Automating Carbon Offsetting Using AI

Case Study

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Climate change has become one of the most pressing global issues, marked by rising temperatures, extreme weather patterns, and severe impacts on ecosystems and human health. Over the past century, global temperatures have risen by about 1.1°C (1.9°F), and 2010–2020 was the hottest decade recorded. Human activities, particularly the emission of greenhouse gases like CO₂, are the primary drivers of this increase.

According to recent statistics on global emissions, certain countries are responsible for a significant share of CO₂ emissions. In 2022, China led globally with 12.67 billion tons of CO₂ emissions, followed by the United States with 4.85 billion tons and India with 2.69 billion tons. These three nations together account for almost half of the world’s CO₂ emissions, illustrating how concentrated the issue can be in certain regions.

CO2 Emission By Year

37900 in 2022

According to recent statistics on global emissions, certain countries are responsible for a significant share of CO₂ emissions. In 2022, China led globally with 12.67 billion tons of CO₂ emissions, followed by the United States with 4.85 billion tons and India with 2.69 billion tons. These three nations together account for almost half of the world’s CO₂ emissions, illustrating how concentrated the issue can be in certain regions.

According to recent statistics on global emissions, certain countries are responsible for a significant share of CO₂ emissions. In 2022, China led globally with 12.67 billion tons of CO₂ emissions,

Solutions to Climate Change

As climate change intensifies, so does the urgency to address it through a range of solutions aimed at reducing greenhouse gas emissions and adapting to changing environmental conditions. Globally, solutions are being implemented across several areas:

      1. Transition to Renewable Energy: Moving away from fossil fuels and embracing renewable sources like solar, wind, and hydropower are critical for reducing emissions. Countries worldwide are investing heavily in renewable energy infrastructure, aiming for low-carbon energy generation to reduce dependence on coal, oil, and natural gas.
      2. Carbon Capture and Storage (CCS): Moving away from fossil fuels and embracing renewable sources like solar, wind, and hydropower are critical for reducing emissions. Countries worldwide are investing heavily in renewable energy infrastructure, aiming for low-carbon energy generation to reduce dependence on coal, oil, and natural gas.
      3. Reforestation and Land Management: rees naturally absorb CO₂, so planting trees and restoring forests are highly effective in capturing carbon. Sustainable land management practices, such as reducing deforestation and preserving natural ecosystems, are equally important.

While these solutions play an important role, carbon offsetting has emerged as a flexible, scalable approach. Carbon offsetting allows individuals, companies, and even countries to compensate for their emissions by funding initiatives that reduce CO₂ elsewhere, often through renewable energy projects, forest preservation, or reforestation efforts.

By focusing on carbon offsetting—particularly in forests, where CO₂ absorption is high—organizations can balance their emissions while supporting critical environmental projects. This approach is also becoming more accessible and effective with advances in technology, including AI-driven monitoring, which is transforming traditional methods.

Carbon Offsetting: What It Is, Why It Matters, and Its Challenges

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Carbon offsetting is a method used to balance out emissions by investing in projects that reduce or capture an equivalent amount of CO₂ elsewhere. Essentially, for every ton of CO₂ emitted, an equal amount is offset by supporting initiatives that remove CO₂ from the atmosphere or prevent its release. Common offset projects include reforestation, renewable energy investments, and improvements in energy efficiency.

Carbon offsetting is crucial because it provides a way for companies and individuals to take immediate action on their carbon footprint. While reducing emissions directly is the ultimate goal, offsetting offers a practical means to mitigate climate impact in the short term. This strategy is particularly valuable for industries with unavoidable emissions, like aviation and heavy manufacturing, enabling them to work toward net-zero targets by funding projects that restore natural carbon sinks.

However, traditional offsetting methods face challenges in transparency and accuracy. Verifying the actual impact of offset projects—such as confirming that trees are effectively sequestering CO₂ over time—can be difficult and costly. This is especially true for large forest-based projects, where changes in land use or deforestation can undermine offset efforts. These challenges highlight the need for innovative solutions, like AI-driven monitoring, to improve accountability and ensure that offset projects deliver on their promised climate benefits.

Drangue’s Approach & Case Study: AI-Driven Forest Carbon Offsetting

At Drangue, we leverage AI-powered object detection and high-resolution satellite imagery to enhance the accuracy and efficiency of forest-based carbon offsetting. Our approach combines satellite data with advanced machine learning models to automate the detection and counting of trees within a given area, ultimately providing a reliable basis for calculating carbon offsets.

Process and Methodology

Using high-resolution 10 cm satellite imagery sourced from Sweden (source for images), we applied our custom-trained AI models to automatically detect and identify individual trees across a targeted forest area. The resolution of this imagery allows for precise detection, even at the single-tree level, ensuring high accuracy in tree counting and location tracking.

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To improve the accuracy of our results, we employed human supervisors who reviewed the AI-generated data, correcting any misclassifications or missed trees by the model. This process allowed us to achieve a refined points map where each point represents the location of a single detected tree.

Results and Findings

In this use case, we analyzed a 10-hectare forested area, where our model successfully detected approximately 10,000 trees. With an average density of trees per hectare being around 1,000 trees per hectare, this level of detail offers valuable insights for forest management and carbon offset estimation.

This data also enables us to generate heatmaps, highlighting areas with higher tree concentrations. Such heatmaps are helpful for assessing forest health, identifying densely forested regions, and prioritizing reforestation or monitoring efforts in sparser areas. The heatmap and tree point map will be presented in a visual format for easy interpretation.

Acres

Number Of Trees

Trees Per Hectare

Calculating Carbon Offset

Estimating the total carbon offset potential based on tree count involves several considerations, as each tree’s carbon sequestration capacity varies. Factors such as tree species, age, and growth rate impact the amount of CO₂ a tree can absorb. For example, older, larger trees typically store more carbon than younger, smaller ones, and certain species absorb CO₂ at faster rates.

Using general estimates for temperate forests, we can approximate that each tree sequesters between 10 to 50 kg of CO₂ per year. Given our detection of 10,000 trees, a broad calculation might look like this:

Lower Bound

\[10,000 \text{ trees} \times 10 \frac{\text{kg CO₂}}{\text{tree/year}} = 100,000 \text{ kg CO₂/year}\]

Upper Bound

\[10,000 \text{ trees} \times 50 \frac{\text{kg CO₂}}{\text{tree/year}} = 500,000 \text{ kg CO₂/year}\]

This yields an estimated offset potential between 100 and 500 metric tons of CO₂ per year for this 10-hectare forest area.

Through this process, Drangue provides an efficient, scalable approach to forest carbon offsetting. By using AI and satellite imagery, we ensure accurate data collection and monitoring, helping stakeholders gain clearer insights into their environmental impact and improving the accountability of forest-based offset projects.

Conclusion

Drangue’s approach demonstrates how AI and satellite technology can redefine the accuracy and efficiency of forest carbon offsetting. By leveraging advanced tools to automatically monitor tree density and forest health, we provide a clearer picture of carbon sequestration potential—empowering organizations to make impactful, data-driven decisions in their sustainability efforts. Join us at Drangue to drive forward innovative, technology-backed solutions for a greener future.