Agriculture-Related Threat: Cattle pasture

MAAP #214: Agriculture in the Amazon: New data reveals key patterns of crops & cattle pasture

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Figure 1. Example of the merged agricultural and pasture data in a section of the Brazilian Amazon. Data: IFRI/SPAM, Lapig/UFG, Mapbiomas, AMW, ACA/MAAP.

A burst of new data and online visualization tools are revealing key land use patterns across the Amazon, particularly regarding the critical topic of agriculture. This type of data is particularly important because agriculture is the leading cause of overall Amazonian deforestation.

These new datasets include:

  • Crops. The International Food Policy Research Institute (IFPRI), a leading agriculture and food systems research authority, recently launched the latest version of their innovative crop monitoring product, the Spatial Production Allocation Model (SPAM).1 This latest version, developed with support from WRI’s Land & Carbon Lab, features spatial data for 46 crops, including soybean, oil palm, coffee, and cocoa. This data is mapped at 10-kilometer resolution across the Amazon and updated through 2020.2
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  • Cattle pasture. The Atlas of Pastures,3 developed by the Federal University of Goiás, facilitates access to data regarding Brazilian cattle pastures generated by MapBiomas. This data is mapped at 30-kilometer resolution and updated through 2022. We use Collection 5 from Mapbiomas for the rest of the Amazonian countries.4
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  • Gold mining. New mining data is included for additional context. Amazon Mining Watch uses machine learning to map open-pit gold mining.5 This data is mapped at 10-kilometer resolution across the Amazon and updated through 2023.

We merged and analyzed these new datasets to provide our first overall estimate of Amazonian land use, the most detailed effort to date across all nine countries of the biome. Figure 1 shows an example of this merged data in a section of the Brazilian Amazon.

Below, we present and illustrate the following major findings across the Amazon, and then zoom in on several regions across the Amazon to show the data in greater detail.

Major Findings

The Base Map illustrates several major findings detailed below.

Base Map. Overview of the merged datasets noted above for crops, pasture, and gold mining. Double-click to enlarge. Data: IFRI/SPAM, Lapig/UFG, Mapbiomas, AMW, ACA/MAAP.

1) Crops
We found that 40 crops in the SPAM dataset overlap with the Amazon, covering over 106 million hectares (13% of the Amazon biome).

Soybean covers over 67.5 million hectares, mostly in southern Brazil and Bolivia. Maize covers slightly more area (70 million hectares) but we consider this a secondary rotational crop with soy (thus, there is considerable overlap between these two crops).

Oil palm covers nearly 8 million hectares, concentrated in eastern Brazil, central Peru, northern Ecuador, and northern Colombia.

In the Andean Amazon zones of Peru, Ecuador, and Colombia, cocoa covers over 8 million hectares and the two types of coffee (Arabica and Robusta) cover 6.7 million hectares.

Other major crops across the Amazon include rice (13.8 million hectares), sorghum (10.9 million hectares), cassava (9.8 million hectares), sugarcane (9.6 million hectares), and wheat (5.8 million hectares).

2) Cattle Pasture
Cattle Pasture covers 76.3 million hectares (9% of the Amazon biome). The vast majority (92%) of the pasture is in Brazil, followed by Colombia and Bolivia.

3) Crops & Cattle Pasture
Overall, accounting for overlaps between the data, we estimate that crops and pasture combined cover 115.8 million hectares. This total is the equivalent of 19% of the Amazon biome.

In comparison, open-pit gold mining covered 1.9 million hectares (0.23% of the Amazon biome).

Zooms across the Amazon

Eastern Brazilian Amazon

Figure 2 shows the transition from the soy frontier to the cattle pasture frontier in the eastern Brazilian Amazon. Also note a mix of other crops, such as oil palm, sugarcane, and cassava, and some gold mining.

Figure 2. Eastern Brazilian Amazon. Data: IFRI/SPAM, Lapig/UFG, Mapbiomas, AMW, ACA/MAAP.

Andean Amazon (Peru and Ecuador)

Figure 3. Andean Amazon. Data: IFRI/SPAM, Lapig/UFG, Mapbiomas, AMW, ACA/MAAP.

The land use patterns are quite different in the Andean Amazon regions of Peru and Ecuador.

