Agriculture-Related Threat: Cacao

MAAP #183: Protected Areas & Indigenous Territories Effective Against Deforestation Across Amazon

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Base Map. Primary forest loss (2017-21) across the Amazon, in relation to protected areas and indigenous territories.

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: protected areas & indigenous territories.

Our study looked across all nine countries of the Amazon biome, a vast area of 883.7 million hectares (see Base Map).

We calculated primary forest loss over the past 5 years (2017-2021).

For the first time, we were able to distinguish fire vs non-fire forest loss. For non-fire, while this does include natural events (such as landslides and wind storms), we consider this our best proxy for human-caused deforestation.

We analyzed the results across three major land use categories:

1) Protected Areas (national and state/department levels), which cover 197 million hectares (23.6% of Amazon).

2) Indigenous Territories (official), which cover 163.8 million hectares (19.6% of Amazon).

3) Other (all remaining areas outside protected areas and indigenous territories), which cover 473 million hectares (56.7% of Amazon).

In summary, we found that deforestation was the primary driver of forest loss, with fire always being a smaller subset. Averaged across all 5 years, protected areas and indigenous territories had similar levels of effectiveness, reducing primary forest loss rate by 3x compared to areas outside of these designations.

Below, we show the key results across the Amazon in greater detail, including a breakdown for the western Amazon (Bolivia, Colombia, Ecuador, and Peru) and the Brazilian Amazon.

Key Findings

Amazon Biome

We documented the loss of 11 million hectares of primary forests across all nine countries of the Amazon biome between 2017 and 2021. Of this total, 71% was non-fire (deforestation and natural) and 29% was fire.

For the major land use categories, 11% of the forest loss occurred in both protected areas and indigenous territories, respectively, while the remaining 78% occurred outside these designations.

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

Figure 1. Primary forest loss rates across the Amazon, 2017-21.

Broken down by year, 2017 had the highest forest loss rates, with both a severe deforestation and fire season. In addition, 2021 had the second highest deforestation rate, while 2020 had the second highest fire loss rate.

Averaged across all five years, protected areas (green) had the lowest overall primary forest loss rate (0.12%), closely followed by indigenous territories (0.14%).

Interestingly, indigenous territories (orange) actually had a slightly lower deforestation rate compared to protected areas (0.7 vs 0.8%), but higher fire loss rate (o.7 vs .04%), resulting in the overall higher forest loss rate noted above.

Outside of these designations (red), the primary forest loss rate was triple (.36%), especially due to much higher deforestation.

Western Amazon

Breaking the results down specifically for the western Amazon (Bolivia, Colombia, Ecuador, and Peru), we documented the loss of 2.6 million hectares of primary forests between 2017 and 2021. Of this total, 80% was non-fire (deforestation and natural) and 20% was fire.

For the major land use categories, 9.6% occurred in protected areas, 15.6% in indigenous territories, and the remaining 74.8% occurred outside these designations.

Figure 2 displays the standardized primary forest loss rates across the western Amazon.

Figure 2. Primary forest loss rates across the Western Amazon, 2017-21.

Broken down by year, 2017 had the highest deforestation rate and overall forest loss rates. But 2020 had the highest fire loss rate, mainly due to extensive fires in Bolivia. 2021 also had a relatively high deforestation rate. Also, note the high level of fires in protected areas in 2020 and 2021, and indigenous territories in 2019.

Averaged across all five years, protected areas had the lowest overall primary forest loss rate (0.11%), followed by indigenous territories (0.16%).

Outside of these designations, the primary forest loss rate was .30%. That is, triple the protected areas rate and double the indigenous territories rate.

Brazilian Amazon

Breaking the results down specifically for the Brazilian Amazon, we documented the loss of 8.1 million hectares of primary forests between 2017 and 2021. Of this total, 68% was non-fire (deforestation and natural) and 32% was fire.

For the major land use categories, 9.4% occurred in indigenous territories, 11.2% occurred in protected areas, and the remaining 79.4% occurred outside these designations.

Figure 3 displays the standardized primary forest loss rates across the Brazilian Amazon.

Figure 3. Primary forest loss rates in the Brazilian Amazon, 2017-21.

Broken down by year, 2017 had the highest forest loss rate recorded in the entire study (.58%), due to both elevated deforestation and fire. Note that indigenous territories were particularly impacted by fire in 2017.

2020 had the next highest forest loss rate, also driven by an intense fire season. Fires were not as severe the following year in 2021, but deforestation increased.

Averaged across all five years, indigenous territories had the lowest overall primary forest loss rate (0.14%), closely followed by protected areas (0.15%).

Interestingly, indigenous territories had a lower deforestation rate compared to protected areas (0.5 vs 0.11%), but higher fire impact (0.09 vs 0.04%).

Outside of these designations (red), the primary forest loss rate was triple (.45%).

Methodology

To estimate deforestation across all three categories (protected areas, indigenous territories, and other), we used annual forest loss data (2017-21) from the University of Maryland (Global Land Analysis and Discovery GLAD laboratory) to have a consistent source across all countries (Hansen et al 2013).

We obtained this data, which has a 30-meter spatial resolution, from the “Global Forest Loss due to Fires 2000–2021” data download page. It is also possible to visualize and interact with the data on the main Global Forest Change portal.

The annual data is disaggregated into forest loss due to fire vs. non-fire (other disturbance drivers). It is important to note that the non-fire drivers 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). Thus, we often use the term “primary forest loss” to describe this filtered data.

Data presented as primary forest loss rate is standardized per the total area covered of each respective category per year (annual). 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 extends from the Andes to the Amazon plain and reaching the transitions with the Cerrado and the Pantanal. This range includes nine countries of the Amazon (or Pan-Amazon region as defined by RAISG) and consists of a combination of the Amazon watershed limit, the Amazon biogeographic limit and the Legal Amazon limit in Brazil. See Base Map above for delineation of this hybrid Amazon limit, designed for maximum inclusion.

Additional data sources include:

  • National and state/department level protected areas: RUNAP 2020 (Colombia), SNAP 2022 (Ecuador), SERNAP & ACEAA 2020 (Bolivia), SERNANP 2022 (Peru), INPE/Terrabrasilis 2022 (Brazil), SOS Orinoco 2021 (Venezuela), and RAISG 2020 (Guyana, Suriname, and French Guiana.)
  • Indigenous Territories: RAISG & Ecociencia 2022 (Ecuador), INPE/Terrabrasilis 2022 (Brazil), RAISG 2020 (Colombia, Bolivia, Venezuela, Guyana, Suriname, and French Guiana), and MINCU & ACCA 2021 (Peru). For Peru, this includes titled native communities and Indigenous/Territorial Reserves for indigenous groups in voluntary isolation.

For analysis, we categorized Protected Areas first, then Indigenous Territories to avoid overlapping areas. Each category was disaggregated by year created/recognized to match the annual report of forest loss, for example. If a Protected area was created in December 2018, it would be considered within the analysis for the year 2019.

Acknowledgements

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

We thank M. MacDowell and M. Cohen for helpful comments on this report.

Citation

Finer M, Mamani N (2023) Protected Areas & Indigenous Territories Effective Against Deforestation Across Amazon. MAAP: 176.

MAAP #134: Agriculture and Deforestation in the Peruvian Amazon

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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 #128: United Cacao Case – 7 Years After Massive Deforestation in the Peruvian Amazon

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Image 1. The first sign of large-scale deforestation, near the town of Tamshiyacu, in June 2013. Data: Planet (RapidEye). First time published. Click to enlarge.

Here, we confirm the massive deforestation of primary forest (more than 2,000 hectares) in the Peruvian Amazon by the company United Cacao between 2013 and 2016.

We present a series of recently obtained (and never before published) satellite images to emphasize the reality and importance of a deforestation case that is still being debated at the highest levels in the Peruvian government, seven years later.

In June 2013, a high-resolution satellite, through scattered clouds, revealed the start of massive deforestation of primary forest near the town of Tamshiyacu, in the Loreto region (Image 1).

In August of that same year, the clouds cleared a bit more, giving a better view. Image 2 (see below) shows the rapid deforestation of primary forest in 2013.

By September 2015, the deforestation had reached 2,380 hectares, or 5,880 acres (Image 3).

Most recently, in October 2020, a new very high-resolution image shows cacao crops in areas that, seven years ago, were primary forest (Image 4).

Below, we show, for the first time, these high and very-high resolution images (5 and 0.5 meters, respectively) recently obtained from the satellite company Planet, clearly showing the situation from 2012 -2020. Additionally, we show the historical context with Landsat images dating back to 1985, and briefly describe the current political situation regarding the case.

