MAAP #91: Introducing PeruSAT-1, Peru’s new High-resolution Satellite

PeruSat-1. Credit: Airbus DS

In September 2016, Peru’s first satellite, PeruSAT-1, launched. It is Latin America’s most powerful Earth observation satellite, capturing images at a resolution of 0.70 meters.

The cutting-edge satellite was constructed by Airbus (France) and is now operated by the Peruvian Space Agency, CONIDA.

The organization Amazon Conservation was granted early access to the imagery to boost efforts related to near real-time deforestation monitoring.

Below, we present a series of PeruSAT images that demonstrate their powerful utility in terms of detecting and understanding deforestation in the Peruvian Amazon.

 

 

 

 

Gold Mining

We have reported extensively on the continuing gold mining deforestation in the southern Peruvian Amazon (see MAAP #87). We are now using PeruSAT to identify active and emerging mining deforestation fronts. For example, in the following images of an active mining zone, it is possible to clearly observe the environmental impact, and identify mining camps and wastewater pools.

PeruSAT-1 image of active gold mining. Data: ®CONIDA (2018), Distribution CONIDA, Peru; All rights reserved.
PeruSAT-1 image (zoom) of active gold mining. Data: ®CONIDA (2018), Distribution CONIDA, Peru; All rights reserved.

Agricultural Expansion

The following image shows a papaya plantation that appeared after a recent deforestation event near the Interoceanic highway in the southern Peruvian Amazon (Mavila, Madre de Dios). See MAAP #42 for more details on papaya emerging as new deforestation driver in this area.

PeruSAT-1 image of papaya plantation. Data: ®CONIDA (2018), Distribution CONIDA, Peru; All rights reserved.

Logging Roads

The following image shows, in high-resolution, a new logging road crossing primary forest in the southern Peruvian Amazon (district of Iñapari, Madre de Dios).

PeruSAT-1 image of logging road. Data: ®CONIDA (2018), Distribution CONIDA, Peru; All rights reserved.

Citation

Villa L, Finer M (2018) Introducing PeruSAT-1, Peru’s new High-resolution Satellite. MAAP: 91.

MAAP #90: Using Drones to monitor Deforestation and Illegal Logging

Drone types: helipcopter and fixed-wing (plane)

For the past three years, the organization Amazon Conservation has been working to establish a sustainable, local-based drones program for environmental monitoring in the southern Peruvian Amazon (Madre de Dios region).

This program is based on two types of drones, multi-rotor (helicopter style) and fixed-wing (airplane style).

One of the main objectives is to improve the near real-time monitoring of deforestation and illegal logging.

The monitoring is currently focused on three priority areas: 1) Brazil nut concessions, 2) forestry concessions of the local association ACOMAT, and 3) along the Interoceanic Highway (see Base Map).

Below, we show a series of drone images that we have used to identify the drivers of recent deforestation events. These drivers include gold mining, agriculture, illegal logging, cattle pasture, and natural forest loss.

Base Map. Priority areas of the Amazon Conservation drones initiative.

Interoceanic Highway

In March 2018, in collaboration with the organization ProPurús, we realized drone flights along the Interoceanic Highway in an effort to demonstrate the possible threats of building a new road along the border with Brazil (see MAAP #76). The following images show the two main threats to the area: gold mining and small/medium-scale agriculture (<50 hectares).

A. Drone image: gold mining.
B. Drone image: Deforestation from agriculture (corn)

Brazil Nut Concessions

In 2018, Amazon Conservation launched a new project, funded by Google Challenge, to develop a monitoring program for Brazil nut concessions covering a million hectares (2.47 million acres) in southern Peru. For example, the following image shows the invasion of a papaya plantation that caused the recent deforestation of five acres inside a concession.

C. Drone image: Invasión of papaya in Brazil nut concession.

ACOMAT Forestry Concessions

Since 2017, Amazon Conservation has been working on a project, financed by the Norwegian Agency for Development Cooperation (NORAD), to improve the monitoring of forest concessions of the local association ACOMAT (Association of Timber and Non-Timber Forest Concessionaires of the Provinces from Manu and Tambopata). The following images show examples of forest loss and degradation due to illegal logging, cattle grazing, natural loss (windstorm), and gold mining.

