Meta has teamed up with the World Resources Institute (WRI) and Land & Carbon Lab to unveil the world’s first ever AI-powered global map of tree canopy height, with unprecedented 1-meter resolution. This will be a transformative tool for the monitoring of forests and carbon market transparency.
The modern technology map utilizes machine learning to convert more than 18 million satellite images. This gives insights into more than a trillion pixels, providing extremely accurate global forest canopy height coverage. According to Meta, in terms of a mean absolute error, the level is as accurate as 2.8 meters, thus capable of serving on both monitoring and verification ends. With its advanced resolution, the map addresses critical gaps in understanding forest ecosystems, enabling precise detection of individual trees and supporting efforts in forest conservation, restoration, and carbon sequestration.
In return, the biggest highlight of the initiative is open access. Here again, tree canopy data and the AI models in question are both available freely and open access across platforms like AWS, Google Earth Engine, or GitHub for developers, conservation teams, and enterprises to work collaboratively. So, one anticipates it as a step up in carbon credit verification, improvement in sustainable management of forests and conservation practices in general.
The dataset indicates that about one-third of Earth’s landmass spans over 50 million square kilometers of territory with tree canopy height more than one meter. This is important for more transparency and accountability in carbon markets: quantifying forest-based carbon credits turns out to be an important challenge for their verification and monitoring. This implies that the tool enables high-resolution tree growth tracking, especially in sparse or small-scale forests, to support more detailed assessments of carbon removal strategies.
Meta highlights democratizing access to artificial intelligence as a means of unlocking financial resources and increasing transparency in the fight against climate change. The company’s carbon removal strategy is largely forest-based carbon sequestration, and this new mapping tool strengthens their ability to monitor, report, and verify these efforts effectively.
The AI model behind the map, called DiNOv2, uses Self-Supervised Learning (SSL) to process huge volumes of unlabeled satellite imagery. This technology, advanced enough to perform well globally, goes beyond canopy mapping and is used for tree detection and segmentation. Its scalability makes this technology a versatile tool for both environmental and commercial applications.
Meta and its partners view this effort as a critical step toward the responsible use of artificial intelligence for climate action. The tool is expected to spur collaboration among stakeholders, encourage innovation in conservation and restoration projects, and improve the integrity of carbon markets. The map provides a reliable, high-resolution baseline for tree canopy height, which equips decision-makers with the data needed to develop actionable solutions for global climate resilience.
This map also shows how technology can be used to accelerate adaptation efforts for climate. With its possibilities regarding insights in forest dynamics and support of restoring degraded ecosystems, it helps combat deforestation and makes adaptation even more effective in reducing climate mitigation strategies. Moreover, it just works with other advancements related to climate technology, such as the recently introduced AI-powered Climate Project Explorer by multilateral climate funds at COP29.
Meta’s partnership with WRI and Land & Carbon Lab is truly a testament that public-private partnerships, in this age of climate crises, can find ways to offer scalable, meaningful solutions that impact the global scope of environmental aspirations. They therefore make this accessible to all through the hope to inspire a great collective effort to create a future that is increasingly sustainable.
According to a statement by Meta, “there’s potential to democratize artificial intelligence and be of critical value for climate solutions since artificial intelligence democratized can also unlock much finance and bring unprecedented levels of transparency for the global mitigation and adaptation to climate changes”.
The unveiling of this map represents a significant milestone in leveraging AI for environmental resilience. It not only advances the understanding of forest ecosystems but also provides a powerful tool for promoting transparency, accountability, and collaboration in global climate efforts. With this innovation, Meta and its partners are paving the way for a more informed and effective approach to conservation, carbon market integrity, and climate adaptation.