Deforestation 2013

Image 2 shows the first stage of large-scale deforestation (1,100 hectares) by the company United Cacao, between August 2012 (left panel) and August 2013 (right panel).

Image 2. Large-scale deforestation by United Cacao between August 2012 (left panel) and August 2013 (right panel). Data: Planet (RapidEye). First time published. Click to enlarge.

Deforestation 2015

Image 3 shows the total large-scale deforestation (2,380 hectares, or 5,880 acres) by United Cacao between August 2012 (left panel) and September 2015 (right panel). Insets A-C indicate the locations of the zooms below.

Image 3. Large-scale deforestation by United Cacao between August 2012 (left panel) and September 2015 (right panel). Data: Planet (RapidEye). First time published. Click to enlarge.

2020 – Cacao Crops in Deforested Areas

Images 4-6 show current cacao crops (right panel) in areas that, seven years ago, were primary forest (left panel).

Image 4. Current cacao crops (right panel) in areas that, seven years ago, were primary forest (left panel). Data: Planet, Airbus. First time published. Click to enlarge.
Image 5. Current cacao crops (right panel) in areas that, seven years ago, were primary forest (left panel). Data: Planet, Airbus. First time published. Click to enlarge.
Image 6. Current cacao crops (right panel) in areas that, seven years ago, were primary forest (left panel). Data: Planet, Airbus. First time published. Click to enlarge.

Current Policy Situation

In 2014, the Ministry of Agriculture (MINAGRI) ordered United Cacao (Cacao del Perú Norte SAC) to halt its development and production activities, but the company did not comply.

In 2019, MINAGRI rejection the Program for  Adequacy and Environmental Management (PAMA) presented by the company that took over the operation, Tamshi S.A.C. The PAMA is a type of environmental impact evaluation for projects already in operation.

Also in 2019, environmental enforcement of the case was transferred from MINAGRI to the Agency for Environmental Assessment and Enforcement (OEFA).

Most recently, OEFA issued a major fine, equivalent to around $35 million, to the company Tamshi S.A.C. for carrying out activities without having an approved environmental management plan. OEFA also issued 17 corrective measures, one of which was the immediate stoppage of activities.

Acknowledgments

We thank C. Ipenza, A. Felix, C. Noriega, S. Novoa, 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), and EROL Foundation.

Citation

Finer M, Mamani N (2020) United Cacao Case – 7 Years After Massive Deforestation in the Peruvian Amazon. MAAP: 128.

MAAP #127: Mennonite Colonies Continue Major Deforestation in Peruvian Amazon

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Recent deforestation associated with the Mennonite colony Tierra Blanca 1, in Loreto, Peru. Data: Planet

The Mennonites, a religious group often associated with organized agricultural activity, have started three new colonies in the Peruvian Amazon.

We have documented the deforestation of 8,500 acres (3,440 hectares) in these three colonies over the past four years (updated October 2020).

The deforestation started in 2017, but continues to be active in 2020 (with 1,900 acres lost, 25% of the total).

Notably, this combined Mennonite deforestation now exceeds the total loss from the infamous United Cacao case (2,400 hectares), one of the last major controversial large-scale deforestation cases in the Peruvian Amazon (MAAP #27).

Moreover, there are strong indications that the deforestation associated with these three Mennonite colonies is illegal (see Legality Statement below).

Below, we present the following:

  • A Base Map showing the location of the three new Mennonite colonies in the Peruvian Amazon.
  • A series of satellite images showing the recent deforestation in the most active colony (Tierra Blanca 1), including a very high resolution (0.5 meter) Skysat image.
  • a Legality Statement.
  • A graphic showing that the deforested area was not previously cleared (that is, it was intact forest).

 

 

 

 

Base Map. Location of the three new Mennonite Colonies in the Peruvian Amazon. Data: MAAP.

Base Map

The Base Map shows the location of the three new Mennonite colonies in the Peruvian Amazon.

Two colonies are located near the town of Tierra Blanca in the northern Peruvian Amazon (Loreto region).

The other colony is located near the town of Masisea in the central Peruvian Amazon (Ucayali region).

Of the total deforestation (8,500 acres):

  • 63% (5,370 acres) is from the colony Tierra Blanca 1;
  • 25% (2,145 acres) is from the colony Masisea;
  • 12% (990 acres) is from the colony Tierra Blanca 2.

 

 

 

 

 

 

Deforestation 2017-20

The following image shows the total deforestation of 5,370 acres (2,174 hectares) between November 2016 (left panel) and October 2020 (right panel), associated with the Mennonite colony Tierra Blanca 1. The red dot serves as a reference point between the two panels. Click to enlarge.

Deforestation between September 2016 (left panel) and October 2020 (right panel), associated with the Mennonite colony Tierra Blanca 1. Data: Planet, MAAP. Click to enlarge.

Deforestation 2020

The following image shows the most recent deforestation of 1,540 acres (625 hectares) between January 2020 (left panel) and October 2020 (right panel), associated with the Tierra Blanca 1 Mennonite colony. The red lines indicate new 2020 deforestation. Also see the Annex below for a map of the 2020 deforestation in relation to previous 2017-19 deforestation. Click to enlarge.

Deforestation between January 2020 (left panel) and October 2020 (right panel), associated with the Mennonite colony Tierra Blanca 1. Data: Planet, MAAP. Click to enlarge.

Very High Resolution Satellite Image (Skysat)

We recently obtained a very high resolution (0.5 meter) satellite image of the Tierra Blanca 1 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.

Very high resolution satellite image (0.5 meters) over the Tierra Blanca 1 colony. Data: Planet (Skysat). Click to enlarge.

Legality Statement

Regarding the findings in Loreto (Tierra Blanca), we consulted with the Regional Government of Loreto who, in a document dated October 15, 2020, indicated that the Mennonite colonies do not have any approvals for the large-scale forest clearing in the area. The documented also indicated that they were coordinating with the environmental prosecutor’s office (known as FEMA) to investigate the case and its environmental impact.

Regarding the findings in Ucayali (Massisea), our investigations revealed that there is an investigation in progress by the environmental prosecutor’s office (FEMA). In addition, the regional government has initiated a sanctioning procedure for the alleged unauthorized land use change (deforestation) associated with Mennonite colony near Masisea.

Annex

We present a time series of satellite images ranging from 1985 to 2020 that shows that the major deforestation in the area began with the Mennonite intervention.

Annex. Deforestation in 2020 in relation to 2017-19, associated with Mennonite colony Tierra Blanca 1. Data: MAAP.

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, Suarez D (2020) MAAP: Mennonite Colonies Continue Major Deforestation in Peruvian Amazon Peruana. MAAP: 27.

MAAP Synthesis #3: Deforestation in the Andean Amazon (Trends, Hotspots, Drivers)

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Satellite image of the deforestation produced by United Cacao. Source: DigitalGlobe (Nextview)

MAAP, an initiative of the organization Amazon Conservation, uses cutting-edge satellite technology to monitor deforestation in near real-time in the megadiverse Andean Amazon (Peru, Colombia, Ecuador, and Bolivia).

The monitoring is based on 5 satellite systems: Landsat (NASA/USGS), Sentinel (European Space Agency), PeruSAT-1, and the companies Planet and DigitalGlobe. For more information about our innovative methodology, see this recent paper in Science Magazine.

Launched in 2015, MAAP has published nearly 100 high-impact reports on the major Amazonian deforestation issues of the day.

Here, we present our third annual synthesis report with the objective to concisely describe the bigger picture: Deforestation trends, patterns, hotspots and drivers across the Andean Amazon.

Our principal findings include:

Trends: Deforestation across the Andean Amazon has reached 4.2 million hectares (10.4 million acres) since 2001. Annual deforestation has been increasing in recent years, with a peak in 2017 (426,000 hectares). Peru has had the highest annual deforestation, followed by surging Colombia (in fact, Colombia surpassed Peru in 2017). The vast majority of the deforestation events are small-scale (‹5 hectares).

Hotspots: We present the first regional-scale deforestation hotspots map for the Andean Amazon, allowing for spatial comparisons between Peru, Colombia, and Ecuador.  We discuss six of the most important hotspots.

Drivers: We present MAAP Interactive, a dynamic map with detailed information on the major deforestation drivers: gold mining, agriculture (oil palm and cacao), cattle ranching, logging, and dams. Agriculture and ranching cause the most widespread impact across the region, while gold mining is most intense southern Peru.

Climate Change. We estimated the loss of 59 million metric tons of carbon in the Peruvian Amazon during the last five years (2013-17) due to forest loss. In contrast, we also show that protected areas and indigenous lands have safeguarded 3.17 billion metric tons of carbon.

