Local Monitoring of the Amazon Rainforest using Open Source Tools

Project duration: 2020 - 2022 (18 months)

In order to achieve forest conservation, the first step is to know how much forest there actually exists and how much of it has been lost. Only with this information, a forest can be protected and managed in a sustainable way. This project will contribute to increasing the sources of valid and scientifically-based information on regional and local deforestation. It will do this by empowering managers of local forest conservation units through training and capacity building.

This project contributes to the ongoing forest conservation endeavors in Peru by developing a near-real-time (NRT), low-cost, and user-friendly forest monitoring system to detect deforestation and forest degradation processes at local scales in the Amazon rainforest. Forest managers will learn to use freely available, high-resolution satellite images and open-source software to detect changes in tree cover and infer whether this change is due to natural processes or deforestation caused by human activities.

This project is conducted in partnership with Arbio. Arbio is a Peruvian non-profit association founded in 2010 in Puerto Maldonado, Madre de Dios. They manage and protect 916 hectares of Amazon rainforest in the watershed of the Las Piedras river, Madre de Dios. The organization is led by women and its purpose is to implement forest conservation actions involving civil society and the private sector.

The founders of Arbio and BluoVerda have known each other for more than 15 years. Tatiana and Mariana studied forestry sciences at the UNALM university in Lima (Peru) and have since then been engaged in the sustainable management and conservation of forest ecosystems. Through this project, Arbio and BluoVerda join efforts to advance the technology for monitoring changes in forest cover using open-source software.

Contact person: Dr. Mariana Vidal Merino (m.vidal@bluoverda.org)

This project is implemented together with our local partner:

This project is supported by: