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MAAP #27: United Cacao Continues Deforestation of Primary Forest In Tamshiyacu (Loreto, Peru)

Posted on by dcadmin

Deforestation continues to increase in the land owned and operated by United Cacao  near the town of Tamshiyacu in the northern Peruvian Amazon. Since 2013, we have documented the deforestation of 2,380 hectares (5,880 acres) related to this project, the vast majority at the expense of primary forest*. Of this total, 250 hectares were clear-cut after the Peruvian Ministry of Agriculture ordered the “paralyzation” of the company’s agricultural activities in December 2014**. Here in MAAP #27, we present evidence that indicates the deforestation related to this project will continue to expand in the coming months.

Image 27a. Data: USGS.
Image 27a. Data: USGS.

Image 27a shows a series of satellite images (Landsat) that shows the advance of deforestation in in the northern part of the United Cacao project. The left panel shows this area contained a remnant of primary forest (see dark green color in Inset A) in July 2014. The central panel shows that, by September 2015, a new access road network was constructed in the southern part of this area (see pink color, which indicates recently deforested areas). Finally, the right panel shows that in February 2016 (the most recent image), the southern part of that same area is now deforested, while a new access road network has been constructed to the north. Thus, if this pattern continues (access roads followed by large-scale deforestation), we predict that deforestation will soon occur in this northern area.

High-Resolution View

Image 27b shows, in high-resolution, the deforestation of primary forest between June (left panel) and November (right panel) of 2015 in the northern part of the United Cacao project described above (see red box in both images). The image also shows the area of primary forest that is now threatened with additional deforestation (see yellow box in both images).

Image 27b. Data: WorldView-3 from Digital Globe (NextView).
Image 27b. Data: WorldView-3 from Digital Globe (NextView).

Deforestation Trend

The graph to the right shows the trend of accumulated deforestation in the United Cacao project area between 2012 and February 2016. The company began operations in early 2013, the same year as the large increase in deforestation. Also note that deforestation increased in 2015 despite the Ministry of Agriculture’s “paralyzation” order in late 2014.

Data: PNCB/MINAM, Hansen/UMD/Google/USGS/NASA, Hansen et al 2016 (ERL)***
Data: PNCB/MINAM, Hansen/UMD/Google/USGS/NASA, Hansen et al 2016 (ERL)***

GLAD weekly alerts

It is worth emphasizing how quickly and precisely the new GLAD weekly alert system picked up the new access road construction in 2016 (see Image 27c).

Image 27c. Data: UMD/GLAD, GFW, UrtheCast
Image 27c. Data: UMD/GLAD, GFW, UrtheCast

Notes

*According to the Supreme Decree (No. 018-2015-MINAGRI) approving the Regulations for Forest Management under the framework of the new 2011 Forestry Act (No. 29763), the official definition of primary forest in Peru is: “Forest with original vegetation characterized by an abundance of mature trees with species of superior or dominant canopy, which has evolved naturally.” Using methods of remote sensing, our interpretation of that definition are areas that from the earliest available image (in this case, from 1985) are characterized by dense closed-canopy coverage and experienced no major clearing events. See MAAP #9 and MAAP #2 for more details.

** Resolución de Dirección General N° 462-2014-MINAGRI-DVDIAR-DGAAA. A recent press release from the organization Environmental Investigation Agency reports that the order is still in effect (http://eia-global.org/blog/united-cacao-linked-companies-ordered-to-stop-operations-by-peruvian-author).

***Hansen, M.C., A. Krylov, A. Tyukavina, P.V. Potapov, S. Turubanova, B. Zutta, S. Ifo, B. Margono, F. Stolle, and R. Moore (2016) Humid tropical forest disturbance alerts using Landsat data.  Environ. Res. Lett. 11: 034008. Accessed through Global Forest Watch: www.globalforestwatch.org

Citation

Finer M, Novoa S (2016) United Cacao Continues Deforestation of Primary Forest in Tamshiyacu (Loreto, Peru). MAAP: #27.