I. Deforestation Trends

Image 1 shows forest loss trends in the Andean Amazon between 2001 and 2017.*  The left graph shows data by country, while the right graph shows data by forest loss event size.

Image 1. Annual forest loss by country and size. Data: Hansen/UMD/Google/USGS/NASA, UMD/GLAD, Global Forest Watch, MINAM/PNCB, RAISG.

Trends by Country

Over the past 17 years (2001-2017), deforestation has surpassed 4.2 million hectares (10.4 million acres) in the Andean Amazon (see green line). Of this total, 50% is Peru (2.1 million hectares/5.2 million acres), 41% Colombia (1.7 million hectares/4.27 million acres), and 9% Ecuador (887,000 acres/359,000 hectares). This analysis did not include Bolivia.

Since 2007, there has been an increasing deforestation trend, peaking during the past two years (2016-17). In fact, 2017 has the highest annual forest loss on record with 426,000 hectares (over one million acres), more than double the total forest loss in 2006.

Peru had the highest average annual Amazonian deforestation between 2009 and 2016. The past four years have the highest annual deforestation totals on record in the country, with peaks in 2014 (177,566 hectares/439,000 acres) and 2016 (164,662 hectares/406,888 acres). According to new data from the Peruvian Environment Ministry, there was an important decline in 2017 (155,914 hectares/385,272 acres), but it is still the fourth highest annual total on record.

There has been a surge of deforestation in Colombia during the past two years. Note that in 2017, Colombia surpassed Peru with a record high of 214,700 hectares (530,400 acres) deforested.

Deforestation is also increasing in Ecuador, with highs of 32,000 hectares (79,000 acres) in 2016 and 55,500 hectares (137,000) acres in 2017.

For context, Brazil has had an average deforestation loss rate of 639,403 hectares (1.58 million acres) over the past several years.

* Data: Colombia & Ecuador: Hansen/UMD/Google/USGS/NASA; Peru: MINAM/PNCB, UMD/GLAD. While this information includes natural forest loss events, it serves as our best estimate of deforestation resulting from anthropogenic causes.  It is estimated that the non-anthropic loss comprises approximately 3.5% of the total loss. Note that the analysis does not include Bolivia.

Trends by Size

The pattern related to the size of deforestation events in the Andean Amazon remained relatively consistent over the last 17 years. Most noteworthy: the vast majority (74%) of the deforestation events are small-scale (‹5 hectares). Only 2% of deforestation events are large-scale (>100 hectares). The remaining 24% are medium-scale (5-100 hectares).

These results are important for conservation efforts.  Addressing this complex situation – in which most of the deforestation events are small-scale – requires significantly more attention and resources.  In addition, while large-scale deforestation (usually associated with agro-industrial practices) is not that common, it nonetheless represents a serious latent threat, due to the fact that only a small number of agro-industrial projects (for example, oil palm) are able to rapidly destroy thousands of acres of primary forest.

II. Deforestation Hotspots

Image 2: Deforestation hotspots 2015-2017. Data: Hansen/UMD/Google/USGS/NASA.

We present the first regional-scale deforestation hotspots map across the Andean Amazon (Colombia, Ecuador, Peru).  Image 2 shows the results for the past three, 2015 – 2017.

The most critical zones (“high” deforestation density) are indicated in red. They include:

A. Central Peruvian Amazon: Over the last 10 years, this zone, located in the Ucayali and Huánuco regions, has consistently had one of the largest concentrations of deforestation in Peru (Inset A).  Its principal drivers include oil palm and cattle grazing.

B. Southern Peruvian Amazon: This zone, located in the Madre de Dios region, is impacted by gold mining (Inset B1), and increasingly by small- and medium-scale agriculture along the Interoceanic Highway (Inset B2).

C. Central Peruvian Amazon: A new oil palm plantation located in the San Martín region has been identified as a recent large-scale deforestation event in this zone (Inset C).

D. Southwestern Colombian Amazon: Cattle grazing is the principal deforestation driver documented in this zone, located in the departments of Caquetá and Putumayo (Inset D).

E. Northern Colombian Amazon: There is expanding deforestation along a new road in this zone, located in the department of Guaviare (Inset E).

F. Northern Ecuadoran Amazon: This zone is located in the Orellana province, where small- and medium-scale agriculture, including oil palm, is the principal driver of deforestation (Inset F).

 

 

III. Drivers of Deforestation     

MAAP Interactive (screenshot)

One of the main objectives of MAAP is to improve the availability of precise and up-to-date information regarding the current drivers (causes) of deforestation in the Andean Amazon.  Indeed, one of our most important advances has been the use of high-resolution imagery to identify current deforestation drivers.

In order to improve the analysis and understanding of the identified drivers, we have created an Interactive Map that displays the spatial location of each driver associated with every MAAP report.  An important characteristic of this map is the ability to filter the data by driver, by selecting the boxes of interest.

Image 3 shows a screenshot of the Interactive Map.  Note that it contains detailed information on these principal drivers: gold mining, oil palm, cacao, small-scale agriculture, cattle pasture, logging roads, and dams.  It also includes natural causes such as floods, forest fires, and blowdowns.  In addition, it highlights deforestation events in protected areas.

Below, we discuss the principal drivers of deforestation and degradation in greater detail.

 

 

 

 

Agriculture – oil palm, cacao, and other crops

Image 4: Interactive Map, agriculture. Data: MAAP.

Image 4 shows the results of the interactive map when applying the agriculture-related filters.

Legend:
Oil palm (bright green)
Cacao (brown)
Other crops (dark green)

Agricultural activity is one of the principal causes of deforestation in the Andean Amazon.

The majority of agriculture-related deforestation is caused by small- and medium-scale plantations (‹50 hectares).

Deforestation for large-scale, agro-industrial plantations is much less common, but represents a critical latent threat.

 

 

 

 

 

Large-scale Agriculture

We have documented five major deforestation events produced by large-scale plantations since 2007:  four of these occurred in Peru (three of which are related to oil palm and one to cacao) and one in Bolivia (resulting from sugar cane plantations).

First, between 2007 and 2011, two large-scale oil palm plantations caused the deforestation of 7,000 hectares on the border between Loreto and San Martín (MAAP #16).  Subsequent plantations in the surrounding area caused the additional deforestation of 9,800 hectares.

It is importnat to note that the Peruvian company Grupo Palmas is now working towards a zero deforestation value chain and has a new sustainability policy (see Case C of MAAP #64).

Next, between 2012 and 2015, two other large-scale oil palm plantations deforested 12,000 hectares in Ucayali  (MAAP #4, MAAP #41).

Between 2013 and 2015, the company United Cacao deforested 2,380 hectares for cacao plantations in Loreto (MAAP #9, MAAP #13, MAAP #27, MAAP #35).

Deforestation from large-scale agriculture decreased in Peru between 2016 and 2017, but there was one notable event: an oil palm plantation of 740 hectares in San Martín (MAAP #78).

Another notable case of deforestation related to large-scale agriculture has been occurring in Bolivia, where a new sugarcane plantation has caused the deforestation of more than 2,500 hectares in the department of La Paz.

Additionally, we found three new zones in Peru characterized by the deforestation pattern produced by the construction of organized access roads which have the potential of becoming large-scale agriculture areas (MAAP #69).

Small and Medium-scale Agriculture

Deforestation caused by small- and medium-scale agriculture is much more widespread, but it is often difficult to identify the driver from satellite imagery.

We have identified some specific cases of oil palm in Huánuco, Ucayali, Loreto, and San Martín (MAAP #48, MAAP #26, MAAP #16).

Cacao and papaya are emerging drivers in Madre de Dios.  We have documented cacao deforestation along the Las Piedras River (MAAP #23, MAAP #40) and papaya along the Interoceanic Highway (MAAP #42).

Corn and rice cultivation appear to be turning the area around the town of Iberia into a deforestation hotspot (MAAP #28).  In other cases, we have documented deforestation resulting from small- and medium-scale agriculture, though it has not been possible to identify the type of crop (MAAP #75, MAAP #78).

Additionally, small-scale agriculture is possibly a determining factor in the forest fires that degrade the Amazon during the dry season (MAAP #45, MAAP #47).

The cultivation of illicit coca is a cause of deforestation in some areas of Peru and Colombia.  For example, in southern Peru, the cultivation of coca is generating deforestation within the Bahuaja Sonene National Park and its surrounding areas.

Cattle Ranching

Image 5: Interactive Map, cattle ranching. Data: MAAP.

