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.

*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.
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  • 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).
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  • The countries with the highest 2020 Amazon primary forest loss are 1) Brazil, 2) Bolivia, 3) Peru, 4) Colombia, 5) Venezuela, and 6) Ecuador.
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  • 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%).
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  • 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.

MAAP #134: Agriculture and Deforestation in the Peruvian Amazon

Peru’s first National Agricultural Area Map. Source: MIDAGRI.

For the first time, Peru has a detailed National Agricultural Area Map.

This unique map, produced with high-resolution satellite imagery, was published by the Peruvian Ministry of Agrarian Development (MIDAGRI) in January.*

This map reveals that the agricultural area at the national level is 11.6 million hectares, as of 2018.

Here, we analyze this new information in relation to annual forest loss data, generated by the Peruvian Environment Ministry (Geobosques).

The goal is to better understand the critical link between agriculture and deforestation in the Peruvian Amazon.

Specifically, we analyze the agricultural area of 2018 in relation to the preceding forest loss between 2001 and 2017.

Below are two main sections:

First, we present our Base Map that illustrates the major results.

Second, we show a series of zoomed images of select areas to illustrate key results in detail. These areas include major deforestation events related to oil palm, cacao, and other crops.

 

 

 

 

 

Base Map showing our major results. Data: MAAP, MIDAGRI, MINAM/Geobosques. Double click to enlarge.

Major Results

  • We found that 43% (4.9 million hectares) of Peru’s total agricultural area in 2018 was located in the Amazon basin.
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  • Of these Amazonian agricultural areas, more than 1.1 million hectares (24%) came from forest lost between 2001 and 2017 (indicated in red on the Base Map).
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  • Expressed another way, over half (56%) of the forest loss in the Peruvian Amazon between 2001 and 2017 corresponds to an agricultural area in 2018.
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  • The Base Map also shows, in brown, the agricultural area that is not linked to recent forest loss. The vast majority is located outside the Amazon basin (western Peru).
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  • Finally, the Base Map shows, in black, the recent forest loss not linked to agriculture. Much of this loss corresponds to gold mining (southeastern Peru), logging roads, and natural loss such as landslides.

 

 

 

 

 

 

Zooms of Key Areas

A. United Cacao (Loreto)

Image A shows the large-scale deforestation associated with the company United Cacao between 2013 and 2016, in the Loreto region  (MAAP # 128). The clearing, as the name indicates, was for the installation of Peru’s first and only industrial-style cacao plantation. In total, the deforestation for the plantation reached 2,380 hectares.

Zoom A. United Cacao (Loreto region). Data: MAAP, MIDAGRI, MINAM/Geobosques.

B. Oil Palm (Shanusi, Loreto)

Image B shows the large-scale deforestation of more than 16,800 hectares associated with oil palm plantations between 2006 and 2015, along the border of the Loreto and San Martin regions (MAAP #116). Of this total, the deforestation of 6,975 hectares was linked to two plantations managed by the company Grupo Palmas company. The remainder occurred in the private areas surrounding the company’s plantations.

Zoom B. Oil palm deforestation around Shanusi (Loreto region). Data: MAAP, MIDAGRI, MINAM/Geobosques.

C. Oil Palm (Ucayali)

Image C shows the large-scale deforestation of more than 12,000 hectares for two oil palm plantations between 2011 and 2015, in the Ucayali region (MAAP #41).

Zoom C. Oil palm deforestation (Ucayali region). Data: MAAP, MIDAGRI, MINAM/Geobosques.

D. Iberia (Madre de Dios)

Image D shows the expanding agriculture-related deforestation around the town of Iberia, near the border with Brazil and Bolivia (MAAP #75). The major cause, according to local sources, is the increase in corn, papaya, and cacao plantations. We have documented the deforestation of more than 3,000 hectares in this area since 2014.

Zoom D. Agriculture related deforestation around Iberia (Madre de Dios region). Data: MAAP, MIDAGRI, MINAM/Geobosques.

E. Zona Minera (Madre de Dios)

Finally, Image E shows deforestation in the gold mining hotspot known as La Pampa, in the Madre de Dios region. The non-agricultural deforestation in the center is the major illegal gold mining front. Around that area, and along the Interoceanic Highway, there is extensive agriculture-related deforestation.

Zoom E. Mining and agriculture deforestation in southern Peru (Madre de Dios region). Data: MAAP, MIDAGRI, MINAM/Geobosques.