D. Drone image: illegal logging.
E. Drone image: cattle pasture.
F. Drone image: natural forest loss from windstorm.
G. Drone image: gold mining.

Citation

Garcia R, Novoa S, Castañeda C, Rengifo P, Jimenez M, Finer M (2018) Using Drones to monitor Deforestation and Illegal Logging. MAAP: 90.

MAAP #85: Illegal Logging in the Peruvian Amazon, and how Satellites can help address it

Example of new logging road in the Peruvian Amazon. Data: Planet

We propose a new tool to address illegal logging in the Peruvian Amazon: using cutting-edge satellites to monitor logging road construction in near real-time.

Illegal logging in the Amazon is difficult to detect because it is selective logging of individual valuable trees, not large clear-cuts.

However, a new generation of satellites can quickly detect new logging roads, which in turn may indicate the leading edge of illegal logging.

Here, we analyzed satellite imagery to identify all new logging roads built in the Peruvian Amazon over the past three years (2015-17).

We then show how it is possible to track logging road construction in near-real time, using three satellite-based systems: GLAD alerts, Sentinel-1 (radar satellites), and Planet (optical satellites).

 

 

 

 

 


The Technology

GLAD alerts. Source: GFW

GLAD alerts quickly detect areas of recent forest loss (based on 30 meter resolution Landsat imagery) and highlight those pixels. For example, the image on the right shows GLAD alerts for a recent logging road. The satellites described below can then zoom in on these highlighted areas and continue the monitoring in near real-time.

The European Space Agency’s Sentinel-1 satellites freely offer a new image every 12 days no matter the weather conditions, as radar technology allows it to penetrate clouds (see MAAP #79).

The company Planet has a fleet of 175+ mini satellites, lined up like pearls in a necklace, that are able to capture a high-resolution optical image almost daily, though clouds remain an issue (see MAAP #59).

 

 

 

 

Key Findings

Base Map. Logging roads in the Peruvian Amazon. Data: MAAP, SERNANP, IBC. Click to enlarge.

The Base Map illustrates the location of all logging roads built in the Peruvian Amazon since 2001.

We estimate the construction of 1,365 miles (2,200 km) of logging roads during the last three years (2015-17). We indicate these roads in red.

Note that the roads are concentrated in three zones:

  • Southern Loreto, between Cordillera Azul and Sierra del Divisor National Parks;
  • Southern Ucayali; and
  • Northeast Madre de Dios.

Another important finding is the potential rapid speed of logging road construction: up to 1.5 miles (2.5 km) per week.

Next, we focus on two emblematic logging roads (near Sierra del Divisor and Cordillera Azul National Parks, respectively) to demonstrate the feasibility of near real-time monitoring based on Sentinel-1 and Planet satellites.

 

 

 

 

 

A. Logging Road near Sierra del Divisor

Image A1 is a GIF that shows a series of radar images (Sentinel-1) of the construction of a logging road between 2015 and 2017 just north of Sierra del Divisor National Park. The length of the road is 43 miles (69 km). Image A2 is a Planet image showing the status of the road as of the end of 2017.

Image A1. Construction of logging road near Sierra del Divisor. Data: ESA
Image A2. Logging road near Sierra del Divisor. Data: Planet

B. Logging Road near Cordillera Azul

Image B1 is a GIF that shows a series of radar images (Sentinel-1) of the construction of a logging road between 2015 and 2017 east of Cordillera Azu National Park. The length of the road is 33 miles (53 km). Image B2 is a Planet image showing the status of the road as of the end of 2017.

Image B1. Construction of logging road near Cordillera Azul. Data: ESA
Image B2. Logging road near Cordillera Azul. Data: Planet

Notes

Not all illegal logging requires roads, but logging roads may indicate some of the most organized, financed, and large-scale operations.

Coordinates

Zona A: -6.966982,-74.6521
Zona B: -7.650428,-75.552979

Citation

Villa L, Finer M (2018) Illegal Logging in the Peruvian Amazon, and how Satellites can help. MAAP: 85.

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

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 #68: 2017 DEFORESTATION HOTSPOTS IN THE PERUVIAN AMAZON (Part 2)

Image 68. Base map. Data: PNCB/MINAM, UMD/GLAD, SERNANP.