By analyzing high-resolution satellite imagery, we have developed a methodology for identifying areas deforestated by cattle ranching.*

Image 5 shows the results of the Interactive Map when applying the “Cattle pasture” filter, indicating the documented examples in Peru and Colombia.

Legend:
Cattle ranching (orange)

Cattle ranching is the principal driver of deforestation in the central Peruvian Amazon (MAAP #26, MAAP #37, MAAP #45, MAAP #78). We also identified recent deforestation from cattle ranching in northeastern Peru (MAAP #78).

In the Colombian Amazon, cattle ranching is one the primary direct drivers in the country’s most intense deforestation hotspots (MAAP #63, MAAP #77).

* Immediately following a major deforestation event, the landscape of felled trees is similar for both agriculture and cattle pasture.  However, by studying an archive of images and going back in time to analyze older deforestation cases, it is possible to distinguish between the drivers.  For example, after one or two years, agriculture and cattle pasture appear very different in the images. Ther former tends to have organized rows of new plantings, while the latter is mostly grassland.

 

 

 

Gold Mining

Image 6: Interactive Map, gold mining. Data: MAAP.

Image 6 shows the results of the Interactive Map when applying the “Gold mining” filter.

Legend:
Gold Mining (yellow)
*With dot indicates within protected area

The area that has been most impacted by gold mining is clearly the southern Peruvian Amazon, where we estimate the total deforestation of more than 63,800 hectares. Of this, at least 7,000 hectares have been lost since 2013.  The two most critical zones are La Pampa and Alto Malinowski in Madre de Dios (MAAP #87, MAAP #75, MAAP #79).  Another critical area exists in Cusco in the buffer zone of the Amarakaeri Communal Reserve, where mining deforestation is now less than one kilometer from the boundary of the protected area (MAAP #71).

It is important to highlight two important cases in which the Peruvian government has taken effective actions to halt illegal mining within protected areas (MAAP #64).  In September 2015, illegal miners invaded Tambopata National Reserve and deforested 550 hectares over the course of a two-year period.  At the end of 2016, the government intensified its interventions and the invasion was halted in 2017. In regards to Amarakaeri Communal Reserve, in June 2015 we revealed the mining invasion deforestation of 11 hectares.  Over the course of the following weeks, SERNANP and ECA Amarakaeri implemented measures and rapidly halted the illegal activity.

Other small gold-mining fronts are emerging in the northern and central Peruvian Amazon (MAAP #45, MAAP #49).

In addition, we have also documented deforestation linked to illegal gold-mining activities in the Puinawai National Park in the Colombian Amazon.

Logging

Image 7: Interactive Map, logging roads. Data: MAAP.

In MAAP #85 we proposed a new tool to address illegal logging in the Peruvian Amazon: utilize satellite imagery to monitor construction of logging roads in near real-time.

Image 7 shows the results of the Interactive Map when applying the “Logging roads” filter.

Legend:
Logging Road (purple)

We estimate that 2,200 kilometers of forest roads have been constructed in the Peruvian Amazon during the last three years (2015-2017).  The roads are concentrated in southern Loreto, Ucayali, and northwestern Madre de Dios.

 

 

 

 

 

 

Roads

Image 8: Interactive map, roads. Data: MAAP.

It has been well-documented that roads are one of the most important drivers of deforestation in the Amazon, particularly due to the fact that they facilitate human access and activities related to agriculture, cattle ranching, mining, and logging.

Image 8 shows the results of the Interactive Map when applying the “Roads” filter.

Legend:
Road (gray)

We have analyzed two controversial proposed roads in Madre de Dios, Peru.

The Nuevo Edén – Boca Manu – Boca Colorado road would traverse the buffer zone of two protected areas: Amarakaeri Communal Reserve and Manu National Park (MAAP #29).

The other, the Puerto Esperanza-Iñapari road, would traverse the Purús National Park and threaten the territory of the indigenous peoples in voluntary isolation who live in this remote area (MAAP #76).

 

 

 

 

Hydroelectric dams

Image 9 shows the results of the Interactive Map when applying the “Dams” filter.

Legend:
Hydroelectric Dam (light blue)

To date, we have analyzed three hydroelectric dams located in Brazil.  We have documented the loss of 36,100 hectares of forest associated with flooding produced by two dams (San Antonio and Jirau) on the Madeira River near the border with Bolivia (MAAP #34).  We also analyzed the controversial Belo Monte hydroelectrical complex located on the Xingú River, adn estimate that 19,880 hectares of land have been flooded. According to the imagery, this land is a combination of forested areas and agricultural areas (MAAP #66).

Additionally, we show a very high-resolution image of the exact location of the proposed Chadín-2 hydroelectric dam on the Marañón River in Peru (MAAP #80).

Hydrocarbon (oil and gas)

Image 10: Interactive map, hidrocarbon. Data: MAAP.

Image 10 shows the results of the Interactive Map when applying the “Hydrocarbon“ filter.

Legend:
Hydrocarbon (black)

Our first report on this sector focused on Yasuní National Park in the Ecuadorian Amazon.  We documented the direct and indirect deforestation amounts of 417 hectares (MAAP #82).

We also show the location of recent deforestation in two hydrocarbon block in Peru: Block 67 in the north and Blocks 57 in the south.

 

 

 

 

 

 

 

Climate Change

Tropical forests, especially the Amazon, sequester huge amounts of carbon, one of the main greenhouse gases driving climate change.

In MAAP #81, we estimated the loss of 59 million metric tons of carbon in the Peruian Amazon during the last five years (2013-17) due to forest loss, especially deforestation from mining and agricultural activities. This finding reveals that forest loss represents nearly half (47%) of Peru’s annual carbon emissions, including from burning fossil fuels.

In contrast, in MAAP #83 we show that protected areas and indigenous lands have safeguarded 3.17 billion metric tons of carbon, as of 2017. That is the equivalent to 2.5 years of carbon emissions from the United States.

The breakdown of results are:
1.85 billion tons safeguarded in the Peruvian national protected areas system;
1.15 billion tons safeguarded in titled native community lands; and
309.7 million tons safeguarded in Territorial Reserves for indigenous peoples in voluntary isolation.

Citation

Finer M, Mamani N (2018) Deforestation in the Andean Amazon (Trends, Hotspots, Drivers). MAAP Synthesis #3.

MAAP #75: Pope to visit Madre de Dios, region with Deforestation Crisis (Peru)

Posted on by dcadmin
Table 76. Data: PNBC/MINAM (2001-16), UMD/GLAD (2017, until the first week of November).

Pope Francis, as part of his upcoming visit to Peru in January, will visit the Madre de Dios region in the southern Peruvian Amazon. He is expected to address issues facing the Amazon and its indigenous communities, including deforestation.

In this article, we show that Madre de Dios is experiencing a deforestation crisis, due mainly to impacts from gold mining, small-scale agriculture, and roads.

Table 76 shows the increasing trend of annual forest loss since 2001, peaking in 2017. In fact, in 2017 forest loss exceeded 20,000 hectares (49,000 acres) for the first time, doubling the loss in 2008.*

The table also shows the ranking of Madre de Dios in respect to the annual forest loss compared to all other regions of the Peruvian Amazon (see red line). For the first time, Madre de Dios is the region with the second highest forest loss total, behind only Ucayali.

Next, we present a map of deforestation hotspots in Madre de Dios in 2017, along with satellite images of a number of the most intense hotspots.

*The total estimated forest loss in 2017 was based on early warnings alerts generated by the University of Maryland (GLAD alerts) and the Peruvian Environment Ministry (PNCB/MINAM). The estimate is 20,826 hectares as of the first week of November.

Deforestation Hotspots in Madre de Dios

Image 76 shows a map of deforestation hotspots in Madre de Dios in 2017, based on early warning forest loss data. The colors yellow (low), orange (medium/high), and red (very high) correspond to the areas with the highest concentration of alerts, i.e. the main deforestation hotspots of 2017. Note how the majority of the forest loss is concentrated along the recently paved Interoceanic highway.

Next, we show satellite imagery for 7 hotspots (Insets A-G) that together account for the deforestation of 6,000 hectares (15,000 acres). We show that the main deforestation drivers are gold mining and small-scale agriculture.

Image 76. Base Map of Hotspots in Madre de Dios in 2017. Data: PNBC/MINAM, UMD/GLAD

La Pampa (Inset A)

The area known as La Pampa continues to experience significant deforestation due to the advance of gold mining. Despite a series of field interventions by the Peruvian Government, we documented the deforestation of 1,385 acres (560 hectares) in 2017 (Image 76a). Since 2013, the total deforestation in La Pampa is 11,270 acres (4,560 hectares).

Image 76a. Data: Planet

Upper Malinowski (Inset B)

Upstream of La Pampa, the headwaters of the Malinowski River represent a second area devastated by the recent advance of gold mining. We documented the deforestation of 1,795 acres (726 hectares) in 2017 along the upper Malinowski (Image 76b). Since 2015, the total deforestation along the upper Malinowski is 5,260 acres (2,130 hectares).

Image 76b. Data: Planet

Santa Rita and Guacamayo (Insets C y D)

To the north of the La Pampa and Upper Malinowski mining areas, and on the other side of the Interoceanic highway, are two areas with significant recent deforestation due to small-scale agriculture. In these two areas, we documented the deforestation of 2,890 acres (1,170 hectares) in 2017 (Images 76c, 76d). Additional research focused on the exact type of crops is required, but local sources indicate an increase in papaya and cacao in the area.

Image 76c. Data: Planet, ESA
Image 76d. Data: Planet

Iberia (Inset E)

On the other side of Madre de Dios, along the Interoceanic Highway near the border with Brazil and Bolivia, is the town of Iberia. This area has become a major deforestation hotspot in recent years. We documented the deforestation of 2,250 acres (910 hectares) in 2017 (Image 76e). Since 2014, the total deforestation around Iberia is 6,795 acres (2,750) hectares. A large part of the deforestation is within forestry concessions, indicating that these concessions have been invaded. The cause of the deforestation is small-scale agriculture (specifically, according to local sources, corn, papaya, and cacao).

Image 76e. Data: Planet

Tahuamanu (Inset F)

To the west of Iberia, an isolated hotspot emerged caused by the rapid proliferation of logging roads. This hotspot is located within a forestry concession, but its impact is troubling due to the extension and density of the new road network. We estimate the construction of 130 km of new logging forest roads in this area in 2017 (Image 76f).

Image 76f. Data: Planet

Las Piedras (Inset G)

Finally, deforestation continues within two ecotourism concessions along the Las Piedras River, a remote area famous for its exceptional wildlife (see this video). We documented the deforestation of 300 acres (134 hectares) in 2017 (Image 76g). Since 2013, the total deforestation along the Las Piedras River is 1,495 acres (605 hectares). Note that the Las Piedras Amazon Center Ecotourism Concession represents an effective barrier against deforestation impacting the surrounding concessions. According to local sources, the main causes of deforestation are cacao plantations and cattle pasture.

Image 76g. Data: Planet

Coordinates

Zona A: -12.99, -69.90
Zona B: -13.05, -70.17
Zona C: -12.85, -70.26
Zona D: -12.84, -69.99
Zona E: -11.31, -69.61
Zona F: -11.23, -70.05
Zona G: -11.601711, -70.477295

References

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

Citation

Finer M, Novoa S, Garcia R (2017) Pope to visit Madre de Dios (Peru), region with Deforestation Crisis. MAAP: 75.

MAAP Interactive: Deforestation Drivers in the Andean Amazon

Posted on by dcadmin

Since its launch in April 2015, MAAP has published over 70 reports related to deforestation (and natural forest loss) in the Andean Amazon. We have thus far focused on Peru, with several reports in Colombia and Brazil as well.

These reports are meant to be case studies of the most important and urgent deforestation events. We often use forest loss alerts (known as GLAD) to guide us, and satellite imagery (from Planet and DigitalGlobe) to identify the deforestation driver.

Here we present an interactive map highlighting the drivers identified in all published MAAP reports. These drivers include gold mining, agriculture (e.g. oil palm and cacao), cattle pasture, roads, and dams (see icon legend below map). We also include natural causes such as floods and blowdowns (fire included under agriculture since most human caused). Furthermore, we highlight deforestation events within protected areas. Note that you can filter by driver by checking boxes of interest.

We hope the result is one of the most detailed and up-todate resources on patterns and drivers of deforestation in the Andean Amazon. Over the coming year we will continue to focus on Peru and Colombia, and begin to include Ecuador and Bolivia as well.

To view the interactive map, please visit:

MAAP Interactive: Deforestation Drivers in the Andean Amazon
https://www.maaproject.org/interactive/

For more information on patterns and drivers of deforestation in the Peruvian Amazon, see our latest Synthesis report 

MAAP #64: Good News Deforestation Stories (Peruvian Amazon)

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We admit that most MAAP stories are about the bad news of Amazon deforestation. But fortunately there is good news as well.

Here we highlight 5 good news stories from the Peruvian Amazon that show how near real-time monitoring may lead to halting deforestation from emerging threats, such as gold mining and large-scale agriculture (oil palm and cacao plantations).

The detailed cases are:
A) United Cacao (cacao),
B) Plantations of Pucallpa (oil palm),
C) Grupo Romero (oil palm),
D) Amarakaeri Comunal Reserve (gold mining), and
E) Tambopata National Reserve (gold mining).

 

 

 

United Cacao

Image 64a. Data: NASA/USGS

The rapid deforestation of primary forest for a large-scale cacao plantation in the northern Peruvian Amazon took everyone by surprise in 2013. Civil society led the way in exposing and tracking the deforestation with satellite imagery and the government eventually confirmed the forest loss data. For its part, MAAP published 6 articles (for example MAAP #35 and MAAP #2).

Although total deforestation eventually reached 5,880 acres (2,380 hectares), the company, due to a complicated combination of factors, was suspended from the London Stock Exchange and no new deforestation has been detected in over a year.

Image 64a shows that the cacao project area was covered by intact forest in late 2012, followed by large-scale deforestation of primary forest in 2013. The deforestation slowed, and then stopped, between 2014 and 2017. The yellow circle indicates the cacao plantation area over time.

Plantations of Pucallpa (oil palm)

In a remarkable case, satellite imagery was used to demonstrate that an oil palm company (Plantations of Pucallpa) had breached the Code and Conduct of the RSPO (Roundtable on Sustainable Palm Oil), a non-profit entity founded to develop and implement global standards for sustainable palm oil.

In 2015, the Native Community of Santa Clara de Uchunya (with the support of the NGO Forest Peoples Programme) presented an official complaint to the RSPO against Plantations of Pucallpa, a member of the roundtable. An important component of the complaint alleged massive deforestation, but the company adamantly denied it. MAAP articles showing the deforestation of 15,970 acres (6,460 hectares) were used as evidence (MAAP #4, MAAP #41), as was independent government analysis.

In April 2017, the RSPO concluded that Plantations of Pucallpa cleared 14,145 acres (5,725 hectares) despite declaring no land-clearing, thus breaching the Code and Conduct. Several months prior this decision, the company divested its oil palm estates and withdrew from the RSPO. We have not detected any new deforestation in the project area in over a year.

Image 64b shows the massive deforestation for two large-scale oil palm plantations in the central Peruvian Amazon (Plantations of Pucallpa is the plantation to the north). The yellow circles indicate the oil palm plantation project areas over time. Note that the project area was a mix of primary and secondary forest in 2011, immediately prior to the deforestation, which began in 2012. The deforestation intensified in 2013 before nearly reaching its maximum extent in 2015. We have not detected any new deforestation since 2016.

Image 64b. Data: NASA/USGS, MAAP

Grupo Romero (oil palm)

Perhaps the best news of the bunch is about four large-scale oil palm plantations that were stopped before any deforestation occurred. As detailed in a recent report by Environmental Investigation Agency, the Peruvian business conglomerate Grupo Romero conducted environmental impact studies for four new oil palm plantations in the northern Peruvian Amazon. Analysis of these studies revealed that these plantations would cause the massive deforestation of 56,830 acres (23,000 hectares) of primary forest. After strong pushback from civil society, including legal action, a recent report from Chain Reaction Research revealed that Grupo Romero is now working towards a zero-deforestation supply chain and thus found that the four planned plantations are no longer feasible and abandoned the projects.

Image 64c shows how the project area for two of the proposed oil palm plantations (in yellow), Santa Catalina and Tierra Blanca, is largely covered by intact, primary forest.

Image 64c. Data: NASA/USGS, Grupo Palmas (Grupo Romero)

Amarakaeri Communal Reserve (gold mining)

In June 2015, we revealed the deforestation of 11 hectares in Amarakaeri Communal Reserve due to an illegal gold mining invasion. The Reserve, located in the southern Peruvian Amazon, is an important protected area that is co-managed by indigenous communities (ECA Amarakaeri) and SERNANP, Peru’s protected areas agency (see MAAP #6). In the following weeks, the Peruvian government, led by SERNANP, cracked down on the illegal mining activities. A year later, we showed that the deforestation had been stopped, with no further expansion into the Reserve (MAAP #44). In fact, we showed that there were signs of recovering vegetation on the recently mined areas.

