry lands (known as Permanent Production Forests, or BPP in Spanish).

 

 

 

 

 

 

 

 

 

 

 

 

*Methodology

To estimate deforestation across all three categories, we used annual forest loss data (2017-20) from the University of Maryland (Global Land Analysis and Discovery GLAD laboratory) to have a consistent source across all four countries (Hansen et al 2013).

We obtained this data, which has a 30-meter spatial resolution, from the “Global Forest Change 2000–2020” data download page. It is also possible to visualize and interact with the data on the main Global Forest Change portal.

It is important to note that these data include both human-caused deforestation and forest loss caused by natural forces (landslides, wind storms, etc…).

We also filtered this data for only primary forest loss, following the established methodology of Global Forest Watch. Primary forest is generally defined as intact forest that has not been previously cleared (as opposed to previously cleared secondary forest, for example). We applied this filter by intersecting 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).

Thus, we often use the term “primary forest loss” to describe the data.

Data presented as primary forest loss or deforestation rate is standardized per the total area covered of each respective category. For example, to properly compare raw forest loss data in areas that are 100 hectares vs 1,000 hectares total size respectively, we divide by the area to standardize the result.

Our geographic range included four countries of the western Amazon and consists of a combination of the Amazon watershed limit (most notably in Bolivia) and Amazon biogeographic limit (most notably in Colombia) as defined by RAISG. See Base Map above for delineation of this hybrid Amazon limit, designed for maximum inclusion.

Additional data sources include: National and state/deprartment level protected areas: RUNAP 2020 (Colombia), SNAP 2017 & RAISG 2020 (Ecuador), SERNAP & ACEAA 2020 (Bolivia), and SERNANP 2020 (Peru).

Indigenous Territories: RAISG 2020 (Colombia, Ecuador, and Bolivia), and MINCU & ACCA 2020 (Peru). For Peru, this includes titled native communities and Indigenous/Territorial Reserves for indigenous groups in voluntary isolation.

For the additional analysis in Peru, we used deforestation data from MINAM/Geobosques (note this is actual deforestation and not primary forest loss) and BPP data from SERFOR. We also separated data from titled native communities and Territorial/Indigenous Reserves for groups in voluntary isolation.

Acknowledgements

We thank M. MacDowell (AAF) A. Folhadella (ACA), J. Beavers (ACA), S. Novoa (ACCA), and D. Larrea (ACEAA) for their helpful comments on this report.

This work was supported by the Andes Amazon Fund (AAF), Norwegian Agency for Development Cooperation (NORAD), and International Conservation Fund of Canada (ICFC).

 

Citation

Finer M, Mamani N, Silman M (2021) Protected Areas & Indigenous Territories Effective Against Deforestation in the Western Amazon. MAAP: 141.

MAAP #140: Detecting illegal gold mining in rivers with specialized satellites

Image: Skysat (Planet). Analysis: MAAP/Amazon Conservation.

Illegal gold mining is a widespread problem in the southern Peruvian Amazon (Madre de Dios region), where it has caused river contamination and the deforestation of more than 100,000 hectares.

This activity has also emerged in the northern Peruvian Amazon (Loreto region), where it is not yet causing deforestation and the main threat is the contamination of rivers and important water resources.

This type of gold mining activity in water bodies (such as rivers) is illegal in Peru (see the “Legal situation” section below).

Identifying this type of mining (that is, in rivers and not causing deforestation) is difficult because the small mining boats (known as dragas) are mobile and imperceptible to medium and high-resolution satellites.

In this report, we test a novel technique based on tasking very high-resolution specialized satellites (in this case, Skysat with a spatial resolution of 0.5 meters) to detect illegal gold mining in the rivers of Loreto.

Below, we demonstrate how we used Skysat to detect illegal mining boats in the Nanay and Pintuyacu rivers, the main sources of drinking water for the city of Iquitos (capital of Loreto).

