Agroforestry & Conservation

Precision Agriculture & Forestry

Peace &
Justice

Climate Change & Disaster Management

Infrastructure, Energy & Governance

Ecosystem Services & Biodiversity

Illegal logging detection and prediction

Environmental Crime detection and prediction for mixed tropical systems 

Summary

Deforestation will release as much CO2 in the atmosphere in 24 hours, as 8 million people flying from London to New York. It is estimated that in 100 years, there will be no rainforests left if deforestation continues at the present rate. The key to combating these pressing problems is detecting and predicting illegal deforestation practices to ensure a swift and effective response.

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To combat deforestation and forest degradation in tropical rainforests, Space4Good, in collaboration with Indonesia-based Arsari Enviro Industri, aims to deliver a reliable and near-real-time monitoring platform that can detect deforestation events at a high spatial resolution. In the context of mixed tropical agroforestry ecosystems, the approach we are developing is both novel and innovative.
 

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Methodology

Using the time-series data from the ESA Sentinel-1 radar satellite in combination with the local expertise (knowledge and feedback loop from local experts) and Artificial Intelligence, we can accurately map the deforested areas and alert the local authorities. But how does it work and what is new about the platform? The improved timeliness, scale, and resolution of the information derived from Sentinel-1 data have made it possible for the local stakeholders to monitor thousands of hectares remotely. There’s even more to it. The conventional cloud and haze cover problems associated with the tropical areas are eliminated with the inclusion of Sentinel-1 radar data that can see through the clouds and surpass these challenges and record and characterize the magnitude of change. Through the approach, it is possible to assess both the extent as well as the time of the deforestation event. 

We are now able to remotely monitor deforestation and alert local authorities via social media to the occurrence of an event. We can even go so far as to ascertain risk areas and predict deforestation events by taking into consideration pattern recognition using AI, land-use change, and a multitude of other factors to determine drivers and key areas where deforestation is predicted. Knowing when and where deforestation occurs can help reduce these catastrophic emissions by preventing the loss of the earth’s essential forest systems and enable a quick response to illegal deforestation. 

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Partners

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Detected deforestation in 2019 and 2020. (Switch layers on and off using the toggle and get more information by clicking on the polygons).

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DEFORESTATION DETECTIONS
Since 2019 - in the 200,000 hectares of mixed tropical