Figure 3 shows, that instead of soy and cattle pasture, there is instead oil palm, rice, coffee, and cocoa.

Also note the extension of the cattle pasture frontier in the western Brazilian Amazon, towards Peru and Bolivia.

 

 

 

 

 

 

 

 

 

 

 

 

Northeast Amazon (Venezuela, Guyana, Suriname, French Guiana)

Figure 4 shows the general lack of crops in the core Amazon regions Guyana, Suriname, and French Guiana, which is surely a major factor they are all considered High Forest cover, Low Deforestation countries (HFLD). In contrast, note there is abundant gold mining activity throughout this region.

Figure 4. Northeastern Amazon. Data: IFRI/SPAM, Lapig/UFG, Mapbiomas, AMW, ACA/MAAP.

Methods

For the SPAM data, we used the physical area, which is measured in a hectare and represents the actual area where a crop is grown (not counting how often production was harvested from it). We only considered values ​​greater than or equal to 100 ha per pixel.

For the Base Map, due to their importance as primary economic crops, we layered soybean and oil palm as the top two layers, respectively. From there, crops were layered in order of their total physical area across the Amazon. Thus, the full extensions of some crops are not shown if they overlap pixels with other crops that have greater physical area. For overlaps with crops and pasture, we favored the crops.

Notes & Data Sources

1 International Food Policy Research Institute (IFPRI), 2024, “Global Spatially-Disaggregated Crop Production Statistics Data for 2020 Version 1.0” https://doi.org/10.7910/DVN/SWPENT, Harvard Dataverse, V1

Spatial Production Allocation Model (SPAM)
SPAM 2020 v1.0 Global data (Updated 2024-04-16)

2 Note that the spatial resolution is rather low (10-kilometers) so all crop coverage data above should be interpreted as referential only.

3 The Atlas of Pastures (Atlas das Pastagens), open to the public, was developed by the Image Processing and Geoprocessing Laboratory of the Federal University of Goiás (Lapig/UFG), to facilitate access to results and products generated within the MapBiomas initiative, regarding Brazilian pastures.

https://atlasdaspastagens.ufg.br/

4 MapBiomas Collection 5;  https://amazonia.mapbiomas.org/en/

5 See MAAP #212 for more information on Amazon Mining Watch.

Citation

Finer M, Ariñez A (2024) Agriculture in the Amazon: New data reveals key patterns of crops & cattle pasture. MAAP: 214.

MAAP #136: Amazon Deforestation 2020 (Final)

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

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

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

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

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

We highlight several key findings:

  • The Amazon lost nearly 2.3 million hectares (5.6 million acres) of primary forest loss in 2020 across the nine countries it spans.
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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 #133: Deforestation Continues in National Parks of Colombian Amazon

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Base Map. Deforestation 2020-21 in the National Parks of the Colombian Amazon. Data: MAAP.

As we have indicated in previous reports (MAAP #120), there is an “arc of deforestation” in the northwest Colombian Amazon, impacting numerous protected areas and indigenous reserves.

Here, we emphasize that this deforestation currently impacts four National Parks: Tinigua, Macarena, Chiribiquete and La Paya.

In the Base Map, the red circles indicate the areas most impacted by recent deforestation within these parks.

The letters (A-D) indicate the location of the high-resolution satellite images (Planet) below.

While Tinigua and Macarena continue as the most impacted National Parks, below we focus on the new deforestation fronts in Chiribiquete and La Paya.

Specifically, we show the most recent and urgent deforestation, since September 2020 to the present (February 2021).

 

 

 

 

Chiribiquete National Park

Chiribiquete National Natural Park lost more than 1,000 hectares (2,500 acres) in the last six months, in six different areas of the park (see Base Map above). Much of this deforestation appears to be associated with the conversion of primary forest to illegal cattle pasture. The following satellite images show deforestation in three of these areas (A-C) between September 2020 (left panel) and February 2021 (right panel). *It is important to note that immediately prior to this publication authorities carried out a major intervention to crack down on the illegal activity within the park (see news here).

Image A. Deforestation in Chiribiquete National Park, western sector 1. Reference coordinate: 1.05497 ° N, 74.26465 ° W. Data: Planet, MAAP.
Image B. Deforestation in Chiribiquete National Park, western sector 2. Reference coordinate: 1.57990 ° N, 73.78689 ° W. Data: Planet, MAAP.
Image C. Deforestation in Chiribiquete National Park, northern sector 1. Reference coordinate: 2.00975, -73.45541. Data: Planet, MAAP.

La Paya National Park

La Paya National Park lost more than 150 hectares (370 acres) in the last six months, in the northwest sector of the park (see Base Map above).
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The following image shows an example of deforestation in this sector of the park between September 2020 (left panel) and January 2021 (right panel).

Image D. Deforestation in La Paya National Park, northern sector. Reference coordinate: 0.39677 ° N, 75.48505 ° W. Data: Planet, MAAP.

Fire Season

In addition, the fire season has started in the Colombian Amazon. Interestingly, now (February to March) is typically Colombia’s peak deforestation and fire season, in contrast with Brazil, Bolivia, and Peru, whose seasons peak between June and October.
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The following very high-resolution images (Skyat) reveal the burning of recently deforested areas within Chiribiquete National Park.
Fire inside Chiribuete National Park (February 11, 2021) burning recently deforested areas. Data: Planet (Skysat).
Zoom of fire inside Chiribuete National Park (February 11, 2021) burning recently deforested areas. Data: Planet (Skysat).

Acknowledgmens

We thank R. Botero (FCDS) and G. Palacios for their helpful comments on this report.

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

Citation

Finer M, Mamani N (2021) Deforestation Continues in National Parks of Colombian Amazon. MAAP: 133.

MAAP #132: Amazon Deforestation Hotspots 2020

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Base Map. Forest loss hotspots across the Amazon in 2020. Data: UMD/GLAD, RAISG, MAAP. The letters A-G correspond to the zoom examples below.

We present a first look at the major hotspots of primary forest loss across the Amazon in 2020 (see Base Map).*

There are several major headlines:

  • We estimate over 2 million hectares (5 million acres) of primary forest loss across the nine countries of the Amazon in 2020.*
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  • The countries with the highest 2020 primary forest loss are 1) Brazil, 2) Bolivia, 3) Peru, 4) Colombia, 5) Venezuela, and 6) Ecuador.
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  • The majority of the hotspots occurred in the Brazilian Amazon, where massive deforestation stretched across nearly the entire southern region. Many of these areas were cleared in the first half of the year and then burned in July and August. In September, there was a shift to actual forest fires (see MAAP #129).
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  • Several of the most intense hotspots were in the Bolivian Amazon, where fires raged through the dry forests (known as the Chiquitano) in the southeast region.
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  • There continues to be an arc of deforestation in the northwestern Colombian Amazon, impacting numerous protected areas.
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  • In the Peruvian Amazon, deforestation continues to impact 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).

Below, we show a striking series of high-resolution satellite images that illustrate some of the major deforestation events across the Amazon in 2020 (indicated A-G on the Base Map).

Widespread Deforestation in the Brazilian Amazon

Zooms A-C show examples of a troublingly common phenomenon in the Brazilian Amazon: large-scale deforestation events in the first half of the year that are later burned in July and August, causing major fires due to the abundant recently-cut biomass. Much of the deforestation in these areas appears to associated with clearing rainforests for cattle pastures. The three examples below show the striking loss of over 21,000 hectares of primary forest in 2020.

Zoom A. Deforestation in the Brazilian Amazon (Amazonas state) of 3,400 hectares between April (left panel) and November (right panel) 2020. Data: ESA, Planet.
Zoom B. Deforestation in Brazilian Amazon (Amazonas state) of 2,540 hectares between January (left panel) and November (right panel) 2020. Data: Planet.
Zoom C. Deforestation in Brazilian Amazon (Para state) of 15,250 hectares between January (left panel) and October (right panel) 2020. Data: Planet.

Forest Fires in the Brazilian Amazon

In September, there was a shift to actual forest fires in the Brazilian Amazon (see MAAP #129). Zoom D and E show examples of these major forest fires, which burned over 50,000 hectares in the states of Pará and Mato Grosso. Note both fires impacted indigenous territories (Kayapo and Xingu, respectively).

