Since its launch in April 2015, MAAP has published over 70 reports related to deforestation (and natural forest loss) in the Andean Amazon. We have thus far focused on Peru, with several reports in Colombia and Brazil as well.
These reports are meant to be case studies of the most important and urgent deforestation events. We often use forest loss alerts (known as GLAD) to guide us, and satellite imagery (from Planet and DigitalGlobe) to identify the deforestation driver.
Here we present an interactive map highlighting the drivers identified in all published MAAP reports. These drivers include gold mining, agriculture (e.g. oil palm and cacao), cattle pasture, roads, and dams (see icon legend below map). We also include natural causes such as floods and blowdowns (fire included under agriculture since most human caused). Furthermore, we highlight deforestation events within protected areas. Note that you can filter by driver by checking boxes of interest.
We hope the result is one of the most detailed and up-todate resources on patterns and drivers of deforestation in the Andean Amazon. Over the coming year we will continue to focus on Peru and Colombia, and begin to include Ecuador and Bolivia as well.
To view the interactive map, please visit:
MAAP Interactive: Deforestation Drivers in the Andean Amazon
For more information on patterns and drivers of deforestation in the Peruvian Amazon, see our latest News and Resources
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.
Image 59a. Source: Planet
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.
In previous articles MAAP #56 and MAAP #57, we presented a series of striking satellite images of the recent deadly floods in northern Peru. Satellites provide additional types of data critical to better understanding events such as extreme flooding. Here, we present two more types of satellite data related to the flooding: ocean water temperature and precipitation.
In the previous MAAP #56, we showed a series of satellite images of the deadly floods that recently hit northern Peru.
In this report, we show a series of new, very high resolution satellite images (50 cm) of the flooding. They show, in striking detail, some of the local impacts, including to croplands and the Pan-American Highway.
Image 57. Data: ESRI, INEI, MINAM. Click to enlarge.
Image 57 shows the 13 rivers that recently overflowed in northern Peru.
Below, we show images of the flooding around four of the rivers, labelled A-D.
Intense rainfall is causing severe and deadly flooding along the northern coast of Peru.
The cause is likely “coastal El Niño,” a phenomenon produced by abnormal ocean warming along the equatorial coast of the Pacific Ocean.
Image 56a. Datos: NASA, ESA, JRC/Google
Image 56a shows a preliminary estimate of the flooded areas along the northern coast (in red). We created this estimation via an analysis of radar images (Sentinel-1) that identified areas saturated with water.
Below, we show satellite images of the areas indicated by Insets A-D, which represent examples of flooding events.
Note that the red points indicate the same spots between panels.