The Earth’s forests are some of our biggest tools in combatting the effects of climate change, with huge potential for carbon sequestration. However, forests are simultaneously being ravaged by the effects of extreme weather events, global temperature rise and deforestation. Remote sensing is an important tool that can be used to monitor deforestation, providing rapid insight into which areas are suffering the most and a timeline of changes to the forests.
Large scale deforestation has been ongoing since at least the 1960s. Despite our increased knowledge, campaigns, government pledges, and the threat that a global increase of 2 degrees presents, deforestation in the Amazon rainforest has accelerated to the highest levels yet by 2021. Not only is preserving the Amazon vital for mitigating climate change, but also for the indigenous people and wildlife who are being threatened by its continued destruction.
Remote sensing and satellite imagery are integral to monitoring deforestation. By using the European Space Agency’s Sentinel-1 satellites, we have access to Synthetic Aperture Radar (SAR) images of the ground regardless of weather conditions. This means there is huge power in these satellites for observing the forests and tracking changes. By combining signals of backscatter from different polarisations into an image we can build up a picture of the texture of the surface. This allows us to visually see the deforested areas.
D-CAT's unique set of capabilities allows us to ingest, process and add value to Sentinel data. Taking advantage of our cloud-based Fusion Platform®, we can process Sentinel-1 data to build a picture of deforestation in the Amazon. This can be used to identify areas of interest and track them over time to flag anomalous changes.
A demonstration of this can be seen in the figure below, which shows a small area in Brazil in 2019 (left) and 2021 (right). The Sentinel-2 colour images (top) are compared to the deforestation detection produced from the Sentinel-1 data (bottom), where the darker areas are dense forest, and the lighter areas are classified as deforested. Areas with a significant difference in the two years have been highlighted in yellow. We see that the deforestation has increased from 13% of our test area to 28% in just two years, giving us a markedly different landscape.
Since Sentinel-1 has a revisit period of 10 days, forest updates are available at this frequency. Utilising SAR for this analysis ensure reliable results irrespective of cloud cover or weather events, guaranteeing consistent tracking in near real time throughout the year. Monitoring deforestation in this way allows us to produce actionable insights to aid conservation on a large scale.