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

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 miningoil 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

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 MatsiguenkaYine 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   

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

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

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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

*NoteDuring 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.