 

MAAP #26: Deforestation Hotspots in the Peruvian Amazon, 2015

Posted on by dcadmin

Thanks to the newly launched GLAD alerts (developed by the University of Maryland and Google1, and presented by Global Forest Watch), we now have weekly access to high-resolution forest loss data across Peru. Here in MAAP #26, we analyze the first batch of this data to better understand deforestation patterns in the Peruvian Amazon in 2015. In the coming weeks and months, we will use this map as a base for investigating major hotspots of forest loss in the country.

According to the GLAD alert data, total estimated forest loss in Peru in 2015 was 158,658 hectares (392,050 acres). If confirmed, that represents the second highest total on record, behind only 2014 (177,500 hectares).

To better understand where the GLAD alert data was concentrated in 2015, we conducted kernel density estimation, a type of analysis that calculates the magnitude per unit area of a particular phenomenon (in this case, forest loss). Image 26a shows the kernel density map for forest loss in the Peruvian Amazon in 2015. It reveals that recent deforestation was concentrated in a number of hotspots in the departments of Huánuco, Madre de Dios, and Ucayali.

Note that in MAAP #25, we conducted this same type of analysis for 2012 – 2014 forest loss data. Thus, with this latest analysis we can see how deforestation trends shifted in 2015.

Insets A and B highlight an area in central Peru (department of Ucayali) where deforestation intensified in 2015. See below for high-resolution images showing the deforestation in these areas. In the coming weeks and months, we will be publishing additional articles highlighting other key 2015 deforestation hotspots.

Image 26a. Kernel density map for forest loss in the Peruvian Amazon in 2015. Data: Hansen et al 2016 (ERL).
Image 26a. Kernel density map for forest loss in the Peruvian Amazon in 2015. Data: Hansen et al 2016 (ERL).

Inset A

Image 26b shows detailed deforestation information for the area indicated in Inset A (from Image 26a). Note the extensive 2015 deforestation just to the west of two large-scale oil palm plantations (201 hectares, see pink areas).

Image 26b. 2000-15 deforestation for area in Inset A. Data: Hansen et al 2016 (ERL), PNCB/MINAM, Hansen/UMD/Google/USGS/NASA, USGS (Landsat 8)
Image 26b. 2000-15 deforestation for area in Inset A. Data: Hansen et al 2016 (ERL), PNCB/MINAM, Hansen/UMD/Google/USGS/NASA, USGS (Landsat 8)

Further below, Image 26c shows a high-resolution satellite image of the area in Inset A1 before (left panel) and after (right panel) the recent deforestation events.

Image 26c. High-resolution view of area in Inset A1 before (left panel) and after (right panel) recent deforestation events. Data: WorldView-2 de Digital Globe (NextView).
Image 26c. High-resolution view of area in Inset A1 before (left panel) and after (right panel) recent deforestation events. Data: WorldView-2 de Digital Globe (NextView).

 

Inset B

Image 26d shows detailed deforestation information for the area indicated in Inset B (from Image 26a). Note the extensive 2015 deforestation along the Aguaytia River (164 hectares, see pink areas). Recent deforestation (2012-14) appears to be associated with agricultural and logging activities.

Image 26d. 2000-15 deforestation for area in Inset B from Image Xa. Data: Hansen et al 2016 (ERL), PNCB/MINAM, Hansen/UMD/Google/USGS/NASA, USGS (Landsat 8)
Image 26d. 2000-15 deforestation for area in Inset B from Image Xa. Data: Hansen et al 2016 (ERL), PNCB/MINAM, Hansen/UMD/Google/USGS/NASA, USGS (Landsat 8)

Further below, Image 26e shows a high-resolution satellite image of the area in Inset B1 before (left panel) and after (right panel) the recent deforestation events.

Image 26e. High-resolution view of area in Inset B1 before (left panel) and after (right panel) recent deforestation events. Data: WorldView-2 de Digital Globe (NextView).
Image 26e. High-resolution view of area in Inset B1 before (left panel) and after (right panel) recent deforestation events. Data: WorldView-2 de Digital Globe (NextView).

Methodology

We conducted this analysis using the Kernel Density  tool from Spatial Analyst Tool Box of ArcGis 10.1 software. Our goal was to emphasize local concentrations of deforestation in the raw data while still representing overarching patterns of deforestation between 2012 and 2014. We accomplished this 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.

