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Accurately Measuring Carbon Content in Forests

August 31, 2023
5 mins
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Problem

Treeconomy faced challenges in accurately measuring the carbon content in forests, a crucial aspect of carbon offsetting. Traditional methods were time-consuming and prone to errors, leading to a risk of greenwashing and loss of trust in the carbon market. Despite exploring open-source data and satellite imagery, Treeconomy found limitations in existing solutions, such as the need for manual tree counting and inefficient monitoring of forest changes like growth or deforestation.

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Key Result

With Encord's data annotation tool, Treeconomy achieved significant improvements in data accuracy and efficiency. Encord enabled the training of computer vision algorithms to accurately count trees in forest locations, saving time and effort compared to manual methods. The integration of Encord with existing datasets and compatibility with Microsoft Azure streamlined the process further. As a result, Treeconomy was able to count entire forests in minutes rather than weeks, leading to more reliable carbon offsets. This increased accuracy allowed Treeconomy to sell carbon offsets at premiums ranging from 50% to 150% above alternative options, generating increased revenue that could be reinvested into communities and reforestation efforts.

Treeconomy uses Encord to collect reliable, granular data on trees. This is used to more accurately measure the carbon content in forests. More reliable carbon credit data bolsters Treeconomy’s reputation, allows the company to charge 50-150% more for carbon credits, and enables them to redirect more funds to reforestation efforts. 

Customer

Treeconomy, an Earth Tech company, was created to better incentivize the planting of trees. It does so by accurately quantifying carbon captured and stored by trees (using sophisticated technology), packaging them as carbon offsets, and selling these high-quality carbon offsets to industries. Profits generated benefit landowners and incentivize them to preserve forests and plant trees. 

What sets Treeconomy apart from competitors is its use of world-class remote sensing, machine learning, and monitoring tools. This enables Treeconomy to more accurately measure carbon offsets and detect changes to a project location that could alter carbon levels. Doing so helps to assure investors that their nature-based carbon credits are real, that trees are really growing, and that the project is delivering on its impact claims. 

Problem

Accurately measuring the amount of carbon in a forest is extremely important for carbon offsetting. Errors can lead to greenwashing and a loss of trust in the carbon market. As Treeconomy Co-Founder Robert Godfrey notes “Right now there are a number of companies being called out and caught with bad credits on their books, where projects have maybe grossly overestimated their climate impact.” 

Yet measuring carbon in forests is difficult. Traditionally, this was done by meticulously going from tree to tree with a tape measure and making broad extrapolations based on these measurements. The process was time-consuming and error-prone. Monitoring changes in the forest - like growth or deforestation - was similarly laborious. 

To address these challenges, Treeconomy explored open-source data and satellite imagery but found they had limitations. For example, satellite imagery still required them to manually count trees, a time-consuming and inefficient process. They created a computer vision algorithm to detect tree crowns from high-resolution drone and satellite data imagery but determined that larger and more relevant data sets were required to produce more accurate results. 

Solution

Treeconomy turned to Encord as an intuitive and flexible data annotation tool capable of labeling hundreds of images at once. The tool has enabled Treeconomy to train its computer vision algorithm to accurately count the number of trees in a given location.

One of the big advantages of Encord for Treeconomy is its compatibility with Microsoft Azure and ease of use. This enabled the team to seamlessly integrate their existing data sets, thereby saving time and effort. 

Using Encord resulted in a positive discovery for Treeconomy: The tool could facilitate their future plans of labeling specific tree species - not just counting trees - and remove the need to hire staff for the task. 

Results

Encord has helped Treeconomy gather more accurate data and save time. As Godfrey explains, “Encord helps us to offer a ‘best in class’ capability for counting trees. It has helped us to improve the computer vision algorithm that allows us to delineate individual tree tops. [We were able] to count the entire forest in two minutes as opposed to two weeks.” 

By accurately quantifying trees in a forest, Treeconomy has been able to create more reliable carbon offsets. According to Godfrey, this has allowed the company to package and sell these offsets at premiums ranging from 50% to 150% above those of alternative options. 

This increased revenue is not only good for the company’s bottom line but is channeled back into the communities, benefiting landowners and supporting reforestation efforts. Ultimately, these actions reinforce Treeconomy's dedication to transforming sustainable land use into an economically rewarding and competitive venture.

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Frequently asked questions
  • Yes. In addition to being able to train models & run inference using our platform, you can either import model predictions via our APIs & Python SDK, integrate your model in the Encord annotation interface if it is deployed via API, or upload your own model weights.

  • At Encord, we take our security commitments very seriously. When working with us and using our services, you can ensure your and your customer's data is safe and secure. You always own labels, data & models, and Encord never shares any of your data with any third party. Encord is hosted securely on the Google Cloud Platform (GCP). Encord native integrations with private cloud buckets, ensuring that data never has to leave your own storage facility.

    Any data passing through the Encord platform is encrypted both in-transit using TLS and at rest.

    Encord is HIPAA&GDPR compliant, and maintains SOC2 Type II certification. Learn more about data security at Encord here.

  • Yes. If you believe you’ve discovered a bug in Encord’s security, please get in touch at security@encord.com. Our security team promptly investigates all reported issues. Learn more about data security at Encord here.

  • Yes - we offer managed on-demand premium labeling-as-a-service designed to meet your specific business objectives and offer our expert support to help you meet your goals. Our active learning platform and suite of tools are designed to automate the annotation process and maximise the ROI of each human input. The purpose of our software is to help you label less data.

  • The best way to spend less on labeling is using purpose-built annotation software, automation features, and active learning techniques. Encord's platform provides several automation techniques, including model-assisted labeling & auto-segmentation. High-complexity use cases have seen 60-80% reduction in labeling costs.

  • Encord offers three different support plans: standard, premium, and enterprise support. Note that custom service agreements and uptime SLAs require an enterprise support plan. Learn more about our support plans here.

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