*Notes and Methodology

According to MIDAGRI, the National Agricultural Area Map was “generated based on satellite images from RapidEye and later updated with satellite images from Sentinel-2 and the Google Earth platform, which allowed the mapping and precise measurement of the agricultural surface throughout the national territory.”

The data include “agricultural land with cultivation and without cultivation.” We assume that these data include cattle pasture.

The identification and quantification of deforested areas (2001-2017) that correspond to agricultural area in 2018 results from the analysis carried out in GIS by the superposition of both geospatial layers (MINAM and MIDAGRI).

Amazonian agricultural areas that came from forest lost between 2001 and 2017 = 1,185,722 hectares (indicated in red on the Base Map).

Acknowledgments

We thank E. Ortiz (AAF), S. Novoa (ACCA) and G. Palacios for their helpful comments on this report.

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

Citation

Vale Costa H, Finer M (2021) Agriculture and Deforestation in the Peruvian Amazon. MAAP: 134.

MAAP #131: Power of Free High-resolution Satellite Imagery from Norway Agreement

Image 1. Monthly Planet basemap for October 2020 across the Amazon, as seen on Global Forest Watch.

This report demonstrates the powerful application of freely available, high-resolution satellite imagery recently made possible thanks to an agreement between the Government of Norway and several satellite companies.*

This unprecedented agreement will bring commercial satellite technology, previously out of reach to many, to all working in tropical forest conservation around the world.

Here we show how MAAP (an initiative of Amazon Conservation) will use this information to enhance our real-time monitoring program and quickly share timely findings to partners in the field.

Specifically, we highlight the importance of the monthly basemaps (4.7-meter Planet imagery) available under the Norway agreement.* For example, Image 1 shows the stunning, nearly cloud-free October 2020 basemap across the Amazon.

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Moreover, we show the power of this imagery visualized on Global Forest Watch, where it can be combined with early warning forest loss alerts.
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Below, we highlight three examples where we combined this data to quickly detect and confirm deforestation in the Colombian, Ecuadorian, and Peruvian Amazon, respectively.

Colombian Amazon

First, we detected recent forest loss alerts (known as GLAD alerts), in the northwestern sector of Chiribiquete National Park. Image 2 is a screen shot of our monitoring search in Global Forest Watch (link here).

Second, we investigated the alerts with the freely available monthly Planet basemaps. Images 3-5 show the basemaps from October to December 2020. These images confirm that the area was covered in intact (likely primary) Amazon rainforest in October, and then experienced a major deforestation event (225 hectares) in November and December. Similar deforestation in the area appears to be conversion to cattle pasture. Note the crosshairs (+) represent the same point in all four images.

Image 2. Forest loss alerts in Chiribiquete National Park

Image 3. Monthly Planet basemap for October 2020 in Chiribiquete National Park.

Image 4. Monthly Planet basemap for November 2020 in Chiribiquete National Park.

Image 5. Monthly Planet basemap for December 2020 in Chiribiquete National Park.

Peruvian Amazon

Similarly, we detected recent forest loss alerts in an illegal gold mining area in the southern Peruvian Amazon known as Pariamanu (Image 6). Images 7 & 8 show the monthly basemaps confirming the expansion of illegal mining deforestation between October and December (see yellow arrows). Global Forest Watch link here.

Image 6. Forest loss alerts in illegal gold mining zone (Pariamanu).

Image 7. Monthly Planet basemap for October 2020 in Pariamanu.

Image 8. Monthly Planet basemap for October 2020 in Pariamanu.

Ecuadorian Amazon

Finally, we detected recent forest loss alerts of 100 hectares in an indigenous territory (Kichwa) surrounding an oil palm plantation in the Ecuadorian Amazon (Image 9). Images 10 & 11 show the monthly basemaps confirming large-scale deforestation between September and December, likely for the expansion of the plantation. Note the crosshairs (+) represents the same point in all three images. Global Forest Watch link here.

Image 9. Forest loss alerts in the Ecuadorian Amazon.

Image 10. Monthly Planet basemap for September 2020 in Ecuadorian Amazon.

Image 11. Monthly Planet basemap for December 2020 in Ecuadorian Amazon.

Summary

In summary, we show a major advance for free and real-time deforestation monitoring thanks to an agreement between the Government of Norway and satellite companies.* A key aspect of this agreement is making publically available (such as on Global Forest Watch) monthly basemaps created by the innovative satellite company Planet. Thus, users can now freely visualize recent forest loss alerts and then investigate them with high-resolution monthly basemaps on On Global Forest Watch. MAAP illustrated this process with three examples in the Colombian, Peruvian, Ecuadorian Amazon, respectively.