Reference

1 Hansen, M.C., A. Krylov, A. Tyukavina, P.V. Potapov, S. Turubanova, B. Zutta, S. Ifo, B. Margono, F. Stolle, and R. Moore. Humid tropical forest disturbance alerts using Landsat data. Environmental Research Letters, in press. Accessed through Global Forest Watch on March 2, 2016. www.globalforestwatch.org

Citation

Finer M, Novoa S, Snelgrove C (2015) 2015 Deforestation Hotspots in the Peruvian Amazon. MAAP: 26.

Deforestation Hotspots in The Peruvian Amazon, 2015

Posted on by dcadmin

Thanks to the newly launched GLAD alerts (developed by the University of Maryland and Google1, and presented by Global Forest Watch), we now have weekly access to high-resolution forest loss data across Peru. Here in MAAP #26, we analyze the first batch of this data to better understand deforestation patterns in the Peruvian Amazon in 2015. In the coming weeks and months, we will use this map as a base for investigating major hotspots of forest loss in the country.

MAAP: Near-Real Time Deforestation Monitoring Aids Intervention in Illegal Gold Mining

Posted on by Ana Folhadella

In April 2015, ACA launched a cutting-edge near real-time deforestation monitoring system for the Andean Amazon known as MAAP (maaproject.org). MAAP analyzes high resolution satellite imagery to make precise and timely deforestation information available to the policy makers and the public. Over the past year, 25 deforestation case studies have been published on the MAAP portal, on important topics including illegal mining, oil palm plantation expansion, and the importance of protected areas.

Most recently, we documented an illegal gold mining invasion of an important protected area in the southern Peruvian Amazon (Tambopata National Reserve). Peruvian officials used this information to plan an intervention against the illegal mining activity.

ACA Supports Conservation and Cultural Heritage at the Indigenous Amarakaeri Reserve

Posted on by Ana Folhadella

At nearly 1 million acres, the Amarakaeri Communal Reserve protects not only vast expanses of tropical forest in one of the most biodiverse regions of the world, but also the cultural heritage and traditional ecological knowledge of the Matsiguenka, Yine and Harakbut indigenous groups who for centuries have called this forest their home.  With support from ACA and its partners, these indigenous groups, living in 10 communities across the region, are working to ensure responsible management of the reserve for years to come.

ACA Supports Conservation and Cultural Heritage at the Indigenous Amarakaeri Reserve Group Photo
With ACA’s support, the Shintuya indigenous community is one of 10 communities having an active role in the management and decision-making for their ancestral lands through the process of updating the master plan for the Amarakaeri Communal Reserve.

The communities are in a process with Peru’s National Park Service and other partners to update the reserve’s master plan, the document that guides the management of its natural resources. As part of the planning process, the communities are presenting a cultural map of sacred sites and ancestral landmarks, developed through a previous 10-year effort, with the goal of incorporating them into the master plan of the reserve. Through this process, the community members have an active voice in the management and decision-making for their ancestral lands.

The master plan process is part of a three year project funded by USAID to build capacity of indigenous leaders and communities in conflict resolution and effective reserve management.

To find out more about our work with communities and conservation corridors, visit our website at: www.amazonconservation.org 

ACA Hosts Beetle Expert Who Discovers Over 1,000 New Species   

Posted on by Ana Folhadella

ACA Hosts Beetle Expert Who Discovers Over 1,000 New Species   

Caroline Chaboo, Ph.D., (left) is an assistant professor of evolutionary biology and a curator of the Biodiversity Institute at the University of Kansas. She has developed deep beetle expertise through field work in some 25 different countries and through many years of research and publishing scientific papers on the subject. During the past decade, she has focused her research on Peru in collaboration with ACA.

Back in 2006, Chaboo applied for an ACA fellowship and received one. “That is how I became hooked on doing my field work in Peru in conjunction with ACA. Also, ACA has three field stations in Peru, and they encompass different forest types – rainforest, bamboo forest, riverine forest, cloud forest, and even alpine grasslands. Now I conduct my research at all three field stations and return year after year to them in order to continue it.” 

