It’s wonderful for the economy to sell carbon credits, but it’s not great for the environment if the money is immediately used to cut down the tree representing those credits. Using technology more commonly associated with autonomous vehicles, Gaia AI is developing a tool that may be used for that and other areas of forest management. A pre-seed funding round totaling $3 million was recently completed by the company.

The startup is now employing lidar and computer vision equipment to gather data, but is ultimately establishing a data platform to solve some of the key challenges in forestry.

“In autonomous vehicles, cars don’t drive themselves off of just LiDAR, or radar, or computer vision. It’s by combining them that you can use the right sensor for the right task,” says Peter McHale, co-founder and CEO at Gaia AI. “Forestry is no different, and by working with measurements from satellite imagery, above-canopy drones, below-canopy LiDAR and computer vision and forester input, we can use the right measurement to solve the right problem.”

The spin-off from MIT aims to provide foresters with the means through which they may make data-driven decisions that will improve their bottom line. Gaia AI says that their technology makes it 100 times faster to acquire and act on the rich data the firm is gathering, analysing, and reporting on, which can be utilised by wood operations.

Similar approaches are being taken by some of Gaia AI’s rivals, such as Treeswift, which is gathering data from aerial or satellite imagery. Gaia suggests combining data from a variety of sources because, as she puts it, “it allows you to see the forest for the trees.”

“Most forestry measurement-related startups build up a single hammer and then try to argue that all the problems in forestry are a nail for that hammer. The problem with satellite imagery by itself is that it cannot see below the canopy of a forest, where the tree trunks are which hold the majority of the biomass and carbon of a tree. You need below-canopy data to unlock the value in satellite data, and make it not only scalable but also accurate,” says McHale. “The problem with making autonomous drones fly below the canopy is it involves taking on the hardest technical problems while not focusing on the real problems that forest managers have. For drones flying under-canopy in a forest, you will have an unhappy customer when they have to carry around a ladder to untangle the drone from the branches every time the perception system misses a thin branch.”

A major concept of Gaia is the belief that the measurement is best done by computers, and the forest managing is for the people. This is because foresters have knowledge and expertise for how to manage forests, but are often left to perform tasks that are a bad use of their time.

“Longer term, Gaia AI will be the Google of forestry, utilizing advanced data capabilities to solve the biggest problems holding back the potential of nature and make timber companies a lot of money along the way,” says McHale. “This next year is a big moment for the company, and it’s important we execute well on our go-to-market in order to give this big vision our best shot.”

Lumber mills, we were told by the corporation, use a high level of data optimization; cameras scan logs, and software calculates the optimal cuts for each tree, maximising the profit made from each one. It is better for the environment if trees, which are a renewable resource, are used to their full potential. Gaia AI explains that such optimization may be found at the mill but not in the woods.