*Notes 

In September 2020, Norway’s Ministry of Climate and Environment entered into a contract with Kongsberg Satellite Services (KSAT) and its partners Planet and Airbus, to provide universal access to high-resolution satellite monitoring of the tropics in order to support efforts to stop the destruction of the world’s rainforests. This effort is led by Norway’s International Climate and Forest Initiative (NICFI). The basemaps are mosaics of the best cloud-free pixels each month. In addition to viewing the monthly basemaps on Global Forest Watch, users can sign up with Planet directly at this link: https://www.planet.com/nicfi/

Acknowledgements

We thank M. Cohen (ACA), M. Weisse (WRI/GFW), E. Ortiz (AAF) and G. Palacios for their helpful comments on this report.

This work was supported by NORAD (Norwegian Agency for Development Cooperation).

Citation

Finer M, Mamani N (2020) Power of Freely Available, High-resolution Satellite Imagery from Norway Agreement. MAAP: 131.

MAAP #130: Illegal Gold Mining Down 78% in Peruvian Amazon, But Still Threatens Key Areas

Image 1. Very high resolution image of recent gold mining deforestation along the Pariamanu River. Data: Planet (Skysat).

As part of USAID’s Prevent Project (dedicated to combating environmental crimes in the Amazon), we conducted an updated analysis of illegal gold mining deforestation in the southern Peruvian Amazon.

In early 2019, the Peruvian government launched Operation Mercury, an unprecedented crackdown on the rampant illegal gold mining in the region.

The Operation initially targeted an area known as La Pampa, the epicenter of the illegal mining. In 2020, it expanded to surrounding critical areas.

In this report, we compare rates of gold mining deforestation before vs after Operation Mercury at six key sites (see Base Map and Methodology below).

We report four major results:

1) Gold mining deforestation decreased 90% in La Pampa (the most critical mining area) following Operation Mercury.

2) Gold mining deforestation increased in three key areas –Apaylon, Pariamanu, and Chaspa – indicating that some miners expelled from La Pampa moved to surrounding areas. The Peruvian government, however, has recently carried out major interventions in all three of these areas.

3) Overall, gold mining deforestation decreased 78% across all six sites following Operation Mercury.

4) Illegal mining does persist, however. We documented 1,115 hectares of gold mining deforestation across all six sites since Operation Mercury (but, compared to 6,490 hectares before the Operation).

Below, we provide a more detailed breakdown of the major results across all six sites. We also present a series of very high resolution satellite images (Skysat) of the recent gold mining deforestation.

Base Map – 6 Major Illegal Gold Mining Sites

The Base Map illustrates the results across the six major gold mining fronts in the southern Peruvian Amazon. Red indicates gold mining deforestation post Operation Mercury (March 2019 – October 2020), while yellow indicates the pre Operation baseline (January 2017 – February 2019).

Base Map. Major gold mining fronts in the southern Peruvian Amazon before (yellow) and after (red) Operation Mercury. Data: MAAP.

In La Pampa, we documented the dramatic loss of 4,450 hectares within the buffer zone of Tambopata National Reserve (Madre de Dios region) prior to Operation Mercury. Following the Operation, we confirmed the loss of 300 hectares. Note the main mining front in the core of the buffer zone has essentially been stopped, with most recent activity further north near the Interoceanic Highway.

In neighboring Alto Malinowski, located in the buffer zone of Bahuaja Sonene National Park (Madre de Dios region), we documented the loss of 1,558 hectares prior to Operation Mercury. Following the Operation, we confirmed the loss of 419 hectares.

In Camanti, located in the buffer zone of Amarakaeri Commuanl Reserve, we documented the loss of 336 hectares prior to Operation Mercury. Following the Operation, we confirmed the loss of 105 hectares.

In Pariamanu, located in the primary forests along the Pariamanu River (Madre de Dios region), we documented the loss of 72 hectares prior to Operation Mercury. Following the Operation, we confirmed the loss of 98 hectares. In response, the government conducted a major intervention in August 2020.

In Apaylon, located in the buffer zone Tambopata National Reserve (Madre de Dios region), we documented the loss of 73 hectares prior to Operation Mercury. Following the Operation, we confirmed the loss of 78 hectares. In response, the government has conducted a series of interventions in the area during 2020.

Chaspa, located in the buffer zone of Bahuaja Sonene National Park (Puno region), represents a unique case of a new gold mining front that appeared following Operation Mercury. Starting in September 2019, we documented the deforestation of 113 hectares impacting the Chaspa River watershed. In response, the government conducted a major intervention in October 2020.

