Predicting deforestation with an Early Warning System
Deforestation is one of the greatest threats to nature. It is a huge challenge for us as WWF to combat this. But if we can predict where the forest will be cut down illegally, we can intervene in time. Or even prevent deforestation before it actually happens.
A variety of existing technical programmes and models is being used to combat deforestation. These systems usually give a warning after the chainsaw has already started. Unfortunately, that is too late. WWF is working on a model that can predict illegal deforestation before the trees are being felled.
Intervene before deforestation
This new model is called an Early Warning System (EWS). It is able to connect big data such as satellite images with human activity. For example, if a road is being constructed somewhere, chances are that it turns out to be an access road for devices that cut down trees. Or the seasonal change from rainy to dry can cause increased access to the forests. This often results in a piece of forest going down. At such events, the system gives a notification to all relevant stakeholders, allowing them to take timely action in preventing deforestation.
In the video below, project leader Jorn Dallinga briefly explains how EWS works.
For a more detailed explanation about EWS, please also read our FIG paper.
We have developed a medium-term model that can predict deforestation 6 months in advance. This model is currently being tested in an area in Central Kalimantan, Indonesia. The tests already achieved 80% accuracy!
Involve local people
The involvement of local stakeholders (such as villagers, organisations and government agencies) is an essential part of the process as they eventually become the users of EWS. Local and indigenous peoples in particular have been part of the project from step one. They often depend on the forest for their livelihood and have been protecting it for centuries. EWS also helps them with better protection, for example by preventing illegal deforestation in their community forest.
With EWS, we aim to reduce the illegal logging of forests in Sumatra and Borneo by 10-35%. If local stakeholders are able to respond and act in time, we can achieve this. Within a few years, estimates are that EWS could reduce illegal deforestation by almost 30%. This not only prevents loss of habitat but also the release of CO2. We can really make a difference for nature with EWS!
We implement the Early Warning System together with governments and local communities. EWS is being developed by a collaboration with the Boston Consultancy Group and a ‘tech consortium’, led by Deloitte with AWS, Jheronimus Academy of Data Science and Utrecht University.
EWS is partly supported by the Shared Resources, Joint Solutions (SRJS) programme, a strategic partnership with IUCN NL and the Netherlands Ministry of Foreign Affairs. With SRJS, we want to strengthen the capacity of local NGOs and civil society organisations in sixteen low- and middle-income countries. The programme aims to ensure climate resilience, water supply and food security by joining forces with the public and private sector.
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With SRJS, we support and strengthen local NGOs and civil society organisations in 16 countries, so that we can safeguard water supply, climate resilience and food security together with governments and companies. We also ensure that these organisations work together to become stronger.