Image 64d shows the gold mining deforestation approaching (2011-12) and entering (2013-15) Amarakaeri Communal Reserve (yellow circles indicate areas of invasion). However, it also shows how, following action by the government and ECA Amarakaeri, the deforestation was halted and did not expand in 2016-17.

Image 64d. Data: NASA/USGS, Sentinel/ESA, RapidEye/Planet

Tambopata National Reserve (gold mining)

In September 2015, illegal gold miners started to invade Tambopata National Reserve, an important protected area in the southern Peruvian Amazon with world renowned biodiversity. In a series of MAAP articles, we tracked the invasion as it intensified in 2016, and eventually reached 1,360 acres (550 hectares) by early 2017. However, by late 2016, the Peruvian Government intensified its interventions against the illegal mining activity, and the rate of deforestation quickly and sharply decreased. In the most recent satellite imagery, we have not detected any major new expansion of illegal gold mining within the Reserve.

Image 64e shows the initial invasion of Tambopata National Reserve between September 2015 and January 2016. The deforestation within the Reserve intensifies during 2016, but slows significantly in 2017. The yellow circles indicate areas of invasion.

Image 64e. Data: Planet, SERNANP

References

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

Citation

Finer M, Novoa S, Olexy T, Scott A (2017) Good News Deforestation Stories (Peruvian Amazon). MAAP: 64.

MAAP SYNTHESIS #2: PATTERNS AND DRIVERS OF DEFORESTATION IN THE PERUVIAN AMAZON

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We present our second synthesis report, building off our first report published in September 2015. This synthesis is largely based on the 50 MAAP reports published between April 2015 and November 2016. The objective is to synthesize all the information to date regarding deforestation trends, patterns and drivers in the Peruvian Amazon.

MAAP methodology includes 4 major components: Forest loss detection, Prioritize big data, Identify deforestation drivers, and Publish user-friendly reports. See Methodology section below for more details.

Our major findings include:

  • Trends. During the 15 years between 2001 and 2015, around 4,448,000 acres (1,800,000 hectares) of Peruvian Amazon forest has been cleared, with a steadily increasing trend. 2014 had the highest annual forest loss on record (438,775 acres), followed by a slight decrease  in 2015. The preliminary estimate for 2016 indicates that forest loss remains relatively high. The vast majority (80%) of forest loss events in the Peruvian Amazon are small-scale (<5 hectares), while large-scale events (> 50 hectares) pose a latent threat due to new agro-industrial projects.
  • Hotspots. We have identified at least 8 major deforestation hotspots. The most intense hotspots are located in the central Amazon (Huánuco and Ucayali). Other important hotspots are located in Madre de Dios and San Martin. Two protected areas (Tambopata National Reserve and El Sira Communal Reserve) are threatened by these hotspots.
  • Drivers. We present an initial deforestation drivers map for the Peruvian Amazon. Analyzing high-resolution satellite imagery, we have documented six major drivers of deforestation and degradation: small/medium-scale agriculture, large-scale agriculture, cattle pasture, gold mining, illegal coca cultivation, and roads. Small-scale agriculture and cattle pasture are likely the most dominant drivers overall. Gold mining is a major driver in southern Peru. Large-scale agriculture and major new roads are latent threats. Logging roads are likely a major source of forest degradation in central Peru.

Deforestation Trends

Image 1 shows forest loss trends in the Peruvian Amazon from 2001 to 2015, including a breakdown of the size of the forest loss events. This includes the official data from the Peruvian Environment Ministry, except for 2016, which is a preliminary estimate based on GLAD forest loss alerts.

Image 1. Data: PNCB/MINAM, UMD/GLAD. *Estimate based on GLAD alerts.

During the 15 years between 2001 and 2015, around 4,448,000 acres (1,800,000 hectares) of Peruvian Amazon forest has been cleared (see green line). This represents a loss of approximately 2.5% of the existing forest as of 2001.There have been peaks in 2005, 2009, and 2014, with an overall increasing trend. In fact, 2014 had the highest annual forest loss on record (386,626 acres). Forest loss decreased in 2015 (386,732 acres), but is still the second highest recorded. The preliminary estimate for 2016 indicates that forest loss continues to be relatively high.

It is important to note that the data include natural forest loss events (such as storms, landslides, and river meanders), but overall serves as our best proxy for anthropogenic deforestation. The non-anthropogenic forest loss is estimated to be approximately 3.5% of the total.1

The vast majority (81%) of forest loss events in the Peruvian Amazon are small-scale (<5 hectares, equivalent of 12 acres), see the yellow line. Around 16% of the forest loss events are medium-scale (5-50 hectares, equivalent of 12-124 acres), see the orange line. Large-scale (>50 hectares, equivalent of 124 acres) forest loss events, often associated with industrial agriculture, pose a latent threat. Although the average is only 2%, large-scale forest loss rapidly spiked to 8% in 2013 due to activities linked with a pair of new oil palm and cacao plantations. See MAAP #32 for more details on the patterns of sizes of deforestation events.

Deforestation Patterns

Image 2 shows the major deforestation hotspots in 2012-14 (left panel) relative to 2015-16 (right panel), based on a kernel density analysis.2 We have identified at least 8 major deforestation hotspots, labeled as Hotspots A-H.

Image 2. Data: PNCB/MINAM, GLAD/UMD. Click to enlarge.

The most intense hotspots, A and B, are located in the central Amazon. Hotspot A, in northwest Ucayali, was dominated by two large-scale oil palm projects in 2012-14, but then shifted a bit to the west in 2015-16, where it was dominated by cattle pasture and small-scale oil palm. Hotspot B, in eastern Huánuco, is dominated by cattle pasture (MAAP #26).

Hotspots C and D are in the Madre de Dios region in the southern Amazon. Hotspot C indicates the primary illegal gold mining front in recent years (MAAP #50). Hotspot D highlights the emerging deforestation zone along the Interoceanic Highway, particularly around the town of Iberia (MAAP #28).

Hotspots E-H are agriculture related. Hotspot E indicates the rapid deforestation for a large-scale cacao plantation in 2013-14, with a sharp decrease in forest loss 2015-16 (MAAP #35). Hotspot F indicates the expanding deforestation around two large-scale oil palm plantation (MAAP #41). Hotspot G indicates the intensifying deforestation for small-scale oil palm plantations (MAAP #48).

Hotspot H indicates an area impacted by intense wildfires in 2016.

Protected Areas, in general, are effective barriers against deforestation (MAAP #11). However, several protected areas are currently threatened, most notably Tambopata National Reserve (Hotspot C; MAAP #46). and El Sira Communal Reserve (Hotspot B; MAAP #45).

Deforestation Drivers

Image 3. Data: MAAP, SERNANP. Click to enlarge.

Surprisingly, there is a striking lack of precise information about the actual drivers of deforestation in the Peruvian Amazon. According to an important paper published in 2016, much of the existing information is vague and outdated, and is based solely on a general analysis of the size of deforestation events.3  

As noted above, one of the major advances of MAAP has been using high-resolution imagery to better identify deforestation drivers.

Image 3 shows the major deforestation drivers identified thus far by our analysis. As far as we know, it represents the first spatially explicit deforestation drivers map for the Peruvian Amazon.

To date, we have documented six major direct drivers of deforestation and degradation in the Peruvian Amazon: small/medium-scale agriculture, large-scale agriculture, cattle pasture, gold mining, illegal coca cultivation, and roads.

At the moment, we do not consider the hydrocarbon (oil and gas) and hydroelectric dam sectors as major drivers in Peru, but this could change in the future if proposed projects move forward.

We describe these major drivers of deforestation and degradation in greater detail below.

Small/Medium-scale Agriculture

The literature emphasizes that small-scale agriculture is the leading cause of deforestation in the Peruvian Amazon.1 However, there is little actual empirical evidence demonstrating that this is true.3 The raw deforestation data is dominated by small-scale clearings that are most likely for agriculture or cattle pasture. Thus, it is likely that small-scale agriculture is a major driver, but a definitive study utilizing high-resolution imagery and/or extensive field work is still needed to verify the assumption.

In several key case studies, we have shown specific examples of small-scale agriculture being a deforestation driver. For example, using a combination of high-resolution imagery, photos from the field, and local sources, we have determined that:

  • Oil Palm, in the form of small and medium-scale plantations, is one of the main drivers within deforestation Hotspot B (Ucayali; MAAP #26), Hotspot G (northern Huánuco; MAAP #48), and Hotspot F (Loreto-San Martin;MAAP #16). This was also shown for Ucayali in a recent peer-reviewed study.4 See below for information about large-scale oil palm.
  • Cacao is causing rapid deforestation along the Las Piedras River in eastern Madre de Dios (MAAP #23, MAAP #40). See below for information about large-scale cacao.
  • Papaya is an important new driver in Hotspot D, along the Interoceanic Higway in eastern Madre de Dios (MAAP #42).
  • Corn and rice plantations may also be an important driver in Hotspot D in eastern Madre de Dios (MAAP #28).