It is important to emphasize that this new technique has great potential for public institutions (national and regional levels) and local actors to detect and respond to illegal activity in real-time with appropriate measures (see the “Conclusion” section below).

Base Map: Mining in Nanay and Pintuyacu Rivers (Loreto region)

The Base Map below shows the precise points where illegal gold mining activity was found during 2020 and 2021 in the Nanay and Pintuyacu rivers of the Loreto region. For context, the map also includes the two nearby protected areas (one national, Allpahuayo Mishana, and another regional, Alto Nanay-Pintuyacu-Chambira). All the identified mining activity is illegal because there are no mining concessions in the area, in addition to the fact that it is occurring in bodies of water.

The yellow triangles indicate the illegal activity detected in 2020, based on field data or observations corroborated by specialists.

Based on this information, between March and May 2021, we tasked and analyzed very high-resolution satellite images (Skysat from the company Planet) for various strategic locations along both rivers. For images with possible mining activity, we consulted with field specialists for confirmation. The red triangles indicate the locations of illegal gold mining detected by Skysat and confirmed by the experts.

Base Map. Data: FEMA, MAAP, SERNANP.

Very High-resolution Satellite Images (Skysat)

Next, we show a series of striking images of illegal gold mining detected by Skysat and confirmed by experts. Note that with the very high resolution (0.5 meters), one can actually visualize the detail of a small mining boat. Image 1 shows several mining boats together in the Nanay River (near the town of Puca Urco). There are previous examples from the field of mining boats lining up together during their illegal activity (see the “Annex” section below).

Image 1. Mining boats in the Nanay River. Image: Skysat (Planet). Analysis: MAAP/Amazon Conservation.

Images 2-4 show other examples of likely mining boats in the Nanay River, this time within a national protected area (Alto Nanay-Pintuyacu-Chambira Regional Conservation Area). Note that these cases are also characterized by the presence of several boats lined up together.

Image 2. Mining boats in the Nanay River, in the Alto Nanay-Pintuyacu-Chambira Regional Conservation Area. Image: Skysat (Planet), Analysis: MAAP/Amazon Conservation.
Image 3. Mining boats in the Nanay River, in the Alto Nanay-Pintuyacu-Chambira Regional Conservation Area. Image: Skysat (Planet), Analysis: MAAP/Amazon Conservation.
Image 4: Mining boats in the Nanay River. Image: Skysat (Planet), Analysis: MAAP/Amazon Conservation.

Image 5 shows the presence of illegal mining boats in the Pintuyacu River.

Image 5: Mining boats in the Pintuyacu River. Image: Skysat (Planet), Analysis: MAAP/Amazon Conservation.

Conclusion

Unlike the dire situation in the southern Peruvian Amazon (Madre de Dios region), the illegal gold mining in northern Peru (Loreto region) does not cause deforestation and is caused by small mining boats in the rivers, making it practically invisible to medium and high-resolution satellites. This report presents a novel technique based on the strategic tasking of very high-resolution satellite images (Skysat) to detect this type of river-based illegal mining in real-time. With these images, we demonstrate the unprecedented capability to detect and visualize illegal activity in vast and remote areas, even down to the level of a small mining boat.

This new technique may allow public institutions and local actors to better respond to illegal activity in real-time with appropriate monitoring and control protocols. For example, key actors, such as the Peruvian Special Environmental Prosecutor’s Office (FEMA) can use this type of imagery in the planning and execution of their field interventions.

It is also important to highlight that the neighboring countries of Colombia and Bolivia experience the same problem of gold mining in rivers, so there is potential to replicate this model in other countries of the Amazon.

Annex

Here we show a photo from the field (Nanay River) of how the mining boats may line up during their illegal activity. This photo is for reference only and does not directly correspond to the cases described above.

Reference image of mining boats lined up during illegal activity. Source: ACRANPC.