In a previous report, MAAP #65, we presented information about deforestation hotspots in 2017 in the Peruvian Amazon, based on early warning alert data from January until mid-July.

Between July and August, the amount of alerts greatly increased, likely due to arrival of the dry season. Thus, this report includes new updated data until mid-August.*

We find new deforestation hotspots in the regions of Madre de Dios and Ucayali (see base map).** At the national level, we now estimate the forest loss of 111,200 acres (45,000 hectares) thus far in 2017 (thru August 17).***

Below, we present satellite imagery of the following hotspots:

– La Pampa, Madre de Dios (Inset A)
– Guacamayo, Madre de Dios (Inset F)
– Iberia, Madre de Dios (Inset G)
– South of Sierra del Divisor, Ucayali (Inset H)
– Nueva Requena, Ucayali (Inset I)

**The data were generated by the National Program of Forest Conservation for Climate Change Mitigation, Peruvian Ministry of Environment (PNCB/MINAM).

**See Hotspots A-E in MAAP #65

***We emphasize that our calculations are just estimates. Official forest loss data are produced annually by the Peruvian Ministry of Environment.

 

La Pampa, Madre de Dios (Inset A)

Illegal gold mining deforestation continues to expand in the buffer zone of Tambopata National Reserve in the southern Peruvian Amazon. The Peruvian Government has conducted several interventions this year, most notably in July. However, between July and August we documented the additional loss of 67 acres (27 hectares), increasing the 2017 total deforestation in this zone to 1,280 acres (517 hectares). Image 68a is a GIF illustrating the gold mining deforestation from January to September 2017.

Image 68a. Data: Planet

Guacamayo, Madre de Dios (Inset F)

North of La Pampa, in another gold mining zone, known as Guacamayo, we have documented the rapid deforestation of 182 acres (74 hectares). This newly deforested area is located next to the mining zone (within a forestry concession), and appears to be caused by agricultural activity.

Image 68f. Data: Planet

Iberia, Madre de Dios (Inset G)

Around the  town of Iberia, located along the Interoceanica highway near the border with Brazil, has recently become a major deforestation hotspot (see MAAP #28 and MAAP #47). Between June and August 2017, we detected the deforestation of 1,075 acres (435 hectares). Much of this deforestation is within forestry concessions, indicating that the concessions have been invaded. The deforestation appears  to be caused by agriculture (according to local sources, the clearing is for corn plantations).

Image 68g. Data: Planet.

South of Sierra del Divisor, Ucayali (Inset H)

In the central Peruvian Amazon, just south of Sierra del Divisor National Park, we detected the new construction of 25 km of logging roads in the forestry concessions surrounding the park. We also detected the deforestation of 138 acres (56 hectares), close to the National Park’s limit for what appears to be agricultural activity.

Image 68h. Data: Planet, SERNANP

Nueva Requena, Ucayali (Inset I)

Also in the central Peruvian Amazon, in the Nueva Requena district near two controversial oil palm plantations (MAAP #41), we detected the deforestation of 1,130 acres (457 hectares) in state forestry lands (known as Permanent Production Forest). This includes 26 km of new logging and agricultural roads. It is important to note that this area was recently in the news regarding the killing of six farmers over land rights dispute.

Image 68i. Data: Planet

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 (2017) 2017 Deforestation Hotspots in the Peruvian Amazon (Part 2). MAAP: 68.

MAAP 59: Power of “Small Satellites” from Planet

Image 59a. Source: Planet

The company Planet is pioneering the use of high-resolution “small satellites” (Image 59a). They are a fraction of the size and cost of traditional satellites, making it possible to produce and launch many as a large fleet. Indeed, Planet now operates 149 small satellites, known as Doves, the largest fleet in history. The Doves capture color imagery at 3-5 meter resolution, and will line up (like a string of pearls) to cover everywhere on Earth’s land area every day.

Over the past year, MAAP* has demonstrated the power of Planet imagery to monitor deforestation and degradation in near real-time in the Amazon. A consistent flow of new, high-resolution imagery is needed for this type of work, making Planet’s fleet model ideal. Below, we provide a recap of key MAAP findings based on Planet imagery, for a diverse set of cases including gold mining, agriculture deforestation, logging roads, wildfire, blowdowns, landslides, and floods.**

*MAAP has been fortunate to have access to Planet imagery via the Ambassador program.
**Note: In the images below, the red dot () indicates the same location across time between panels.