Zoom D. Forest fire in Brazilian Amazon (Para state) that burned 9,000 hectares between March (left panel) and October (right panel) 2020. Data: Planet.
Zoom E. Forest fire in Brazilian Amazon (Mato Grosso state) that burned over 44,000 hectares between May (left panel) and October (right panel) 2020. Data: Planet.

Forest Fires in the Bolivian Amazon

The Bolivian Amazon also experienced another intense fire season in 2020. Zoom F shows the burning of a massive area (over 260,000 hectares) in the Chiquitano dry forests (Santa Cruz department).

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

Arc of Deforestation in the Colombian Amazon

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, Zoom G 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.

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

Deforestation in the central Peruvian Amazon

Finally, Zoom H 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.

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

*Notes and Methodology

The analysis was based on early warning forest loss alerts known as GLAD alerts (30-meter resolution) produced by the University of Maryland and also presented by Global Forest Watch. It is critical to highlight that this data represents a preliminary estimate and more definitive data will come later in the year. For example, our estimate does include some forest loss caused by natural forces. Note that this data detects and classifies burned areas as forest loss. Our estimate includes both confirmed (1,355,671 million hectares) and unconfirmed (751,533 ha) alerts.

Our geographic range is the biogeographic boundary of the Amazon as defined by RAISG (see Base Map above). This range includes nine countries.

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%.

Acknowledgements

We thank E. Ortiz (AAF), M.E. Gutierrez (ACCA), and S. Novoa 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. MAAP: 132.

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

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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 #122: Amazon Deforestation 2019

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Table 1. Amazon 2019 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.

MAAP #113: Satellites Reveal what Fueled Brazilian Amazon Fires

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Base Map. Brazilian Amazon 2019. Data: UMD/GLAD, NASA (MODIS), DETER, Hansen/UMD/Google/USGS/NASA.

As part of our ongoing coverage, we present two key new findings about the Brazilian Amazon fires that captured the world’s attention in August (see our novel satellite-based methodology below).

First, we found that many of the fires, covering over 450,000 hectares, burned areas recently deforested since 2017 (orange in Base Map). That is a massive area equivalent to over a million acres (or 830,000 American football fields), mostly in the states Amazonas, Rondônia, and Pará.

Importantly, 65% (298,000 hectares) of this area was both deforested and burned this year, 2019.

Second, we found 160,400 hectares of primary forest burned in 2019 (purple in Base Map).* Most of these areas surround deforested lands in the states of Mato Grosso and Pará, and were likely pasture or agricultural fires that escaped into the forest.

As far as we know, these are the first precise estimates based on detailed analysis of satellite imagery. Other estimates based solely on fire alerts tend to greatly overestimate burned areas due to their large spatial resolution.

Below we present a series of satellite time-lapse videos showing examples of the different types of fires we documented.

Policy Implications

The policy implications of these findings are critically important: national and international focus needs to be on minimizing new deforestation, in addition to fire prevention and management.

That is, we need to recognize that many of the fires are in fact a lagging indicator of previous deforestation, thus to minimize fires we need to minimize deforestation.

For example, one of the leading deforestation drivers in the Brazilian Amazon is cattle ranching (1, 2, 3). What measures can be taken to prevent the further expansion of the ranching frontier?

Satellite Time-lapse Videos

Deforestation Followed by Fire

Video A shows the deforestation of 1,760 hectares (4,350 acres) in Mato Grosso state in 2019 (May to July), followed by fires in August. Planet link.

Video B shows the deforestation of 650 hectares (1,600 acres) in Rondônia state in 2019 (April to July), followed by fire in August. Planet link.

Deforestation Caused by Fire

Videos C-D show 2019 fires burning primary or secondary forest surrounding recently or previously cleared areas.

*Notes

In addition to the finding of 160,400 hectares of primary forest burned in 2019, we also found: 25,800 hectares of secondary forest burned in 2019;
35,640 hectares of primary forest burned in the northern state of Roraima in March 2019 (plus an additional 16,500 hectares of secondary forest.

Methodology

Deforestation Fires

We created two “hotspots” layers, one for deforestation and the other for fires, by conducting a kernel density analysis. This type of analysis calculates the magnitude per unit area of a particular phenomenon, in this case forest loss alerts (proxy for deforestation) and temperature anomaly alerts (proxy for fires)

Specifically, we used the following data three sets:

2019 GLAD alert forest loss data (30 meter resolution) from the University of Maryland and available on Global Forest Watch.