Scientists weren’t sure how many beetle species were in Peru until recently when a series of scientific papers titled “Beetles of Peru” was published and announced that the number is more than 10,000. The project reflects a decade of inventory, led by Chaboo who along with 40 beetle experts from around the world believe that they have discovered more than 1,000 new species at ACA’s biological stations and around Peru.

               

True, field work in the ACA stations in Peru has its challenges, Chaboo admitted. “It is time-consuming and expensive to conduct these large expeditions to remote places. And I always take groups of students with me. I teach them how to hike and navigate through a forest, how to trap beetles in various micro-habitats. But for both them and myself, it is a joyous experience, hiking, running, exploring, and discovering nature and evolution first-hand, not just from a textbook.”

MAAP #25: Deforestation Hotspots in the Peruvian Amazon, 2012-2014

Posted on by dcadmin

Deforestation continues to increase in the Peruvian Amazon. According to the latest information from the Peruvian Environment Ministry1, 2014 had the highest annual forest loss on record since 2000 (177,500 hectares, or 438,600 acres per year). 2013 and 2012 had the third and fourth highest annual forest loss totals, respectively (behind only 2009).

 

Source: PNCB/MINAM
Source: PNCB/MINAM

To better understand where this deforestation is concentrated, we conducted kernel density estimation. This type of analysis calculates the magnitude per unit area of a particular phenomenon (in this case, forest loss).

Image 25a shows the kernel density map for forest loss in the Peruvian Amazon between 2012 and 2014 and reveals that recent deforestation is concentrated in a number of “hotspots” in the departments of Loreto, San Martin, Ucyali, Huanuco, and Madre de Dios.

Insets A-D highlight four areas with high densities of forest loss described in previous MAAP articles. We are currently studying the other high density deforestation areas not included in the insets.

Image 25a. Kernel density map for forest loss in the Peruvian Amazon between 2012 and 2014. Data: PNCB/MINAM, Hansen/UMD/Google/USGS/NASA.
Image 25a. Kernel density map for forest loss in the Peruvian Amazon between 2012 and 2014. Data: PNCB/MINAM, Hansen/UMD/Google/USGS/NASA.

Inset A: Cacao in Loreto

Image 25b. Deforestation for cacao in northern Peru between December 2012 (left panel) and September 2013 (center panel) and cumulative 2012-14 (right panel). Data: USGS, PNCB/MINAM, Hansen/UMD/Google/USGS/NASA
Image 25b. Deforestation for cacao in northern Peru between December 2012 (left panel) and September 2013 (center panel) and cumulative 2012-14 (right panel). Data: USGS, PNCB/MINAM, Hansen/UMD/Google/USGS/NASA

Inset A (from Image 25a) indicates the deforestation of over 2,000 hectares (4,940 acres) on property owned by the company United Cacao (through its wholly owned Peruvian subsidiary, Cacao del Peru Norte) near the town of Tamshiyacu in the department of Loreto. MAAP #9 demonstrated that much of this deforestation took place at the expense of primary forest. Image 25b highlights this area, showing the forest loss between December 2012 (left panel) and September 2013 (center panel; the pinkish areas indicate recently cleared forests). The right panel shows the cumulative deforestation between 2012 and 2014. See MAAP #9 and MAAP #2 for more details.

Inset B: Oil Palm in Loreto/San Martin

Image 25c. Deforestation for oil palm in northern Peru between September 2011 (left panel) and September 2014 (center panel) and cumulative 2012-14 (right panel). Data: USGS, PNCB/MINAM, Hansen/UMD/Google/USGS/NASA
Image 25c. Deforestation for oil palm in northern Peru between September 2011 (left panel) and September 2014 (center panel) and cumulative 2012-14 (right panel). Data: USGS, PNCB/MINAM, Hansen/UMD/Google/USGS/NASA

Inset B (from Image 25a) indicates expanding deforestation within and around two large-scale oil palm plantations along the Loreto-San Martin border. Image 25c highlights this area, showing the forest loss between Setpember 2011 (left panel) and September 2014 (center panel). The right panel shows the cumulative deforestation between 2012 and 2014 (6,363 hectares, or 15,700 acres). See MAAP #16 for more details.