Illegal Gold Mining

Image 59b. Data: Planet, SERNANP

We used Planet imagery to closely track the recent illegal gold mining invasion of Tambopata National Reserve, a mega-diverse protected area in the southern Peruvian Amazon. Image 59b is a GIF showing the full invasion: from the initial invasion in January 2016, to subsequent deforestation advances in July and November 2016, and the most recent image in March 2017. The total deforestation from the invasion is over 1,235 acres. These images were an important resource for authorities, civil society, and the media responding to the situation.

Illegal Agriculture Deforestation

Image 59c. Data: Planet, SERNANP

We used Planet imagery to document numerous cases of small-scale deforestation for illegal agricultural practices. These examples are important because, cumulatively, small-scale deforestation represents the vast majority (80%) of forest loss events in the Peruvian Amazon (see MAAP Synthesis #2). Image 59c shows the rapid appearance of several new agricultural plots between May (left panel) and June (right panel) 2016 within an important natural protected area in the central Peruvian Amazon, El Sira Communal Reserve.

Logging Roads

Image 59d. Data: Planet

We used Planet imagery to show the rapid construction of logging roads. For example, Image 59d shows the construction of a logging road in the buffer zone of an important national park in the central Peruvian Amazon (Cordillera Azul) between November 2015 (left panel) and July 2016 (right panel).

Wildfire

Image 59e. Data: Planet

Planet imagery was also an important resource to monitor the intense wildfires in Peru last year. Image 59e shows forest loss from an escaped agricultural fire in the northern Peruvian Amazon between May (left panel) and October (right panel) 2016. Note the imagery even caught the smoke from the fires in September (middle panel).

Blowdowns

Image 59f. Data: Planet

We used Planet to help document a little-known, but important, type of natural forest loss in the Peruvian Amazon: blowdown due to strong winds from localized storms known as “hurricane winds.” Image 59f shows a high-resolution view of a recent major blowdown event between January (left panel) and August (right panel) 2016 in the northern Peruvian Amazon.

Landslides

Image 59g. Data: Planet

Planet imagery recently revealed an interesting natural phenomenon: a major landslide within a remote, rugged section of Peru’s newest national park, Sierra del Divisor. Image 59g shows the area between October 2016 (left panel) and March 2017 (right panel).

Floods

Image 59h. Data: Planet

Finally, Planet imagery played a key role in monitoring the impacts of the recent deadly floods that hit the northern Peruvian coast. Image 59h shows the rapid flooding of agricultural plots along a river in northern Peru between February (left panel) and March (right panel) 2017.

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, Mascaro J (2017) Power of “Small Satellites” from Planet. MAAP: 59.

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

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.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.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

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

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

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.

Environmental Investigation Agency EIA (2015) Deforestation by Definition.

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

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

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

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 #43: Early Warning Deforestation Alerts in the Peruvian Amazon, Part 2

In the previous MAAP #40, we emphasized the power of combining early warning forest loss GLAD alerts with analysis of high-resolution satellite imagery as part of a comprehensive near real-time deforestation monitoring system for the Peruvian Amazon.

In the current MAAP, we present 3 new examples of this system across different regions of Peru. Click on the images below to enlarge.

Example 1: Illegal Gold Mining in buffer zone of Bahuaja Sonene National Park (Madre de Dios)
Example 2: Logging Road in buffer zone of Cordillera Azul National Park (Ucayali/Loreto)
Example 3: Deforestation in Permanent Production Forest (Ucayali)

Example 1: Illegal Gold Mining in buffer zone of Bahuaja Sonene National Park (Madre de Dios)

In the previous MAAP #5, we discussed illegal gold mining deforestation along the upper Malinowski River, located in the buffer zone of the Bahuaja Sonene National Park. As seen in Image 43a, the upper Malinowski is just upstream of the areas invaded by illegal gold mining in Tambopata National Reserve and its buffer zone (see MAAP #39 and #31, respectively). In MAAP #5, we documented the deforestation of more than 850 hectares between 2013 and 2015 along the upper Malinowski. Here, we show that gold mining deforestation continues in 2016, with an additional loss of 238 hectares (806 acres). Insets A-C correspond to the areas featured in the high-resolution zooms below.