Gold Mining Deforestation Trends

The following chart illustrates that gold mining deforestation fronts decreased following Operation Mercury in the three largest fronts (La Pampa, Alto Malinowski, and Camanti), and increased in three smaller areas (Pariamanu, Apaylon, and Chaspa). Thus, overall gold mining deforestation decreased 78% across all six major sites following Operation Mercury.

Table 1. Rates of gold mining deforestation before (orange) and after (red) Operation Mercury. Data: MAAP.

In La Pampa, the gold mining deforestation averaged 165 hectares per month prior to Operation Mercury. Following the Operation, the deforestation dropped to 17 hectares per month, an overall 90% decrease.

In Alto Malinowski, the gold mining deforestation dropped from 58 hectares per month to 23 hectares per month following Operation Mercury, an overall 60% decrease.

In Camanti, the gold mining deforestation dropped from 12.5 hectares per month to 6 hectares per month following Operation Mercury, an overall 54% decrease.

In Pariamanu, the gold mining deforestation increased from 2.8 hectares per month to 5 hectares per month following Operation Mercury, an overall 87% increase.

In Apaylon, the gold mining deforestation increased from 2.8 hectares per month to 4 hectares per month following Operation Mercury, an overall 43% increase.

Chaspa, located in the buffer zone of Bahuaja Sonene National Park, represents the unique case of a new gold mining front that appeared following Operation Mercury (8.5 hectares per month).

Very High Resolution Satellite Imagery (Skysat)

We recently tasked very high resolution satellite imagery (Skysat, 0.5 meter) for the major illegal gold mining areas. Below, we present a series showing some of the highlights from these images. Note that insets (in the upper corner of each image) show the same area before the mining activity (see red points as a reference).

Pariamanu

The following two images show the expansion of new gold mining areas into the primary rainforests near the Pariamanu River (Madre de Dios region).

Image 2. Expansion of new gold mining areas into the primary rainforests near the Pariamanu River (Madre de Dios region). Data: Planet.

Image 3. Expansion of new gold mining areas into the primary rainforests near the Pariamanu River (Madre de Dios region). Data: Planet.

La Pampa

The following image shows the expansion of a new gold mining area in the northern part of La Pampa.

Image 4. Expansion of a new mining area in the northern part of La Pampa (Madre de Dios region). Data: Planet, Maxar.

Chaspa

The following image shows the sudden appearance of a new gold mining front along the Chaspa River (Puno region).

Image 5. New gold mining front along the Chaspa River (Puno region). Data: Planet (Skysat).

Camanti

The following image shows the recent expansion of gold mining deforestation in the buffer zone of Amarakaeri Communal Reserve (Cusco region).

Image 6. Recent expansion of gold mining deforestation in the buffer zone of Amarakaeri Communal Reserve (Cusco region). Data: Planet (Skysat).

Methodology

We analyzed high-resolution imagery (3 meters) from the satellite company Planet obtained from their interface Planet Explorer. Based on this imagery, we digitized gold mining deforestation across six major sites: La Pampa, Alto Malinowski, Camanti, Pariamanu, Apaylon, and Chaspa. These were identified as the major active illegal gold mining deforestation fronts based on analysis of automated forest loss alerts generated by University of Maryland (GLAD alerts) and the Peruvian government (Geobosques) and additional land use layers. The area referred to as the “mining corridor” is not included in the analysis because the issue of legality is more complex.

Across these six sites, we identified, digitized, and analyzed all visible gold mining deforestation between January 2017 and the present (October 2020). We defined before Operation Mercury as data from January 2017 to February 2019, and after Operation Mercury as data from March 2019 to the present. Given that the former was 26 months and the latter 20 months, during the analysis the data was standardized as gold mining deforestation per month.

The data is updated through October 2020.

Acknowledgments

We thank A. Felix (DAI), S. Novoa (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 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, Mamani N (2020) Illegal Gold Mining Down 79% in Peruvian Amazon, But Still Threatens Key Areas. MAAP: 130.

MAAP #126: Drones and Legal Action in the Peruvian Amazon

ACOMAT member flying a drone for monitoring their forestry concession. Source: ACCA.

The southern Peruvian Amazon (Madre de Dios region), is threatened by illegal mining, logging, and illegal deforestation.

In response, an association of forest concessionaires (known as ACOMAT) is implementing a comprehensive monitoring system that links the use of technology (satellites and drones) with legal action.