2017 and 2018 forest loss data (30 meter resolution) from the University of Maryland and available on Global Forest Watch (4).

NASA’s Fire Information for Resource Management System (FIRMS) MODIS-based fire alert data (1 km resolution).

We conducted the analysis using the Kernel Density tool from Spatial Analyst Tool Box of ArcGIS, using 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: 10%-25%; High: 26%-50%; Very High: >50%. We then combined all three categories into one color (yellow for deforestation and red for fire). Orange indicates areas where both layers overlap. As background layer, we also included pre-2019 deforestation data from Brazil’s PRODES system.

We prioritized the orange overalp areas for further analysis. For the major orange areas in Rondônia, Amazonas, Mato Grosso, Acre, and Pará, we conducted a visual analysis using the satellite company Planet’s online portal, which includes an extensive archive of Planet, RapidEye, Sentinel-2, and Landsat data. Using the archive, we identified areas that we visually confirmed a) were deforested in 2017-19 and b) were later burned in 2019 between July and September. We then used the area measure tool to estimate the size of these areas, which ranged from large plantations ( ~1,000 hectares) to many smaller areas scattered across the focal landscape.

Forest Fires:

To estimate forests burned in 2019 we combined analysis of several datasets. First, we started with 30 meter resolution ‘burn scar’ data produced by INPE (National Institute for Space Research) DETER alerts, updated through October 2019. In order to avoid overlapping areas, we eliminated alerts previously reported from 2016 to 2018, and alerts from other land use categories (selective logging, deforestation, degradation and mining, and other). Second, we eliminated previously reported 2001-18 forest loss from University of Maryland and INPE (PRODES). Third, to distinguish burning of primary and secondary forest, we incorporated primary forest data from the University of Maryland (5).

References

  1. Krauss C, Yaffe-Bellany D, Simões M (2019) Why Amazon Fires Keep Raging 10 Years After a Deal to End Them. New York Times. https://www.nytimes.com/2019/10/10/world/americas/amazon-fires-brazil-cattle.html
  2. Kelly M, Cahlan S (2019) The Brazilian Amazon is still burning. Who is responsible? Washington Post. https://www.washingtonpost.com/politics/2019/10/07/brazilian-amazon-is-still-burning-who-is-responsible/#click=https://t.co/q2XkSQWQ77
  3. Al Jazeera (2019) See How Beef Is Destroying The Amazon. https://www.youtube.com/watch?v=9o2M_KL8X6g&feature=youtu.be
  4. 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.
  5. 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

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

Citation

Finer M, Mamani N (2019) Satellites Reveal what Fueled Brazilian Amazon Fires. MAAP: 113.

MAAP #101: Deforestation Continues in Colombian Amazon (2019)

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Overflight photo of recent deforestation in Chiribiquete National Park. Credit: FCDS/RFN/AAF.

A major deforestation surge continues in the northwest Colombian Amazon (MAAP #97).

In 2018, it resulted in the loss of 199,000 hectares (491,700 acres)*, making it the most concentrated deforestation hotspot in the entire western Amazon (MAAP #100).

Here, we provide a real-time update for 2019 based on early warning GLAD alerts.** The alerts indicate the loss of 56,300 hectares (139,100 acres) in the first five months of 2019 (January to May) in the Colombian Amazon.

The Base Map (see below) shows the deforestation hotspots are again concentrated in the northwest Colombian Amazon.

We focus on Chiribiquete National Park, showing satellite imagery and overflight photos for two sections of the park experiencing recent deforestation.***

We estimate the deforestation of 2,200 hectares (5,400 acres) inside the Park since its expansion in July 2018.

As described below, one of the main deforestation drivers in the region is conversion to pasture for land grabbing or cattle ranching.

 

 

 

Base Map. 2019 deforestation hotspots in the Colombian Amazon. Data: UMD/GLAD, RUNAP, RAISG.