Inset C: Oil Palm in Ucayali

Image 25d. Deforestation for oil palm in central Peru between September 2011 (left panel) and September 2013 (center panel) and cumulative 2012-14 (right panel). Data: USGS, PNCB/MINAM, Hansen/UMD/Google/USGS/NASA
Image 25d. Deforestation for oil palm in central Peru between September 2011 (left panel) and September 2013 (center panel) and cumulative 2012-14 (right panel). Data: USGS, PNCB/MINAM, Hansen/UMD/Google/USGS/NASA

Inset C (from Image 25a) indicates the deforestation of 9,400 hectares (23,200 acres) of primary forest for two large-scale oil palm plantations in the department of Ucayali. Image 25d highlights this area, showing the forest loss between September 2011 (left panel) and September 2013 (center panel; the pinkish-black areas indicate recently cleared forests). The right panel shows the cumulative deforestation between 2012 and 2014. See MAAP #4 for more details.

Inset D: Gold Mining in Madre de Dios

Image 25e. Deforestation for gold mining in southern Peru between September 2011 (left panel) and September 2014 (center panel) and cumulative 2012-14 (right panel). Data: USGS, PNCB/MINAM, Hansen/UMD/Google/USGS/NASA
Image 25e. Deforestation for gold mining in southern Peru between September 2011 (left panel) and September 2014 (center panel) and cumulative 2012-14 (right panel). Data: USGS, PNCB/MINAM, Hansen/UMD/Google/USGS/NASA

Inset D (from Image 25a) indicates the extensive illegal gold mining deforestation in the buffer zone of Tambopata National Reserve in the department of Madre de Dios. Image 25e highlights this area, showing the forest loss between September 2011 (left panel) and September 2014 (center panel; the lighter areas indicate recently cleared forests). The right panel shows the cumulative deforestation between 2012 and 2014 (4,738 hectares, or 11,700 acres). See MAAP #1 for more details.

It is important to emphasize that in this case, extensive deforestation continued in 2015. See MAAP #12 and MAAP #24 for more details.

Methodology

We conducted this analysis using the Kernel Density  tool from Spatial Analyst Tool Box of ArcGis 10.1 software. Our goal was to emphasize local concentrations of deforestation in the raw data while still representing overarching patterns of deforestation between 2012 and 2014. We accomplished this using the following parameters:

Search Radius: 15000 layer units (meters)

Kernel Density Function: Quadratic

Cell Size in the map: 200 x 200 meters (4 hectares)

Everything else was left to the default setting.

References

1MINAGRI-SERFOR/MINAM-PNCB (2015) Compartiendo una visión para la prevención, control y sanción de la deforestación y tala ilegal.

Citation

Finer M, Snelgrove C, Novoa S (2015) Deforestation Hotspots in the Peruvian Amazon, 2012-2014. MAAP: 25.

MAAP #25: Deforestation Hotspots In The Peruvian Amazon, 2012-2014

Posted on by Ana Folhadella

Download PDF of this article

Forest Loss in the Peruvian Amazon
Source: PNCB/MINAM

Deforestation continues to increase in the Peruvian Amazon. According to the latest information from the Peruvian Environment Ministry1, 2014 had the highest annual forest loss on record since 2000 (177,500 hectares, or 438,600 acres per year). 2013 and 2012 had the third and fourth highest annual forest loss totals, respectively (behind only 2009).

 

 

 

 

 

 

 

 

Image 25a. Kernel density map for forest loss in the Peruvian Amazon between 2012 and 2014. Data: PNCB/MINAM, Hansen/UMD/Google/USGS/NASA.
Image 25a. Kernel density map for forest loss in the Peruvian Amazon between 2012 and 2014. Data: PNCB/MINAM, Hansen/UMD/Google/USGS/NASA.

To better understand where this deforestation is concentrated, we conducted kernel density estimation. This type of analysis calculates the magnitude per unit area of a particular phenomenon (in this case, forest loss).