Situación legal (in Spanish only)

El Decreto Legislativo N.° 1100 prohíbe, en el ámbito de la pequeña minería y minería artesanal, el uso de dragas y otros artefactos similares en todos los cursos de agua, ríos, lagos, lagunas, cochas, espejos de agua, humedales y aguajales. Por lo tanto, toda actividad enmarcada en este supuesto es considerada minería ilegal.

Mediante el Decreto Supremo N.° 150-2020-PCM se declara en emergencia varios distritos de Loreto por la inminente contaminación hídrica del río Nanay. A raíz de esto, se creó una comisión, cuyas actividades giraban en torno a varios operativos conjuntos, entre la Fiscalía Especializada en Materia Ambiental (FEMA), la Policía Nacional del Perú (PNP), la Dirección Regional de Energía y Minas (DREM) y la Autoridad Regional Ambiental (ARA), con el objetivo final de encontrar dragas en dicho río.

Mediante la Ordenanza Regional N.°  006-2003-GR, el Gobierno Regional de Loreto declaró la cuenca del río Nanay “zona de exclusión para actividades de extracción minera y para aquellas que alteren la cobertura vegetal.”

Acknowledgments

We thank Wendy Pineda from Rainforest US and Paul Lopez from the Satellite Monitoring Unit of the Loreto Environmental Specialized Prosecutor’s Office for their technical opinions regarding the confirmation of mining boats identified in the very high-resolution Skysat images.

We also thank Z. Romero (ACCA), G. Palacios (ACA), and G. Ribadeneyra, D. Torres, A. Felix, K. Nielsen, O. Liao and J. Carlos Guerra from USAID’s PREVENT Project, and J. Jara 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 is working 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.

Citation

Finer M, Novoa S, Paz L, Saurez D, Mamani N (2021) Detecting illegal gold mining in rivers with specialized satellites. MAAP: 140.

MAAP #139: Using Satellites to Detect Illegal Logging in Peruvian Amazon

Image 1. Illegal logging camp. Data: Skysat, MAAP/ACCA.

Illegal logging, in addition to larger-scale deforestation, is a major problem impacting the Peruvian Amazon.

In 2019, a Global Witness report, based on official information from the Peruvian government, estimated that at least 60% of the inspected timber over the past 10 years had an illegal origin. This problem not only directly affects the forest and its biodiversity, but also contributes to carbon loss (Qin et al, 2021) and forest degradation.

Illegal logging often involves the selective cutting of high-value trees in prohibited areas (whereas deforestation clears an entire area).

While numerous satellites can detect deforestation, only specialized satellites that are very high-resolution (less than one meter) can detect illegal logging.

In this report, we present a new emblematic case of illegal logging in the southern Peruvian Amazon.

It is based on a novel technique of tasking and analyzing very high-resolution images (in this case, with the Skysat satellite fleet from Planet) for a specific target area. Thanks to this new technique, we can tackle the problem of illegal logging in real-time, previously one of the biggest obstacles (see “Conclusion” section below).


Emblematic case

We refer to this as an emblematic case given the strong indicators of illegality (see Legal Status section, below) combined with likely significant impacts on an area of Amazon primary forest important for both indigenous peoples and biodiversity.

First, it is often difficult to confirm illegal logging given the frequent lack of updated technical and administrative information. This case study overcomes both obstacles.

Second, the illegal activity would not only be affecting a forestry concession (operated by the company Wood Tropical Forest), but also threatening important surrounding areas. Adjacent to the concession (to the west) is the Madre de Dios Territorial Reserve, a critical area that protects the territory of indigenous peoples in voluntary isolation. And to the south is the renowned Los Amigos Conservation Concession, a key area for the conservation of biodiversity.

Base Map

As part of our core work of continually monitoring the Los Amigos Conservation Concession, we acquired a series of very high-resolution images that also covered the surrounding Wood Tropical Forest forestry concession. These images, taken between February and April 2021, were obtained by the Skysat constellation (with a spatial resolution of 0.5 meters), operated by the satellite company Planet.

