A new model for measuring tropical forest carbon stocks and emisssions.
Tropical forests are one of our best defenses against the threat of climate change.
Known as the world’s largest terrestrial “carbon sink,” they absorb and store carbon dioxide from the atmosphere. Despite their vital contributions to our Earth, roughly 30 football fields of tropical forests are destroyed per minute. This is largely due to the fact that we have failed to practically measure and value the services they provide—which are arguably our first defense against climate change.
But new advances in remote sensing and machine learning technologies could play an important role in informing decision-makers, creating fresh financial incentives and setting a new precedent for how we manage tropical deforestation.
In the past, because available satellite imagery over large areas was low resolution and infrequently updated, we often missed details on the ground like forest degradation or fast-moving land conversion. Moreover, although we could map forest cover, we could only indirectly estimate the corresponding forest carbon stocks.
However, new breakthrough research from Arizona State University (ASU) helps break down these technological and cost barriers, using machine learning to combine the insights of ASU’s airborne LiDAR with Planet’s high-spatial and temporal resolution satellite imagery.
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Source and image credit: Planet
Editors Note: It’s well worth viewing the article on a large device, as the animated images help bring context to each section within the story.