Image 25a shows the kernel density map for forest loss in the Peruvian Amazon between 2012 and 2014 and reveals that recent deforestation is concentrated in a number of “hotspots” in the departments of Loreto, San Martin, Ucyali, Huanuco, and Madre de Dios.

Insets A-D highlight four areas with high densities of forest loss described in previous MAAP articles. We are currently studying the other high density deforestation areas not included in the insets.

 

Inset A: Cacao in Loreto

Image 25b. Deforestation for cacao in northern Peru between December 2012 (left panel) and September 2013 (center panel) and cumulative 2012-14 (right panel). Data: USGS, PNCB/MINAM, Hansen/UMD/Google/USGS/NASA
Image 25b. Deforestation for cacao in northern Peru between December 2012 (left panel) and September 2013 (center panel) and cumulative 2012-14 (right panel). Data: USGS, PNCB/MINAM, Hansen/UMD/Google/USGS/NASA

Inset A (from Image 25a) indicates the deforestation of over 2,000 hectares (4,940 acres) on property owned by the company United Cacao (through its wholly owned Peruvian subsidiary, Cacao del Peru Norte) near the town of Tamshiyacu in the department of Loreto. MAAP #9 demonstrated that much of this deforestation took place at the expense of primary forest. Image 25b highlights this area, showing the forest loss between December 2012 (left panel) and September 2013 (center panel; the pinkish areas indicate recently cleared forests). The right panel shows the cumulative deforestation between 2012 and 2014. See MAAP #9 and MAAP #2 for more details.

 

Inset B: Oil Palm in Loreto/San Martin

Image 25c. Deforestation for oil palm in northern Peru between September 2011 (left panel) and September 2014 (center panel) and cumulative 2012-14 (right panel). Data: USGS, PNCB/MINAM, Hansen/UMD/Google/USGS/NASA
Image 25c. Deforestation for oil palm in northern Peru between September 2011 (left panel) and September 2014 (center panel) and cumulative 2012-14 (right panel). Data: USGS, PNCB/MINAM, Hansen/UMD/Google/USGS/NASA

Inset B (from Image 25a) indicates expanding deforestation within and around two large-scale oil palm plantations along the Loreto-San Martin border. Image 25c highlights this area, showing the forest loss between Setpember 2011 (left panel) and September 2014 (center panel). The right panel shows the cumulative deforestation between 2012 and 2014 (6,363 hectares, or 15,700 acres). See MAAP #16 for more details.

 

Inset C: Oil Palm in Ucayali

Image 25d. Deforestation for oil palm in central Peru between September 2011 (left panel) and September 2013 (center panel) and cumulative 2012-14 (right panel). Data: USGS, PNCB/MINAM, Hansen/UMD/Google/USGS/NASA
Image 25d. Deforestation for oil palm in central Peru between September 2011 (left panel) and September 2013 (center panel) and cumulative 2012-14 (right panel). Data: USGS, PNCB/MINAM, Hansen/UMD/Google/USGS/NASA

Inset C (from Image 25a) indicates the deforestation of 9,400 hectares (23,200 acres) of primary forest for two large-scale oil palm plantations in the department of Ucayali. Image 25d highlights this area, showing the forest loss between September 2011 (left panel) and September 2013 (center panel; the pinkish-black areas indicate recently cleared forests). The right panel shows the cumulative deforestation between 2012 and 2014. See MAAP #4 for more details.

 

Inset D: Gold Mining in Madre de Dios

Image 25e. Deforestation for gold mining in southern Peru between September 2011 (left panel) and September 2014 (center panel) and cumulative 2012-14 (right panel). Data: USGS, PNCB/MINAM, Hansen/UMD/Google/USGS/NASA
Image 25e. Deforestation for gold mining in southern Peru between September 2011 (left panel) and September 2014 (center panel) and cumulative 2012-14 (right panel). Data: USGS, PNCB/MINAM, Hansen/UMD/Google/USGS/NASA

Inset D (from Image 25a) indicates the extensive illegal gold mining deforestation in the buffer zone of Tambopata National Reserve in the department of Madre de Dios. Image 25e highlights this area, showing the forest loss between September 2011 (left panel) and September 2014 (center panel; the lighter areas indicate recently cleared forests). The right panel shows the cumulative deforestation between 2012 and 2014 (4,738 hectares, or 11,700 acres). See MAAP #1 for more details.