Zoom 1: Western Chiribiquete (Llanos de Yari)

Zoom 1 shows the deforestation in the recently expanded western section of Chiribiquete National Park between February 2018 (left panel) and May 2019 (right panel). The white inset boxes indicate the areas of the overflight photos shown below.

We estimate the deforestation of 555 hectares (1,300 acres) in this section of the park since July 2018, the date of the expansion of Chiribiquete National Park in this area.

Zoom 1. Western Chiribiquete National Park (Llanos de Yari). Data: Planet.
Inset A1. Overflight photo over Chiribiquete National Park, courtesy of FCDS/RFN/AAF.
Inset A2. Overflight photo over Chiribiquete National Park, courtesy of FCDS/RFN/AAF.

A recent report by the Colombian government agency charged with monitoring deforestation (IDEAM 2019) characterizes the situation as follows:

“In this area, the process of colonization is accelerated, causing a growing demand for resources and new lands, which is encouraged by the reconfiguration of organized armed groups and the absence of state control at the local level. The main conversion of the forest is to pasture, destined for cattle ranching or land grabbing. This transformation is advanced by the area’s tertiary road network, which allows access to new areas of forest and burning as a method of rapid removal of coverage. This area is also used for illicit crops.”

Zoom 2: Northern Chiribiquete

Zoom 2 shows the deforestation in the recently expanded northern section of Chiribiquete National Park between February 2018 (left panel) and April 2019 (right panel). The white inset boxes indicate the areas of the overflight photos shown below.

We estimate the deforestation of 1,650 hectares (4,100 acres) in this section of the park since 2018, the date of the expansion of Chiribiquete National Park in this area.

Zoom 2. Northern Chiribiquete National Park. Data: ESA.
Inset B1. Overflight photo over Chiribiquete National Park, courtesy of FCDS/RFN/AAF.
Inset B2. Overflight photo over Chiribiquete National Park, courtesy of FCDS/RFN/AAF.
Inset B3. Overflight photo over Chiribiquete National Park, courtesy of FCDS/RFN/AAF.
Inset B4. Overflight photo over Chiribiquete National Park, courtesy of FCDS/RFN/AAF.

 

A recent report by the Colombian government agency charged with monitoring deforestation (IDEAM 2019) characterizes the situation as follows:

“As is common in the Amazon region, the main activity driving the transformation of forests in this area is the establishment of pastures, with the purpose of land grabbing or cattle ranching. This transformation is generally financed by external actors, whose primary motivation is speculation and income generation. The armed actors present in the area promote the development of illicit agricultural activities, as well as the expansion of informal road infrastructure, which affects forests by facilitating access.”

Notes

*Including 154,000 hectares (380,5000 acres) of primary forests. The surge started in 2016.

**GLAD alerts, produced by the University of Maryland and presented by Global Forest Watch, are based on Landsat imagery. To generate the deforestation hotspots map, we conducted a kernel density analysis on GLAD alert data from January 1 to May 31, 2019.

***Overflight was March 22, 2019, carried out by Fundación Conservación y Desarrollo, with funding from Rain Forest Norway and Andean Amazon Fund.

References

IDAEM-SMBYC (2019) BOLETÍN DE DETECCIÓN TEMPRANA DE DEFORESTACIÓN #17. Link: http://documentacion.ideam.gov.co/openbiblio/bvirtual/023856/17_BoletinAT-D.pdf

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

Acknowledgments

We thank A. Rojas (FCDS) and R. Botero (FCDS) for helpful comments to this report.

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 #78: Deforestation Hotspots in the Peruvian Amazon, 2017

Posted on by dcadmin
Base Map (Image 78). Data: PNCB/MINAM, UMD/GLAD, SERNANP

As we begin a new year, we make an initial assessment of 2017, estimating deforestation hotspots in the Peruvian Amazon based on early warning alert data.*

We estimate the annual forest loss of 354,410 acres (143,425 hectares) across Peru in 2017. If confirmed, this total represents the lowest in 5 years (average of 394,600 acres since 2012), and a decrease of 13% from last year.**

Deforestation, however, is still widespread. The base map shows the most intense hotspots (areas with highest density of forest loss).

The two main deforestation areas are clearly seen: the central Amazon (Ucayali/Huánuco regions) and the southern Amazon (Madre de Dios). Also, there are several additional hotspots scattered throughout the country.