Our analysis revealed a serious situation of probable illegal logging: at least 3 active logging camps and 37 recently cut trees within the Wood Tropical Forest concession and close to both the neighboring Territorial Reserve and Conservation Concession (see Base Map).

Base Map. Data: MAAP/ACCA.

Very High-Resolution Skysat Images

The following images show some of the major findings made by our analysis of the Skysat data. Images 1-2 show examples of the logging camps, and Images 3-5 show examples of the likely selective illegal logging of high-value trees.

Image 2. Logging camp. Data: Skysat, MAAP/ACCA.
Image 3. Illegal logging. Data: Skysat, MAAP/ACCA.
Image 4. Illegal logging. Data: Skysat, MAAP/ACCA.
Image 5. Illegal logging. Data: Skysat, MAAP/ACCA.

Conclusion

This report presents a novel technique, based on the strategic capture of very high-resolution images (in this case, Skysat) and rapid analysis to detect selective illegal logging in real-time. Previously, one of the biggest obstacles to effectively addressing illegal logging was the inability of traditional monitoring methods to detect such small-scale, but widespread, illegal activity in the field. In this report, we demonstrate an important new capablility of detecting illegal logging activity in vast and remote areas in unprecedented detail, down to the level of a logging camp or individual cut trees.

Legal Situation (in Spanish)

La concesión forestal con Contrato N.° 17-TAM/C-J-007-02 fue otorgada en el año 2002 a la Empresa Shihuahuaco Timber S.A.C. y cedió su posición contractual a la empresa Wood Tropical Forestal en el año 2010, quien es titular del contrato de concesión hasta la actualidad.

La presunción de ilegalidad de la tala selectiva, evidenciada por nuestras imágenes satelitales, se debe a que la concesión forestal no se encontraría realizando actividades de aprovechamiento forestal enmarcadas en planes de manejo aprobados por el Gobierno Regional de Madre de Dios.

En efecto, tras realizar la consulta al Gobierno Regional de Madre de Dios, en su calidad de Autoridad Regional Forestal y de Fauna Silvestre (ARFFS), se advierte que la concesión se encuentra vigente. No obstante, no ha presentado a la ARFFS planes operativos para el aprovechamiento forestal desde hace más de ocho años. Incluso, desde el 30 de enero de 2020, cuenta con una resolución de la ARFFS que aprueba la suspensión del derecho de obligaciones contractuales (Resolución de Gerencia Regional N.° 065-2020-GOREMAD/GRFFS).

En ese sentido, y en tanto no se han presentado planes operativos en los últimos años, podemos inferir que en el área de la concesión forestal posiblemente no se estén realizando actividades lícitas de tala, por lo menos, desde hace ocho años.

Aunado a ello, en el Informe de Supervisión N.° 007-2019-OSINFOR/08.1.1, de acuerdo a una supervisión a la concesión para verificar obligaciones contractuales, el OSINFOR da cuenta de que la concesionaria presentó diversas denuncias entre los años 2016 al 2018 a la  Fiscalía Especializada en Materia Ambiental (FEMA), al Organismo de Supervisión de los Recursos Forestales y de Fauna Silvestre (OSINFOR) y al Gobierno Regional de Madre de Dios, en las cuales advirtió la presencia de terceras personas al interior de la concesión que estarían realizando tala ilegal, deforestación, instalación de campamentos ilegales, entre otros.

Acknowledgments

We thank E. Ortiz (AAF), Z. Romero (ACCA), G. Palacios (ACA), and A. Felix, J. Carlos Guerra, K. Nielsen, O. Liao, and R. Suarez from USAID’s PREVENT Project, and J. Jara 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 is working 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.

This work was also supported by NORAD (Norwegian Agency for Development Cooperation), ICFC (International Conservation Fund of Canada), and EROL Foundation.

Citation

Finer M, Yupanqui O, Suarez D, Novoa S (2021) Using Satellites to Detect Illegal Logging in Peruvian Amazon. MAAP: 139.