It is important to emphasize that in this case, extensive deforestation continued in 2015. See MAAP #12 and MAAP #24 for more details.

Methodology

We conducted this analysis using the Kernel Density  tool from Spatial Analyst Tool Box of ArcGis 10.1 software. Our goal was to emphasize local concentrations of deforestation in the raw data while still representing overarching patterns of deforestation between 2012 and 2014. We accomplished this using the following parameters:

Search Radius: 15000 layer units (meters)

Kernel Density Function: Quadratic

Cell Size in the map: 200 x 200 meters (4 hectares / 9.88 acres)

Everything else was left to the default setting.

References

1MINAGRI-SERFOR/MINAM-PNCB (2015) Compartiendo una visión para la prevención, control y sanción de la deforestación y tala ilegal.

 

Citation

Finer M, Snelgrove C, Novoa S (2015) Deforestation Hotspots in the Peruvian Amazon, 2012-2014. MAAP: 25.

MAAP #24: Illegal Gold Mining Penetrates Deeper into Tambopata National Reserve

Posted on by dcadmin

*Note: During the preparation of this analysis, the Peruvian government conducted an operation against the illegal gold mining activity in the area described below (see this news article in Spanish for more information).

In MAAP #21, we revealed, using high-resolution images, the first sign of an invasion into the Tambopata National Reserve (an important natural protected area in the southern Peruvian Amazon) by illegal gold mining activities. Here in MAAP #24, we show two additional types of satellites imagery (due to lack of new high-resolution image) indicating that the illegal gold mining deforestation continues to penetrate deeper into the Reserve.

Image 24a. Landsat images showing the expansion of deforestation inside the Tambopata National Reserve between December 2015 (left panel) and January 2016 (right panel). Data: USGS, SERNANP.
Image 24a. Landsat images showing the expansion of deforestation inside the Tambopata National Reserve between December 2015 (left panel) and January 2016 (right panel). Data: USGS, SERNANP.

Image 24a shows a comparison between two Landsat images (30 m resolution) indicating that the deforestation continued to increase within the Reserve between December 2015 (left panel) and January 2016 (right panel). The red circles indicate the general location of the newly deforested areas, which appear pink (soil without forest cover) and blue (wastewater pools) in contrast to the green (standing forest). The deforestation inside the Tambopata National Reserve between December 2015 and January 2016 is approximately 20 hectares (49 acres).

Image 24b is the base map showing the area described above in a larger context. The red inset box indicates the area shown in Image 24a.

Image 24b. Reference Map of mining area. Data: SERNANP, WorldView-2 of Digital Globe (NextView).
Image 24b. Reference Map of mining area. Data: SERNANP, WorldView-2 of Digital Globe (NextView).

Radar: Powerful New Tool

Image 24c. Radar images showing the expansion of deforestation inside the Tambopata National Reserve between November 2015 (left panel) and January 2016 (right panel) Data: SERNANP, Sentinel-1
Image 24c. Radar images showing the expansion of deforestation inside the Tambopata National Reserve between November 2015 (left panel) and January 2016 (right panel) Data: SERNANP, Sentinel-1

Image 24c shows, for the first time in MAAP, information from a radar satellite (Sentinel-1 from the European Space Agency). Unlike multi-spectral Landsat imagery that is vulnerable to clouds blocking the view, radar imagery is useful year-round (even the Amazon rainy season) because it can penetrate through cloud cover. In the displayed images, the shades of gray are related to the topography and the height of the forest. Lower areas, such as recently deforested lands and bodies of water, appear darker (almost black) in color, while higher areas such as standing forests appear lighter in color. Image 24c confirms the increase in deforestation between November 2015 (left panel) and January 2016 (right panel) within the area indicated above (see the red boxes).

Citation

Finer M, Novoa S, Olexy T (2016) Illegal Gold Mining Penetrates Deeper into Tambopata National Reserve. MAAP: 24.