Image 43a. Data: UMD/GLAD, Hansen/UMD/Google/USGS/NASA, NASA/USGS, SERNANP
Image 43a. Data: UMD/GLAD, Hansen/UMD/Google/USGS/NASA, NASA/USGS, SERNANP

The following Images 43b-d show, in high-resolution, the rapid expansion of gold mining deforestation between August/September 2015 (left panel) and July/August 2016 (right panel). The yellow circles indicate the main areas of deforestation between the images.

Imagen 43b. Datos: Planet, Digital Globe (Nextview)
Image 43b. Data: Planet, Digital Globe (Nextview)
Imagen 43c. Datos: Planet, Digital Globe (Nextview)
Image 43c. Data: Planet, Digital Globe (Nextview)
Imagen 43d. Datos: Planet, Digital Globe (Nextview)
Image 43d. Data: Planet, Digital Globe (Nextview)

Example 2: Logging Road in buffer zone of Cordillera Azul National Park (Ucayali/Loreto)

In the previous MAAP #18, we discussed the proliferation of logging roads in the central Peruvian Amazon in 2015. Here, we show the expansion of two of these logging roads in 2016. (see Image 43e). Red indicates construction during 2016 (47 km). Insets A1-A3 correspond to the areas featured in the high-resolution zooms below. Note that the northern road (Inset A3) is within the buffer zone of Cordillera Azul National Park. Evidence suggests that this road is not legal because it extends out of the permited area (see MAAP #18 for more details).

Imagen 43e. Datos: UMD/GLAD, Hansen/UMD/Google/USGS/NASA, SERNANP
Image 43e. Data: UMD/GLAD, Hansen/UMD/Google/USGS/NASA, SERNANP

The following images show, in high-resolution, the rapid construction of these logging roads. Image 43f shows the construction of part of the southern road (Inset A1), and the deforestation for a nearby agricultural parcel, between April (left panel) and July (right panel) 2016. Image 43g shows the construction of 1.8 km in just three days along this same road (Inset A2) between July 21 (left panel) and July 24 (right panel) 2016.

Imagen 43f. Datos: Planet
Image 43f. Data: Planet
Imagen 43g. Datos: Planet
Image 43g. Data: Planet

Image 43h shows the construction of 13 km on the northern road between November 2015 (left panel) and July 2016 (right panel) within the buffer zone of the Cordillera Azul National Park.

Imagen 43h. Datos: Planet
Image 43h. Data: Planet

Example 3: Deforestation in Permanent Production Forest  (Ucayali)

Image 43i shows recent deforestation of 136 hectares (336 acres) in 2016 in southern Ucayali region within areas classified as Permanent Production Forest and Foresty Concession. These types of areas are generally zoned for sustainable forestry uses, not clear-cutting, thus we question the legality of the deforestation. Tables A-B correspond to the areas featured in the high-resolution zooms, below.

Imagen 43i. Datos: UMD/GLAD, Hansen/UMD/Google/USGS/NASA, MINAGRI
Image 43i. Data: UMD/GLAD, Hansen/UMD/Google/USGS/NASA, MINAGRI

Image 43j shows deforestation within a section of Permanent Production Forest, and Image 43k shows deforestation within a section of Forestry Concession.

Imagen 43j. Datos: Planet
Image 43j. Data: Planet
Imagen 43k. Datos: Planet
Image 43k. Data: Planet

Citation

Finer M, Novoa S, Goldthwait E (2016) Early Warning Deforestation Alerts in the Peruvian Amazon, Part 2. MAAP: 43.

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

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.

MAAP #18: Proliferation of Logging Roads in the Peruvian Amazon

MAAP articles #3 and #15 detailed the construction of several new logging roads in the central Peruvian Amazon. Here in MAAP 18, we provide a more comprehensive analysis of the proliferation of logging roads in this section of the Amazon. In Image 18a, we show a high resolution example of a new logging road in this area with active construction during 2015 (see Inset A1 in Image 18c for more context).

new18a v2
Image 18a. New logging road in the Peruvian Amazon. Data: WorldView-2 of Digital Globe (NextView).