MAAP #137: New Illegal Gold Mining Hotspot in Peruvian Amazon – Pariamanu

Image 1. Very high-resolution image of the recent gold mining deforestation (10 hectares) in the new hotspot around the Pariamanu river. Data: Planet (Skysat)

In 2019, the Peruvian government launched Operation Mercury to confront the illegal gold mining crisis in the southern Amazonian area known as La Pampa (Madre de Dios region).

As a result, deforestation decreased 90% in this critical area (MAAP# 130).

Some illegal gold mining, however, has moved to several new hotspots (Image 1), although at much lower levels.

The most emblematic hotspot is located along the Pariamanu River, northeast of La Pampa in the Madre de Dios region (see Base Map, below).

We have documented the gold mining deforestation of 204 hectares (504 acres) in the Pariamanu area from 2017 to the present

This mining activity is clearly illegal because it is located within Brazil-nut forestry concessions, and is outside the permitted mining zone (commonly called the “mining corridor”).

Fortunately, a series of timely actions by the Peruvian Government has minimized the irreversible damage along the Pariamanu (see below).

The objective of this report is to present Pariamanu as an emblematic case that links technology with the rapid response action of public entities to address illegal activity in the Amazon.

It also represents a concrete case of strategic collaboration between civil society and the government to try and achieve zero illegal deforestation (and avoided deforestation).

Pariamanu

Base Map. Illegal gold mining deforestation along the Pariamanu river, in the context of La Pampa. Data: MAAP.

Base Map

The Base Map shows the location of illegal gold mining along the Pariamanu River, in the southern Peruvian Amazon (Madre de Dios region).

For context, La Pampa (the previous epicenter of illegal mining) and the regional capitol city of Puerto Maldonado are inlcuded. We also show another new illegal mining hotspot next to La Pampa, known as Apaylon.

In total, we have documented the deforestation of 204 hectares (504 acres) of primary forest caused by illegal gold mining in Pariamanu since 2017, indicated in red.

Note that this deforestation is located within Brazil nut forestry concessions and outside the “mining corridor,” thus clearly indicating its illegality.

Satellite Video: Illegal Gold Mining Deforestation in Pariamanu

We present a satellite image video showing an example of illegal gold mining in the Pariamanu area. These images show the deforestation of 71 hectares (175 acres) between 2016 (first image) and 2021 (last image), in the area indicated by the white inset box in the Base Map above. Note that each image is from July of each year (2016-20), with the exception of 2021 which shows January and March. Press the “play” button (lower left) to start the video. Click on the box (lower right) to view in full screen.

Satellite image video. Data: Planet.

Planet link: https://www.planet.com/stories/illegal-gold-mining-in-southern-peruvian-amazon-pa-6DfO4KuGg

MAAP Reports & Government Action

Operativo en Pariamanu, septiembre del 2020. Foto: FEMA Madre de Dios.

The first MAAP report about Pariamanu was published in November 2016, where we described “the start of mining in a new area” (MAAP #50). We found the mining-caused deforestation of 69 hectares (170 acres) on the banks of the Pariamanu river.

In January 2020, we published the second MAAP report about Pariamanu, documenting that the mining deforestation increased to 99 hectares (245 acres) (MAAP # 115). In this report, we warned that there were indications that some miners displaced by Operation Mercury (in February 2019) have moved to this area.

In response to this situation, the Peruvian Government, led by the Special Prosecutor for Environmental Matters (known as FEMA), carried out a series of field operations in 2020 (May, August and September, respectively), as an extension of Operation Mercury focused on cracking down on the illegal mining in Pariamanu.

The operations were effective in destroying mining equipment and sending a strong message that the government was engaged in this area.

However, we found that gold mining deforestation continued in several small areas between October 2020 and March 2021 (see Image 2), reaching the new total of 204 hectares (504 acres).

Fortunately, the government continues to respond effectively. Most recently (March 19, 2021), FEMA and the Peruvian Coast Guard carried out a new operation in Pariamanu, finding an illegal mining camp and equipment.