Large-scale Agriculture

Large-scale, agro-industrial deforestation remains a latent threat in Peru, particularly in the central and northern Amazon regions. This issue was put on high alert in 2013, with two cases of large-scale deforestation for oil palm and cacao plantations, respectively.

In the oil palm case, two companies that are part of the Melka group,5 cleared nearly 29,650 acres in Hotspot A in Ucayali between 2012 and 2015 (MAAP #4, MAAP #41). In the cacao case, another company in the Melka group (United Cacao) cleared 5,880 acres in Hotspot E in Loreto between 2013 and 2015 (MAAP #9, MAAP #13, MAAP #27, MAAP #35). Dennis Melka has explicitly stated that his goal is to bring the agro-industrial production model common in Southeast Asia to the Peruvian Amazon.6

Prior to these cases, large-scale agricultural deforestation occurred between 2007 and 2011, when oil palm companies owned by Grupo Palmas7 cleared nearly 17,300 acres for plantations in Hotspot H along the Loreto-San Martin border (MAAP #16). Importantly, we documented the additional deforestation of 24,215 acres for oil palm plantations surrounding the Grupo Palmas projects (MAAP #16).

In contrast, large-scale agricultural deforestation was minimal in 2015 and 2016. However, as noted above, it remains a latent threat. Both United Cacao and Grupo Palmas have expansion plans that would clear over 49,420 acres of primary forest in Loreto.8

Cattle Pasture

Using an archive of satellite imagery, we documented that deforestation for cattle pasture is a major issue in the central Peruvian Amazon. Immediately following a deforestation event, the scene of hundreds or thousands of recently cut trees often looks the same whether the cause is agriculture or cattle pasture. However, by using an archive of imagery and studying deforestation events from previous years, one can more easily determine the drivers of the forest loss. For example, after a year or two, agriculture and cattle pasture appear very differently in the imagery and thus it is possible to distinguish these two drivers.

Using this technique, we determined that cattle pasture is a major driver in Hotspots A and B, in the central Peruvian Amazon (MAAP #26, MAAP #37).

We also used this technique to determine that much of the deforestation in the northern section of El Sira Communal Reserve is due to cattle pasture (MAAP #45).

Maintenance of cattle pasture, and small-scale agriculture, are likely important factors behind the escaped fires that degrade the Amazon during intense dry seasons (MAAP #45, MAAP #47).

Gold Mining

Gold mining is one of the major drivers of deforestation in the southern Peruvian Amazon (Hotspot C). An important study found that gold mining cleared around 123,550 acres up through 2012.9 We built off this work, and by analyzing hundreds of high resolution imageres, found that gold mining caused the loss of an additional 30,890 acres between 2013 and 2016 (MAAP #50). Thus, gold mining is thus far responsible for the total loss of around 154,440 acres in southern Peru. Much of the most recent deforestation is illegal due to its occurrence in protected areas and buffer zones strictly off-limits to mining activities.

Most notably, we have closely tracked the illegal gold mining invasion of Tambopata National Reserve, an important protected area in the Madre de Dios region with renowned biodiversity and ecotourism. The initial invasion occurred in November 2015 (MAAP #21), and has steadily expanded to over 1,110 acres (MAAP #24, MAAP #30, MAAP #46). As part of this invasion, miners have modified the natural course of the Malinowski River, which forms the natural northern border of the reserve (MAAP #33). In addition, illegal gold mining deforestation continues to expand within the reserve’s buffer zone, particularly in an area known as La Pampa (MAAP #12, MAAP #31).

Further upstream, illegal gold mining is also expanding on the upper Malinowski River, within the buffer zone of Bahuaja Sonene National Park (MAAP #19, MAAP #43).

In contrast to the escalating situation in Tambopata, we also documented that gold mining deforestation has been contained in the nearby Amarakaeri Communal Reserve, an important protected area that is co-managed by indigenous communities and Peru’s national protected areas agency. Following an initial invasion of 27 acres in 2014 and early 2015, satellite imagery shows that management efforts have prevented any subsequent expansion within the protected area (MAAP #6, MAAP #44).

In addition to the above cases in Madre de Dios, gold mining deforestation is also increasingly an issue in the adjacent regions of Cusco and Puno (MAAP #14).

There are several small, but potentially emerging, gold mining frontiers in the central and northern Peruvian Amazon (MAAP #49). The Peruvian government has been working to contain the illegal gold mining in the El Sira Communal Reserve (MAAP #45). Further north in Amazonas region, there is gold mining deforestation along the Rio Santiago (MAAP #36, MAAP #49), and in the remote Condor mountain range along the border with Ecuador (MAAP #49).

Roads

Roads are a well-documented driver of deforestation in the Amazon, particularly due to their ability to facilitate human access to previously remote areas.10 Roads often serve as an indirect driver, as most of the deforestation directly associated with agriculture, cattle pasture, and gold mining is likely greatly facilitated by proximity to roads. We documented the start of a controversial road construction project that would cut through the buffer zones of two important protected areas, Amarakaeri Communal Reserve and Manu National Park (MAAP #29).

Logging Roads

In relation to general roads described above, we distinguish access roads that are constructed to gain entry to a particular project. The most notable type of access roads in Peru are logging roads, which are likely a leading cause of forest degradation as they facilitate selective logging of valuable timber species in remote areas.

One of the major recent advances in forest monitoring is the ability to quickly identify the construction of new logging roads. The unique linear pattern of these roads appears quite clearly in Landsat-based tree cover loss alerts such as GLAD and CLASlite. This advance is important because it is difficult to detect illegal logging in satellite imagery because loggers in the Amazon often selectively cut high value species and do not produce large clearings. But now, although it remains difficult to detect the actual selective logging, we can detect the roads that indicate that selective logging is taking place in that area.

In a series of articles, we highlighted the recent expansion of logging roads, including the construction of 1,134 km between 2013 and 2015 in the central Peruvian Amazon (MAAP #3, MAAP #18). Approximately one-third of these roads were within the buffer zones of Cordillera Azul and Sierra del Divisor National Parks (MAAP #15).

We documented the construction of an additional 83 km of logging roads during 2016,  (MAAP #40, MAAP #43) including deeper into the buffer zone of Cordillera Azul National Park.

Another major finding is the rapid construction of the logging roads. In several cases, we documented the construction rate of nearly five kilometers per week (MAAP #18, MAAP #40, MAAP #43).

Determining the legality of these logging roads is complex, partly because of the numerous national and local government agencies involved in the authorization process. Many of these roads are near logging concessions and native communities, whom may have obtained the rights for logging from the relevant forestry authority (in many cases, the regional government).

Coca

According to a recent United Nations report, the Peruvian land area under coca cultivation in 2015 (99,580 acres) was the lowest on record (since 2001) and part of a declining trend since 2011 (154,440 acres).11 There are 13 major coca growing zones in Peru, but it appears that only a few of them are actively causing new deforestation. Most important are two coca zonas in the region of Puno that are causing deforestation within and around Bahuaja Sonene National Park (MAAP #10, MAAP #14). Several coca zones in the regions of Cusco and Loreto may also be causing some new deforestation.

Hydroelectric Dams

Although there is a large portfolio of potential new hydroelectric dam projects in the Peruvian Amazon,12 many of not advanced to implementation phase. Thus, forest loss due to hydroelectric dams is not currently a major issue, but this could quickly change in the future if these projects are revived. For example, in adjacent western Brazil, we documented the forest loss of 89,205 acres associated with the flooding caused by two dams on the upper Madeira River (MAAP #34).

Hydrocarbon (Oil & Gas)

During the course of our monitoring, we have not yet detected major deforestation events linked to hydrocarbon-related activities. As with dams, this could change in the future if oil and gas prices rise and numerous projects in remote corners of the Amazon move forward.