We present satellite images (slider format) of the most intense hotspots. The images reveal that the main deforestation drivers include gold mining, oil palm, and general agriculture (crops and livestock).

The hotspots detailed below are:

A. Central Amazon (Ucayali/Huánuco)
B. Southern Madre de Dios
C. Iberia (Madre de Dios)
D. Northeast San Martín
E. Nieva (Amazonas)

 

 

 

A. Central Amazon (Ucayali/Huánuco)

As in previous years, there is a concentration of high intensity hotspots in the central Peruvian Amazon (Ucayali and Huánuco regions). We estimate the deforestation of 57,430 acres (23,240 hectares) in this hotspot during 2017. The images show that the main drivers are likely cattle ranching and oil palm plantations. Image 78a is a slider showing an example of the deforestation in this hotspot during 2017.

[twenty20 img1=”6875″ img2=”6876″ width=”78%” offset=”0.5″]

Image 78a. Central Amazon. Data: Planet, NASA/USGS

B. Southern Madre de Dios

As described in MAAP #75, Madre de Dios has become one of the regions with the highest rates of deforestation in Peru, with a concentration along the Interoceanic highway. We estimate the deforestation of 27,465 acres (11,115 hectares) in southern Madre de Dios during 2017. Image 78b is a slider showing the extensive deforestation that occurred in this area during 2017. The images show that the main drivers are gold mining (south of the highway) and small to medium-scale agriculture (north of the road).

[twenty20 img1=”6877″ img2=”6878″ width=”78%” offset=”0.5″]

Image 78b. South Madre de Dios. Data: Planet

C. Iberia (Madre de Dios)

On the other side of Madre de Dios, near the border with Brazil, another hotspot is located around the town of Iberia. We estimate the deforestation of 7,955 acres (3,220 hectares) in this hotspot during 2017.  Image 78c is a slider showing deforestation in the area of the hotspot west of Iberia (known as Pacahuara). The images show that the main deforestation driver is small to medium-scale agriculture (according to local sources, the main crops include corn, papaya, and cacao).

[twenty20 img1=”6880″ img2=”6879″ width=”78%” offset=”0.5″]

Image 78c. Iberia. Data: Planet

D. Northeast of San Martín

A new hotspot emerged in the northeast corner San Martin due to a large-scale agriculture plantation. Image 78d is a slider that shows the deforestation of 1,830 acres (740 hectares) during the last several months of 2017. The Peruvian Environment Ministry has confirmed that the cause is a new oil palm plantation. Indeed, this new deforestation is close to an area that has experienced extensive deforestation for oil palm plantations in recent years (see MAAP #16).

[twenty20 img1=”6882″ img2=”6881″ width=”78%” offset=”0.5″]

Image 78d. San Martin. Data: Planet

E. Nieva (Amazonas)

In northwestern Peru, there is a new isolated hotspot along a road connecting the towns of Bagua and Saramiriza in the district of Nieva (Amazonas region). We estimate the deforestation of 2,805 acres (1,135 hectares) in this hotspot during 2017. Image 78e is a slider that shows an example of the recent deforestation. The images show that the cause of deforestation is mostly small-scale agriculture and cattle pasture.

[twenty20 img1=”6884″ img2=”6883″ width=”78%” offset=”0.5″]

Image 78e. Nieva. Data: Planet

Notes

*We emphasize that the data presented in this report are estimates based on early warning alert data generated by: 1) GLAD/UMD (Hansen et al 2016 ERL 11: (3)), and 2) the National Program for Forest Conservation for Climate Change Mitigation of the Ministry of the Environment of Peru (PNCB/MINAM). The official forest loss data are produced annually by  PNCB/MINAM.

**According to official PNCB/MINAM data, forest loss in 2016 was 164,662 hectares. The average of the last 5 years (2012-16) was 159,688 hectares.

Coordinates

A. -8.289977,-75.415649
B. -12.969013,-69.918365; -12.872639,-70.263062
C. -11.304257,-69.635468
D. -6.26539,-75.800171
E. -4.972954,-78.21167

References

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

Citation

Finer M, Mamani N, García R, Novoa S (2018) Deforestation Hotspots in the Peruvian Amazon, 2017. MAAP: 78.