ACOMAT was formed in 2012 and now comprises 15 forestry concessions, covering 440,000 acres (178,000 hectares) in the southern Peruvian Amazon (see Base Map). Most of the concessions are alternatives to logging, such as Brazil nuts, Conservation, and Ecotourism.

This comprehensive system has three main elements:

1) Real-time, satellite-based forest loss monitoring (such as GLAD alerts) to quickly detect any possible new threats, even across vast and remote areas.

2) Field patrols with drone flights to verify forest alerts (or monitor threatened areas) with very high resolution images.

3) If suspected illegality is documented, initiate a criminal or administrative complaint, utilizing both the satellite and drone-based evidence.

In the case of ACOMAT, during 2019 they conducted 26 drone patrols and filed 15 legal complaints with the regional Environmental Prosecutor’s Office, known as FEMA. Below, we describe several of these cases.

Note that there is high potential to replicate this comprehensive monitoring model at the level of forest custodians (for example, concessionaires and indigenous communities) in the Amazon and other tropical forests.

Key ACOMAT Cases

Next, we describe four cases where comprehensive monitoring was performed (see Insets A-D on the Base Map).

Base Map. ACOMAT concessions. Data: ACCA, MINAM/PNCBMCC, SERNANP.

A. Illegal logging in the Los Amigos Conservation Concession

In October 2019, a patrol was carried out to investigate a threatened area within the Los Amigos Conservation Concession (the world’s first Conservation Consession). During the patrol, which included five drone flights, illegal logging was documented, including stumps with sawn trees , paths for the transfer of wood to a nearby river, and abandoned camps. The drone images were added as evidence in support of the previously filed criminal complaint to the FEMA in Madre de Dios. Below we present two striking images from the drone flights, clearly showing the illegal logging. Status of the Complaint: In Preliminary Investigation.

Case A. Illegal logging in the Los Amigos Conservation Concession, identified with drone overflight. Source: ACCA.

Case A. Illegal logging in the Los Amigos Conservation Concession, identified with drone overflight. Source: ACCA.

B. Ilegal Logging in the MADEFOL Forestry Concession

In May 2019, a field patrol was carried out to investigate a threatened area within the MADEFOL forestry concession. During the patrol, which included two drone flights, illegal logging was documented, including stumps with sawn trees, a recently abandoned camp, and an access road. With the drone images as evidence, a new criminal complaint was filed with the FEMA in Madre de Dios. Below is an image from the drone flights, clearly showing the evidence of illegal logging. Status of the complaint: In qualification.

Case B. Illegal logging in the “MADEFOL” forestry concession identified with drone overflight. Source: ACCA.

C. Illegal Gold Mining in a Conservation Concession

In May 2019, a field patrol was carried out in the “Inversiones Manu SAC” Conservation Concession to investigate an area that had previously been affected by illegal gold miners. During the patrol, which included two drone flights, illegal gold mining was documented in the Malinowski River. With the drone images as evidence, a new criminal complaint was filed with the FEMA in Madre de Dios. Below is a drone image clearly showing the evidence of illegal gold mining. Status of the complaint: Preliminary Investigation.

Caso C. Minería ilegal en la Concesión de Conservación “Inversiones Manu SAC,” identificada con sobrevuelo de dron. Fuente: ACCA.

D. Deforestation in a Brazil Nut Concession

In October 2019, a patrol was carried out to investigate an early warning deforestation alert within the “Sara Hurtado Orozco B” Brazil nut concession.

During the patrol, which included one drone flight, the recent deforestation of five acres (two hectares) was documented. With the drone images, a new criminal complaint was filed with the FEMA of Madre de Dios. It should be noted that this concession was being investigated for a separate illegal deforestation event. Below is one of the images of the drone flight, clearly showing the illegal deforestation. Status of the complaint: In preliminary proceedings.

Caso D. Deforestación en la Concesión Forestal de Castaña “Sara Hurtado Orozco B”. Fuente: ACCA.

Importance of the “ACOMAT Model”

We have started using the term “Acomat model” to refer to the innovative use of the three elements described above (real-time monitoring, drone flights, and criminal complaints) by the ACOMAT concessionaires.

ACOMAT was created in 2012, and since 2017 has received crucial support from the organization Conservation Amazónica-ACCA, supported by funds from Norway’s International Climate and Forest Initiative (NICFI), led by the Norwegian Agency for Development Cooperation (NORAD).

This project has provided training on all three major aspects, satellite-based monitoring alerts, drones, and the legal process. Concessionaires now receive deforestation alerts to their phones, have the ability to organize and conduct field patrols, and some are trained to perform their own drone flights.