As mentioned above, the objective of this section (and this report) is to present Pariamanu as an emblematic case that links technology with the rapid response action of public entities to address illegal activity in the Amazon. It also represents a concrete case of strategic collaboration between civil society and the government to try and achieve zero illegal deforestation (and avoided deforestation).

Image 2. Data: Planet, MAAP.

Acknowledgments

We thank S. Novoa (ACCA), G. Palacios (ACA), and A. Felix, K. Nielsen, A. Caceres, I. Canelo, J. Carlos Guerra, O. Liao, y H. Che Piu from USAID’s PREVENT Project, 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 is working 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.

This work was also supported by NORAD (Norwegian Agency for Development Cooperation), ICFC (International Conservation Fund of Canada), and EROL Foundation.

Citation

Finer M, Mamani N (2021) New Illegal Gold Mining Hotspot in Peruvian Amazon – Pariamanu. MAAP: 137.

MAAP #136: Amazon Deforestation 2020 (Final)

Base Map. Forest loss hotspots across the Amazon in 2020. Data: Hansen/UMD/Google/USGS/NASA, RAISG, MAAP. The letters A-E correspond to the zoom examples below.

*To download the report, click “Print” instead of “Download PDF” at the top of the page.

In January, we presented the first look at 2020 Amazon deforestation based on early warning alert data (MAAP #132).

Here, we update this analysis based on the newly released, and more definitive, annual data.*

The Base Map illustrates the final results and indicates the major hotspots of primary forest loss across the Amazon in 2020.

We highlight several key findings:

  • The Amazon lost nearly 2.3 million hectares (5.6 million acres) of primary forest loss in 2020 across the nine countries it spans.
    g
  • This represents a 17% increase in Amazon primary forest loss from the previous year (2019), and the third-highest annual total on record since 2000 (see graph below).
    j
  • The countries with the highest 2020 Amazon primary forest loss are 1) Brazil, 2) Bolivia, 3) Peru, 4) Colombia, 5) Venezuela, and 6) Ecuador.
    h
  • 65% occurred in Brazil (which surpassed 1.5 million hectares lost), followed by 10% in Bolivia, 8% in Peru, and 6% in Colombia (remaining countries all under 2%).
    k
  • For Bolivia, Ecuador, and Peru, 2020 recorded historical high Amazon primary forest loss. For Colombia, it was the second highest on record.

In all of the data graphs, orange indicates the 2020 primary forest loss and red indicates all years with higher totals than 2020.

For example, the Amazon lost nearly 2.3 million hectares in 2020 (orange), the third highest on record behind only 2016 and 2017 (red).

Note that the three highest years (2016, 2017, and 2020) had one major thing in common: uncontrolled forest fires in the Brazilian Amazon.

See below for country-specific graphs, key findings, and satellite images for the top four 2020 Amazon deforestation countries (Brazil, Bolivia, Peru, and Colombia).

 

 

 

Brazilian Amazon

2020 had the sixth-highest primary forest loss on record (1.5 million hectares) and a 13% increase from 2019.

Many of the 2020 hotspots occurred in the Brazilian Amazon, where massive deforestation stretched across nearly the entire southern region.

A common phenomenon observed in the satellite imagery through August was that rainforest areas were first deforested and then later burned, causing major fires due to the abundant recently-cut biomass (Image A). This was also the pattern observed in the high-profile 2019 Amazon fire season. Much of the deforestation in these areas appears to associated with expanding cattle pasture areas.

In September 2020 (and unlike 2019), there was a shift to actual Amazon forest fires (Image B). See MAAP #129 for more information on the link between deforestation and fire in 2020.

Note that the three highest years (2016, 2017, and 2020) had one major thing in common: uncontrolled forest fires in the Brazilian Amazon.

Image A. Deforestation in Brazilian Amazon (Amazonas state) of 2,540 hectares between January (left panel) and November (right panel) 2020. Data: Planet.