Methodology

MAAP methodology has 4 major components:

  1. Forest Loss Detection. MAAP reports rely heavily on early-warning tree cover loss alerts to help us identify where new deforestation is happening. Currently, our primary tool is GLAD alerts, which are developed by the University of Maryland and Google,13 and presented by WRI’s Global Forest Watch and Peru’s GeoBosques. These alerts, launched in Peru in early 2016, are based on 30-meter resolution Landsat satellite images and updated weekly. We also occasionally incorporate CLASlite, forest loss detection software based on Landsat (and now Sentinel-2) developed by the Carnegie Institution for Science, and the moderate resolution (250 meters) Terra-i alerts. We are also experimenting with Sentinel-1 radar data (freely available from the European Space Agency), which has the advantage of piercing through cloud cover in order to continue monitoring despite persistent cloudy conditions
  2. Prioritize Big Data. The early warning systems noted above yield thousands of alerts, thus a procedure to prioritize the raw data is needed. We employ numerous prioritization methods, such as creation of hotspot maps (see below), focus on key areas (such as protected areas, indigenous territories, and forestry concessions), and identification of striking patterns (such as linear features or large-scale clearings).
  1. Identify Deforestation Drivers. Once priority areas are identified, the next challenge is to understand the cause of the forest loss. Indeed, one of the major advances of MAAP over the past year has been using high-resolution satellite imagery to identify key deforestation drivers. Our ability to identify these deforestation drivers has been greatly enhanced thanks to access to high-resolution satellite imagery provided by Planet 14
    (via their Ambassador Program) and Digital Globe (via the NextView Program, courtesy of an agreement with USAID). We also occasionally purchase imagery from Airbus(viaApollo Mapping).
  2. Publish User-Friendly Reports. The final step is to publish technical, but accessible, articles highlighting novel and important findings on the MAAP web portal. These articles feature concise text and easy-to-understand graphics aimed at a wide audience, including policy makers, civil society, researchers, students, journalists, and the public at large. During preparation of these articles, we consult with Peruvian civil society and relevant government agencies in order to improve the quality of the information.

Endnotes

1 MINAM-Peru (2016) Estrategia Nacional sobre Bosques y Cambio Climático.

2 Methodology: Kernel Density tool from Spatial Analyst Tool Box of ArcGis. The 2016 data is based on GLAD alerts, while the 2012-15 data is based on official annual forest loss data

3 Ravikumar et al (2016) Is small-scale agriculture really the main driver of deforestation in the Peruvian Amazon? Moving beyond the prevailing narrative. Conserv. Lett. doi:10.1111/conl.12264

4 Gutiérrez-Vélez VH et al (2011). High-yield oil palm expansion spares land at the expense of forests in the Peruvian Amazon. Environ. Res. Lett., 6, 044029.

5 Environmental Investigation Agency EIA (2015) Deforestation by Definition.

6 NG J (2015) United Cacao replicates Southeast Asia’splantation model in Peru, says CEO Melka. The Edge Singapore, July 13, 2015.

7 Palmas del Shanusi & Palmas del Oriente; http://www.palmas.com.pe/palmas/el-grupo/empresas

8 Hill D (2015) Palm oil firms in Peru plan to clear 23,000 hectares of primary forest. The Guardian, March 7, 2015.

9 Asner GP, Llactayo W, Tupayachi R,  Ráez Luna E (2013) Elevated rates of gold mining in the Amazon revealed through high-resolution monitoring. PNAS 46: 18454. They reported 46,417 hectares confirmed and 3,268 hectares suspected (49,865 ha total).

10 Laurance et al (2014) A global strategy for road building. Nature 513:229; Barber et al (2014) Roads, deforestation, and the mitigating effect of protected areas in the Amazon.  Biol Cons 177:203.

11 UNODC/DEVIDA (2016) Perú – Monitoreo de Cultivos de Coca 2015.

12 Finer M, Jenkins CN (2012) Proliferation of Hydroelectric Dams in the Andean Amazon and Implications for Andes-Amazon Connectivity. PLoS ONE 7(4): e35126.

13 Hansen MC et al (2016) Humid tropical forest disturbance alerts using Landsat data. Environ Res Lett 11: 034008.

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

Citation

Finer M, Novoa S (2017) Patterns and Drivers of Deforestation in the Peruvian Amazon. MAAP: Synthesis #2.

MAAP #40: Early Warning Deforestation Alerts in the Peruvian Amazon

Posted on by dcadmin

GLAD alerts are a powerful new tool to monitor forest loss in the Peruvian Amazon in near real-time. This early warning system, created by the GLAD (Global Land Analysis and Discovery) laboratory at the University of Maryland and supported by Global Forest Watch, was launched in March 2016 as the first Landsat-based (30-meter resolution) forest loss alert system (previous systems were based on lower-resolution imagery). The alerts are updated weekly and can be accessed through Global Forest Watch (Image 40a, left panel) or GeoBosques (Image 40a, right panel), a web portal operated by the Peruvian Ministry of Environment.

Imagen 41a. Datos: UMD/GLAD, WRI/GFW, PNCB/MINAM
Image 40a. Data: UMD/GLAD, WRI/GFW, PNCB/MINAM

In MAAP, we often combine these alerts with analysis of high-resolution satellite imagery (courtesy of the Planet Ambassador Program and Digital Globe NextView service) to better understand patterns and drivers of deforestation in near real-time. In this article, we highlight 3 examples of this type of innovative analysis from across the Peruvian Amazon:

Example 1: Logging Roads in central Peru (Ucayali)
Example 2: Invasion of Ecotourism Concessions in southern Peru (Madre de Dios)
Example 3: Buffer Zone of Cordillera Azul National Park (Loreto)

Example 1: Logging Roads in central Peru (Ucayali)

In the previous MAAP #18, we documented the proliferation of logging roads in the central Peruvian Amazon during 2015. In recent weeks, we have seen the start of rapid new logging road construction for 2016. Image 40b shows the linear forest loss associated with two new logging roads along the Tamaya river in the remote central Peruvian Amazon (Ucayali region). Red indicates the 2016 road construction (35.8 km). Insets A and B indicate the areas shown in the high-resolution zooms below.

Image 40b. Data: UMD/GLAD, Hansen/UMD/Google/USGS/NASA, MINAGRI
Image 40b. Data: UMD/GLAD, Hansen/UMD/Google/USGS/NASA, MINAGRI

The following images show, in high-resolution, the rapid construction of logging roads in 2016. Image 40c shows the construction of 16.1 km between March (left panel) and July (right panel) 2016 in the area indicated by Inset A. Image 40d shows the construction of 19.7 km between June (left panel) and July (right panel) 2016 in the area indicated by Inset B.

Image 40c. Data: Planet
Image 40c. Data: Planet
Image 40d. Data: Planet
Image 40d. Data: Planet

Example 2: Invasion of Ecotourism Concessions in southern Peru (Madre de Dios)

Image 40e shows the recent deforestation within two ecotourism concessions along the Las Piedras River in the Madre de Dios region. Red indicates the 2016 GLAD alerts (67.3 hectares). Note that the Las Piedras Amazon Center (LPAC) Ecotourism Concession represents an effective barrier against deforestation occurring in the surrounding concessions. According to local sources, the main drivers of deforestation in the area are related to the establishment of cacao plantations and cattle pasture (see s MAAP #23). Inset A indicates the areas shown in the high-resolution zoom below.

Image 40e. Data: UMD/GLAD, Hansen/UMD/Google/USGS/NASA, MINAGRI
Image 40e. Data: UMD/GLAD, Hansen/UMD/Google/USGS/NASA, MINAGRI

Image 40f shows high-resolution images of the area indicated by Inset A between April (left panel) and July (right panel) 2016. The yellow circles indicate areas of deforestation between these dates.

Image 40f. Data: Planet, DigitalGlobe (Nextview)
Image 40f. Data: Planet, DigitalGlobe (Nextview)

Example 3: Buffer Zone of Cordillera Azul National Park (Loreto)

Image 40g shows the recent deforestation within the western buffer zone of the Cordillera Azul National Park in the Loreto region. Red indicates the 2016 GLAD alerts (87.3 hectares). It is worth noting that this area is classified as Permanent Production Forest, not as an agricultural area.

Image 40g. Data: SERNANP, Landsat, UMD/GLAD, Hansen/UMD/Google/USGS/NASA
Image 40g. Data: SERNANP, Landsat, UMD/GLAD, Hansen/UMD/Google/USGS/NASA

Image 40h shows high-resolution images of the area indicated by Inset A between December 2015 (left panel), January 2016 (central panel), and July 2016 (right panel). The yellow circles indicate areas that were deforested between these dates. The driver of the deforestation appears to be the establishment of small-scale agricultural plantations.

Image 40h. Data: RapidEye/Planet, Digital Globe (Nextview)
Image 40h. Data: RapidEye/Planet, Digital Globe (Nextview)

Citation

Finer M, Novoa S, Goldthwait E (2016) Early Alerts of Deforestation in the Peruvian Amazon. MAAP: 40.