Acknowledgments

We thank R. Segura (DAI), M.E. Gutierrez (ACCA), D. Suarez (ACCA), H. Balbuena (ACCA), M. Silman (WFU), 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.

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

Citation

Finer M, Castañeda C, Novoa S, Paz L (2020) Drones and Legal Action in the Peruvian Amazon. MAAP 126.

 

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

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 #124: Deforestation Hotspots 2020 in the Peruvian Amazon.

Base Map. 2020 Forest Loss Hotspots in the Peruvian Amazon. Data: UMD/GLAD, MAAP, SERNANP.

We have entered the peak deforestation season in the Peruvian Amazon, so it is also a critical time for real-time monitoring (MAAP’s specialty).

Here, we highlight the major deforestation events documented so far in 2020 (through August 23).

The Base Map shows the current forest loss hotspots, indicated by the colors yellow, orange and red.

Below, we present the most urgent deforestation cases, caused by gold mining and agriculture (both large and small scale), the current leading deforestation drivers in Peru.

The Letters A-I on the Base Map correspond to the location of the cases described below.

One of the key cases is the new illegal gold mining hotspot along the Pariamanu river (Letter A in the southern Peruvian Amazon).

Another important case is the expanding large-scale agriculture by a Mennonite colony that continues causing an alarming deforestation.

The other cases deal with small-scale agriculture, which cumulatively represent the main deforestation driver in Peru.

Urgent Deforestation Cases 2020

1. Gold Mining

In MAAP #121, we reported that, in general, gold mining deforestation has decreased in the southern Peruvian Amazon following the government’s Operation Mercury, but it does continue in several critical areas. The images below show two of these areas (Pariamanu and Araza) with alarming new deforestation in 2020.

A. Pariamanu

The following image shows the gold mining deforestation of 52 acres (21 hectares) of primary forest along the Pariamanu River in the southern Peruvian Amazon (Madre de Dios region) between January (left panel) and August (right panel) of 2020. We highlight that the Peruvian government has just carried out an operation against the illegal mining activity in this area.

Pariamanu case (illegal gold mining). Data: Planet, MAAP.

B. Araza

The following image shows the gold mining deforestation of 114 acres (46 hectares) along the Chaspa River in the Puno region, between January (left panel) and August (right panel) of 2020.

Araza case. Data: Planet, MAAP.

2. Large-scale Agriculture

C. Mennonite Colony (near Tierra Blanca)

We reported last year that a new colony of Mennonites caused the deforestation of 4,200 acres (1,700 hectares) between 2017 and 2019 in the Loreto region (MAAP #112). The following image shows the additional deforestation of 820 acres (332 hectares) in 2020 between January (left panel) and August (right panel).

Mennonite case (near Tierra Blanca). Data: Planet, MAAP.

3. Small-scale Agriculture

D. Jeberos

In 2018, we reported on the construction of a new road (65 km) cutting through primary forest in the Loreto region, between the city of Yurimaguas and the town of Jeberos (MAAP #84). The following image shows the deforestation of 40 acres (16 hectares) along the new road in 2020, between January (left panel) and August (right panel).

Jeberos case (near Tierra Blanca). Data: Planet, MAAP.

E. Las Piedras

The following image shows the deforestation of 64 acres (26 hectares) of primary forest in a Brazil-nut concession along the Las Piedras River in the Madre de Dios region, between November 2019 (left panel) and August 2020 (right panel) .

Las Piedras case. Data: Planet, MAAP.

F. Bolognesi

The following image shows an example of deforestation (580 acres or 235 hectares) in one of the areas with the highest concentration of forest loss, located in the Ucayali region.

Bolognesi case. Data: Planet, MAAP.

G. Santa Maria de Nieva

The following image shows an example of deforestation(346 acres or 140 hectares) in another one of the areas with the highest concentration of forest loss, located in the Amazonas region.

Santa Maria de Nieva case. Data: Planet, MAAP.

H. Mishahua River

The following image shows the recent deforestation of 168 acres (68 hectares) along the Mishahua River, in the Ucayali region. Just to the north, we documented extensive deforestation along the Sepahua River in 2019, where it also appears to be starting up again in 2020.

Mishahua case. Data: Planet, MAAP.

I. South of Sierra del Divisor National Park

The following image shows an example of deforestation (166 acres or 67 hectares) in another one of the areas with the highest concentration of forest loss, located south of the Sierra del Divisor National Park in the Ucayali region.

