Meta, the World Resources Institute (WRI), and Land & Carbon Lab have introduced a game-changing tool for environmental monitoring: the first-ever global map of tree canopy height at a 1-meter resolution.
This cutting-edge AI-powered map can detect individual trees worldwide, addressing longstanding gaps in the forest carbon credit market. It is also a leap forward in environmental science, offering unprecedented insights into tree distribution, canopy height, and forest health.
Unparalleled Precision: 50 Million Sq. Km Mapped at 1-Meter Resolution
The innovative map leverages artificial intelligence to analyze more than a trillion pixels from 18 million satellite images. The result is a highly accurate global dataset with a mean absolute error of just 2.8 meters. Such precision is critical for monitoring and verification purposes, especially in areas where accurate data has historically been challenging to obtain.
According to Meta, the model establishes a global baseline for tree canopy height, enabling improved understanding and management of forest ecosystems.
The dataset reveals that approximately one-third of Earth’s landmass—about 50 million square kilometers—has a canopy height above 1 meter. By providing such granular data, this tool offers invaluable insights into the state of global forests, facilitating more targeted and effective conservation efforts.
A notable feature of the initiative is its commitment to open access. The data and models are freely available on platforms such as AWS, Google Earth Engine, and GitHub. Thus, it is accessible to researchers, policymakers, and businesses worldwide. This approach encourages innovation across various fields, from carbon credit verification to environmental conservation.
Meta emphasized the significance of democratizing AI technology, stating:
“Democratizing access to artificial intelligence can be an important tool in unlocking finance for and increasing transparency in mitigating and adapting to climate change.”
Land & Carbon Lab, convened by WRI and the Bezos Earth Fund, is a leading organization dedicated to monitoring and analyzing global land and carbon dynamics. Their Global Tree Canopy Height dataset provides high-resolution, globally consistent measurements of tree heights, offering critical insights into forest structure and carbon storage.
The company delivers accurate and up-to-date information by leveraging advanced satellite imagery and machine learning techniques. Their work enhances our understanding of Earth’s ecosystems and informs strategies to protect and restore vital natural resources.
Laconic and Planet Labs made a similar effort. They partnered for a monitoring system that aims to improve the accuracy of forest carbon projects.
Revolutionizing Forest Carbon Markets
One of the map’s most significant applications is its potential to transform carbon markets.
Forests play a critical role in carbon sequestration, but accurately monitoring and verifying forest carbon credits has been a persistent challenge. High-resolution data provided by this map enhances the ability to track tree growth, particularly in sparse or small-scale forests.
Providing detailed data on tree distribution and canopy height helps identify areas that require immediate attention or are best suited for reforestation. This level of detail is particularly valuable for managing degraded lands, where precision is crucial for effective restoration.
This improved tracking capability ensures greater transparency and accountability in carbon markets. Meta highlighted this point, noting that:
“forest-based carbon removal and the use of technology to better monitor, report, and verify carbon sequestration are essential components of Meta’s carbon removal strategy.”
By addressing these challenges, the map strengthens the integrity of carbon markets and supports global efforts to combat climate change. It also facilitates the creation of actionable strategies for carbon removal and forest restoration, ensuring that investments in these areas yield measurable results.
Meta has been investing heavily in carbon removal initiatives, including nature-based carbon projects. Carbon removal is a key part of its strategy to reduce carbon emissions.
Advanced AI at Work
The technological backbone of the map is an AI model called DiNOv2, which employs Self-Supervised Learning (SSL) to process vast amounts of unlabeled satellite imagery. SSL enables the model to learn patterns and features in data without requiring manual labeling, making it highly scalable and robust.
DiNOv2’s capabilities extend beyond canopy height mapping. It can also support applications like tree detection and segmentation, providing even more tools for researchers and conservationists.
Moreover, the open-access nature of the model enables stakeholders from diverse fields to leverage the dataset for various applications, from scientific research to practical conservation initiatives.
By leveraging this advanced AI technology, Meta and its partners have created a tool that is not only highly accurate but also adaptable to various environmental challenges.
You can explore the tool via Google Earth Engine here.
A Transformative Step for Carbon Market Integrity
Carbon markets are increasingly recognized as a vital tool for addressing climate change. However, their success depends on accurate monitoring and verification of carbon sequestration efforts.
The market has been under intense scrutiny because of various nature-based carbon removal projects suspected and accused of dubious impact. This resulted in decreasing trust and confidence in the market.
The high-resolution tree canopy map addresses this need by providing reliable data that enhances transparency and accountability. By enabling precise monitoring of tree growth and forest health, the map helps verify that carbon removal projects are delivering on their promises. This, in turn, builds trust among market players and encourages greater investment in forest-based carbon removal initiatives.
Meta, WRI, and Land & Carbon Lab have not only created a powerful tool but also set an example of how technology, collaboration, and accessibility can drive meaningful change in addressing the world’s most pressing environmental challenges.
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