Forest Remote Sensing: Explainer

Transparency is paramount in the rapidly growing carbon removal market. As in every market, buyers want assurance that sellers will deliver their purchases and provide the value they promise.

So how do carbon credit suppliers guarantee their carbon storage credentials?

For forests and other nature-based projects, various remote sensing technologies have been employed to quantify and monitor carbon storage.

How does forest remote sensing work in practice?

Remote sensing is used in forest carbon removal projects to map and quantify changes in canopy cover, monitor forest degradation, and estimate carbon storage.

Several approaches come under the umbrella of remote sensing, including LiDAR, radar, and photogrammetry. These often rely on observations from satellites or aircraft. However, this remote sensing data must be combined with field measurements to calibrate and verify the accuracy of carbon storage calculations.

Forest canopy from above

Each approach of remote sensing has its own strengths and pitfalls, thus making some more apt in use cases over others. For example, some are beneficial for measuring mass and density, while others estimate vegetation cover from visual monitoring, allowing to quickly compare changes over time.

Some of the most common remote sensing methods are:

The Method LiDAR (Light Detection and Ranging) Radar (Radio Detection and Randing) Photogrammetry
How it Works Utilises laser pulses to measure distances to the Earth's surface, producing highly detailed 3D maps of forest structures. These laser pulses are usually airborne (transmitted by small planes flying over the canopy). Uses radio waves to penetrate forest canopies, providing information on forest structure and biomass. Radar data can be obtained using aircraft or satellites. Involves analysing aerial or satellite images to create detailed 3D maps and models of forested areas.
Use Cases LiDAR is particularly effective for estimating aboveground biomass and carbon density. Radar is especially useful in areas with dense vegetation or frequent cloud cover, where optical sensors may be less effective. Photogrammetry can capture changes in forest cover over time, aiding in monitoring degradation.

How does remote sensing contribute to transparency in nature-based carbon removal solutions?

Currently, forest carbon removal projects can obtain certification from globally recognised carbon standards, such as Verra, Plan Vivo, and Gold Standard. Obtaining these certifications is a complex process that involves a lot of monitoring and reporting, and so having this badge is a good indicator that a project has been vetted for quality.

Remote sensing plays a crucial role in getting and retaining certification, which in turn establishes trust between buyers and suppliers. This helps the project build a market advantage while also ensuring the longevity of their carbon storage efforts.

Case Study:
Halo Verde Forest Project,
Timor Leste

In October 2022, Klimate participated in a study organised by the European Space Agency (ESA) focused on assessing the utilisation of remote sensing for forestry projects.

The project included conducting a feasibility study of the Halo Verde forestry project in Timor Leste, run by the supplier Fundação Carbon Offset Timor (FCOTI). For the project, we used satellite data in combination with machine learning models developed by the partner Atla.ai and trained with data on biomass growth, tree size and species collected by the team on the ground, to estimate carbon sequestration of the forestry project.

The aim of this initiative was to develop a way of more accurately estimating biomass growth, and therefore ensuring that the forest’s carbon storage capacity is calculated correctly.

The team collected forest measurements by hand, as a way of “ground truthing” the results provided by satellite imaging and machine learning algorithms. Having this additional layer of verification goes a long way to ensuring the credibility of the Halo Verde forestry credits Klimate provides to clients.

FCOTI Halo Verde project

Satellite images from Klimate’s Halo Verde forestation project, run by supplier Fundacão Carbon Offset Timor (FCOTI)

"The ESA project in Timor-Leste was a great learning experience. Assessing carbon storage in forests is quite difficult, but by combining on-the-ground knowledge gathering with remote sensing capabilities, we can obtain a much better understanding of the potential strengths and weaknesses of the project and the credits it issues.

We always conduct a thorough due diligence on all projects we work with, and when combined with additional insights from field visits or technical assessments, we can probe deeper into the inner workings and larger impact of the project. Ultimately, this brings more value to both the project developer and to Klimate's clients, which is why we are constantly exploring how to incorporate local insights and technological advancements into our due diligence."

Simon Bager

Chief Impact Office, Klimate

Remote sensing station

Forest carbon projects have been an ideal proving ground for remote sensing technologies. There is potential to expand their use to other forms of carbon storage, such as enhanced weathering and the use of biochar within agriculture.

Advances in remote sensing technology—such as AI modelling and high resolution imaging software—are improving the speed, accuracy and cost-effectiveness of measuring and monitoring soil carbon stocks. This could therefore facilitate more opportunities for farmer participation in carbon markets and improved data gathering within soil sequestration and biochar.


In the quest for high-quality carbon removal, transparency is key. Remote sensing technologies empower carbon removal projects to quantify and monitor carbon storage, and when paired with on-the-ground-knowledge, can add robust data that fosters trust and credibility among buyers. Through collaborations with groups like ESA, Klimate continues to spearhead innovative solutions for transparent and effective carbon removal initiatives.

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