Mishahua case. Data: Planet, MAAP.

 

Metodology

The analysis was based on early warning GLAD alerts from the Universidad de Maryland and Global Forest Watch.

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 S. Novoa 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 (2020) Deforestation Hotspots 2020 in the Peruvian Amazon. MAAP: 124.

MAAP #124: Deforestation Hotspots 2020 in the Peruvian Amazon

Base Map. 2020 Forest Loss Hotspots in the Peruvian Amazon. Data: UMD/GLAD, MAAP, SERNANP.

We have entered the peak deforestation season in the Peruvian Amazon, so it is also a critical time for real-time monitoring (MAAP’s specialty).

Here, we highlight the major deforestation events documented so far in 2020 (through August 23).

The Base Map shows the current forest loss hotspots, indicated by the colors yellow, orange and red.

Below, we present the most urgent deforestation cases, caused by gold mining and agriculture (both large and small scale), the current leading deforestation drivers in Peru.

The Letters A-I on the Base Map correspond to the location of the cases described below.

One of the key cases is the new illegal gold mining hotspot along the Pariamanu river (Letter A in the southern Peruvian Amazon).

Another important case is the expanding large-scale agriculture by a Mennonite colony that continues causing an alarming deforestation.

The other cases deal with small-scale agriculture, which cumulatively represent the main deforestation driver in Peru.

 

 

 

 

 

Urgent Deforestation Cases 2020

1. Gold Mining

In MAAP #121, we reported that, in general, gold mining deforestation has decreased in the southern Peruvian Amazon following the government’s Operation Mercury, but it does continue in several critical areas. The images below show two of these areas (Pariamanu and Araza) with alarming new deforestation in 2020.

A. Pariamanu

The following image shows the gold mining deforestation of 52 acres (21 hectares) of primary forest along the Pariamanu River in the southern Peruvian Amazon (Madre de Dios region) between January (left panel) and August (right panel) of 2020. We highlight that the Peruvian government has just carried out an operation against the illegal mining activity in this area.

Pariamanu case (illegal gold mining). Data: Planet, MAAP.

B. Araza

The following image shows the gold mining deforestation of 114 acres (46 hectares) along the Chaspa River in the Puno region, between January (left panel) and August (right panel) of 2020.

Araza case. Data: Planet, MAAP.

2. Large-scale Agriculture

C. Mennonite Colony (near Tierra Blanca)

We reported last year that a new colony of Mennonites caused the deforestation of 4,200 acres (1,700 hectares) between 2017 and 2019 in the Loreto region (MAAP #112). The following image shows the additional deforestation of 820 acres (332 hectares) in 2020 between January (left panel) and August (right panel).

Mennonite case (near Tierra Blanca). Data: Planet, MAAP.

3. Small-scale Agriculture

D. Jeberos

In 2018, we reported on the construction of a new road (65 km) cutting through primary forest in the Loreto region, between the city of Yurimaguas and the town of Jeberos (MAAP #84). The following image shows the deforestation of 40 acres (16 hectares) along the new road in 2020, between January (left panel) and August (right panel).

Jeberos case (near Tierra Blanca). Data: Planet, MAAP.

 

E. Las Piedras

The following image shows the deforestation of 64 acres (26 hectares) of primary forest in a Brazil-nut concession along the Las Piedras River in the Madre de Dios region, between November 2019 (left panel) and August 2020 (right panel) .

Las Piedras case. Data: Planet, MAAP.

F. Bolognesi

The following image shows an example of deforestation (580 acres or 235 hectares) in one of the areas with the highest concentration of forest loss, located in the Ucayali region.

Bolognesi case. Data: Planet, MAAP.

G. Santa Maria de Nieva

The following image shows an example of deforestation(346 acres or 140 hectares) in another one of the areas with the highest concentration of forest loss, located in the Amazonas region.

Santa Maria de Nieva case. Data: Planet, MAAP.

H. Mishahua River

The following image shows the recent deforestation of 168 acres (68 hectares) along the Mishahua River, in the Ucayali region. Just to the north, we documented extensive deforestation along the Sepahua River in 2019, where it also appears to be starting up again in 2020.

Mishahua case. Data: Planet, MAAP.

I. South of Sierra del Divisor National Park

The following image shows an example of deforestation (166 acres or 67 hectares) in another one of the areas with the highest concentration of forest loss, located south of the Sierra del Divisor National Park in the Ucayali region.

Mishahua case. Data: Planet, MAAP.