Image 18b illustrates the location of all identified logging roads in the central Peruvian Amazon (southern Loreto and northern Ucayali). Most of these roads are located along the Ucayali River and its headwater tributaries. The left panel highlights just the logging roads, while the right panel also includes protected areas, native communities, and logging concessions.

Image 18b. Logging roads in the central Peruvian Amazon. Data: SERNANP, IBC, USGS, MINAGRI.
Image 18b. Logging roads in the central Peruvian Amazon. Data: SERNANP, IBC, USGS, MINAGRI.

In Image 18b, we documented the construction of 1,134 km of logging roads between 2013 and 2015 in the central Peruvian Amazon. Of this total, 538 km is in the matrix of logging concessions and native communities in southern Ucayali, 226.1 km is in undesiganted areas in southern Loreto, 210 km is in the buffer zone of Cordillera Azul National Park, and 159 km is around the new Sierra del Divisor National Park.

Note that the buffer zone of Cordillera Azul National Park and surroundings of Sierra del Divisor National Park contain logging concessions and native communities, thus the responsibility of forest authority is the regional government.

Determining the legality of these roads is complex. As the right panel highlights, 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).

Below, we focus on the logging roads in the northern section of Image 18b (see Inset A).

Zoom A: Logging Roads in Southern Loreto/Northern Ucayali

Image 18c. Logging roads in southern Loreto/northern Ucayali. Data: SERNANP, IBC, USGS, MINAGRI.
Image 18c. Logging roads in southern Loreto/northern Ucayali. Data: SERNANP, IBC, USGS, MINAGRI.

Image 18c is a zoom of the logging roads shown in the northern section of Image 18a (Inset A), located in southern Loreto and northern Ucayali. It shows five primary areas of interest. Both Insets A1 and A2 correspond to new roads within the southeast buffer zone of the Cordillera Azul National Park with active construction in 2015 (see below for more details).

Insets A3, A4, and A5 correspond to roads with active construction between 2013 and 2015 that have already been featured on MAAP. Inset 3 includes a logging road in the northeast sector of the buffer zone of Cordillera Azul National Park (see MAAP #3 for more details). Insets 3 and 5 show logging roads around the new Sierra del Divisor National Park (see MAAP #15 and MAAP #7 for more details).

Zoom A1: Logging Roads in Nuevo Irazola

Image 18d provides more details about a new logging road with very recent construction within the southeast buffer zone of Cordillera Azul National Park (See Inset A1 in Image 18C for context). This road has grown 68 km between 2013 and 2015, with more than half of this construction occurring over the past year. According to information obtained from the forestry department within the Regional Government of Ucayali (PRMRFFS), the native community of Nuevo Irazola made a logging permission request for industrial and/or commercial use and prepared an Annual Operating Plan. However, a high-resolution (0.5 m) image shows a recent stretch of the road exceeds the area requested for forestry activities (see Image 18d).

MAAP_Ucayali_roads_18c_vALYSSA
Image 18d. High-resolution image of a new forest road in the southeast buffer zone of Cordillera Azul National Park. Data: WorldView-2 of Digital Globe (NextView).

Zoom A2: Rapid Expansion of a Logging Road

Image 18e. Rapid construction of a forest road in the southeast buffer zone of Cordillera Azul National Park. Data: USGS.
Image 18e. Time series of a forest road in the southeast buffer zone of Cordillera Azul National Park. Data: USGS.

Image 18e illustrates the rapid expansion of another forest road located in the southeast section of the Cordillera Azul National Park buffer zone (See Inset A2 in Image 18C for context). We documented the construction of 29.1 km during the six weeks between September 10 (left panel) and October 20 (right panel), a rate of nearly five kilometers per week. The legality of this road is currently unknown, but note that it is extending in the direction of a forestry concession.

Citation

Novoa S, Fuentes MT, Finer M, Pena N, Julca J (2015) Proliferation of Logging Roads in the Peruvian Amazon. MAAP #18.

Note: MAAP #18 is a collaborative effort between Amazon Conservation Association (ACA), Conservación Amazónica (ACCA), and the Centro de Conservación Investigación y Manejo de Áreas Naturales (CIMA).