Image B. Forest fire in Brazilian Amazon (Para state) that burned 9,000 hectares between March (left panel) and October (right panel) 2020. Data: Planet.

Bolivian Amazon

2020 had the highest primary forest loss on record in the Bolivian Amazon, surpassing 240,000 hectares.

Indeed, the most intense hotspots across the entire Amazon ocurred in southeast Bolivia, where fires raged through the drier Amazon forests (known as the Chiquitano and Chaco ecosystems).

Image C shows the burning of a massive area (over 260,000 hectares) in the Chiquitano dry forests (Santa Cruz department).

 

 

 

 

Image C. Forest fire in Bolivian Amazon (Santa Cruz) that burned over 260,000 hectares between April (left panel) and November (right panel) 2020. Data: ESA.

Peruvian Amazon

2020 also had the highest primary forest loss on record in the Peruvian Amazon, surpassing 190,000 hectares.

This deforestation is concentrated in the central region. On the positive, the illegal gold mining that plagued the southern region has decreased thanks to effective government action (see MAAP #130).

Image D shows expanding deforestation (over 110 hectares), and logging road construction (3.6 km), in an indigenous territory south of Sierra del Divisor National Park in the central Peruvian Amazon (Ucayali region). The deforestation appears to be associated with an expanding small-scale agriculture or cattle pasture frontier.

 

 

Image D. Deforestation and logging road construction in Peruvian Amazon (Ucayali region) between March (left panel) and November (right panel) 2020. Data: Planet.

Colombian Amazon

2020 had the second-highest primary forest loss on record in the Colombian Amazon, nearly 140,000 hectares.

As described in previous reports (see MAAP #120), there is an “arc of deforestation” concentrated in the northwest Colombian Amazon. This arc impacts numerous protected areas (including national parks) and Indigenous Reserves.

For example, Image E shows the recent deforestation of over 500 hectares in Chiribiquete National Park. Similar deforestation in that sector of the park appears to be conversion to cattle pasture.

 

 

 

Image E. Deforestation in Colombian Amazon of over 500 hectares in Chiribiqete National Park between January (left panel) and December (right panel) 2020. Data: ESA, Planet.

*Notes and Methodology

To download the report, click “Print” instead of “Download PDF” at the top of the page.

The analysis was based on 30-meter resolution annual data produced by the University of Maryland (Hansen et al 2013), obtained from the “Global Forest Change 2000–2020” data download page. It is also possible to visualize and interact with the data on the main Global Forest Change portal.

Importantly, this data detects and classifies burned areas as forest loss. Nearly all Amazon fires are human-caused. Also, this data does include some forest loss caused by natural forces (landslides, wind storms, etc…).

Note that when comparing 2020 to early years, there are several methodological differences from the University of Maryland introduced to data after 2011. For more details, see “User Notes for Version 1.8 Update.”

It is worth noting that we found the early warning (GLAD) alerts to be a good (and often conservative) indicator of the final annual data.

Our geographic range includes nine countries and consists of a combintion of the Amazon watershed limit (most notably in Bolivia) and Amazon biogeographic limit (most notably in Colombia) as defined by RAISG. See Base Map above for delineation of this hybrid Amazon limit, designed for maximum inclusion. Inclusion of the watershed limit in Bolivia is a recent change incorporated to better include impact to the Amazon dry forests of the Chaco.

We applied a filter to calculate only primary forest loss. 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).

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)
Everything else was left to the default setting.

For the Base Map, we used the following concentration percentages: Medium: 7-10%; High: 11-20%; Very High: >20%.

 

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.

Acknowledgements

We thank E. Ortiz (AAF), M. Silman (WFU), M. Weisse (WRI/GFW) for their helpful comments on this report.

This work was supported by NORAD (Norwegian Agency for Development Cooperation) and ICFC (International Conservation Fund of Canada).

Citation

Finer M, Mamani N (2020) Amazon Deforestation Hotspots 2020 (Final). MAAP: 136.