 

Metodology

The analysis was based on early warning GLAD alerts from the Universidad de Maryland and Global Forest Watch.

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 S. Novoa 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 (2020) Deforestation Hotspots 2020 in the Peruvian Amazon. MAAP: 124.

MAAP #122: Amazon Deforestation 2019

Table 1. Primary forest loss for 2019 (red) compared to 2018 (orange). Data: Hansen/UMD/Google/USGS/NASA, MAAP.

Newly released data for 2019 reveals the loss of over 1.7 million hectares (4.3 million acres) of primary Amazon forest in our 5 country study area (Bolivia, Brazil, Colombia, Ecuador, and Peru).* That is twice the size of Yellowstone National Park.

Table 1 shows 2019 deforestation (red) in relation to 2018 (orange).

Primary forest loss in the Brazilian Amazon (1.29 million hectares) was over 3.5 times higher than the other four countries combined, with a slight increase in 2019 relative to 2018. Many of these areas were cleared in the first half of the year and then burned in August, generating international attention.

Primary forest loss rose sharply in the Bolivian Amazon (222,834 hectares), largely due to uncontrolled fires escaping into the dry forests of the southern Amazon.

Primary forest loss rose slightly in the Peruvian Amazon (161,625 hectares) despite a relatively successful crackdown on illegal gold mining, pointing to small-scale agriculture (and cattle) as the main driver.

On the positive side, primary forest loss decreased in the Colombian Amazon (91,400 hectares) following a major spike following the 2016 peace accords (between the government and FARC). It is worth noting, however, that we have now documented the loss of 444,000 hectares (over a million acres) of primary forest in the Colombian Amazon in the past four years since the peace agreement (see Annex).

*Two important points about the data. First, we use annual forest loss from the University of Maryland to have a consistent source across all five countries. Second, we applied a filter to only include loss of primary forest (see Methodology).

2019 Deforestation Hotspots Map

The Base Map below shows the major 2019 deforestation hotspots across the Amazon.

2019 deforestation hotspots across the Amazon. Data: Hansen/UMD/Google/USGS/NASA, MAAP.

Many of the major deforestation hotspots were in Brazil. Early in the year, in March, there were uncontrolled fires up north in the state of Roraima. Further south, along the Trans-Amazonian Highway, much of the deforestation occurred in the first half of the year, followed by the high profile fires starting in late July. Note that many of these fires were burning recently deforested areas, and were not uncontrolled forest fires (MAAP #113).

The Brazilian Amazon also experienced escalating gold mining deforestation in indigenous territories (MAAP #116).

Bolivia also had an intense 2019 fire season. Unlike Brazil, many were uncontrolled fires, particularly in the Beni grasslands and Chiquitano dry forests of the southern Bolivian Amazon (MAAP #108).

In Peru, although illegal gold mining deforestation decreased (MAAP #121), small-scale agriculture (including cattle) continues to be a major driver in the central Amazon (MAAP #112) and an emerging driver in the south.

In Colombia, there is an “arc of deforestation” in the northwestern Amazon. This arc includes four protected areas (Tinigua, Chiribiquete and Macarena National Parks, and Nukak National Reserve) and two Indigenous Reserves (Resguardos Indígenas Nukak-Maku and Llanos del Yari-Yaguara II) experiencing substantial deforestation (MAAP #120). One of the main deforestation drivers in the region is conversion to pasture for land grabbing or cattle ranching.

Annex – Colombia peace accord trend

Annex 1. Deforestation of primary forest in the Colombian Amazon, 2015-20. Data: Hansen/UMD/Google/USGS/NASA, UMD/GLAD. *Until May 2020

Methodology

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

For our estimate of primary forest loss, we used the annual “forest cover loss” data with density >30% of the “tree cover” from the year 2001. Then 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).

For boundaries, we used the biogeographical limit (as defined by RAISG) for all countries except Bolivia, where we used the Amazon watershed limit (see Base Map).

All data were processed under the geographical coordinate system WGS 1984. To calculate the areas in metric units, the projection was: Peru and Ecuador UTM 18 South, Bolivia UTM 20 South, Colombia MAGNA-Bogotá, and Brazil Eckert IV.

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

Search Radius: 15000 layer units (meters)
Kernel Density Function: Quartic kernel function
Cell Size in the map: 200 x 200 meters (4 hectares)
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%.

References

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

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

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

Acknowledgements

We thank G. Palacios for helpful comments to earlier versions of this report.

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

Citation

Finer M, Mamani N (2020) 2019 Amazon Deforestation. MAAP: 122.