Vibrant Planet Raises $17M Seed Round for SaaS Reforestation

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For Allison Wolf, the 2018 wildfire season in California was a turning point. During this record yearshe started asking a lot of questions.

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“We were in the middle of the 2018 wildfire season when the Carr fire hit, and at the time I thought it was the worst season ever,” Wolf said. “I started asking many, many people — the climate scientists I worked with, land managers, utility executives, insurance executives — why is this happening so disastrously? What does the future look like? And what can be done about it?

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As a result of these discussions, Vibrant Planet was born, a public startup developing the Land Tender. It’s basically SaaS for forestry management, which the company calls a “reforestation operating system”.

With wildfire season starting again in the American West, Vibrant Planet told TechCrunch exclusively that it has raised a $17 million seed round led by the Ecosystem Integrity Foundation and the Jeremy and Hannelore Grantham Environment Foundation.

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“I quickly realized that this was a climate-related issue,” Wolf said. “Land management is, of course, a big part of the problem, because even if the climate remained stable, we would still lose a lot of forest. But climate change is definitely making things worse,” she said.

“We just need to do this – we need to regenerate forests faster and they can survive climate change and they can help us survive climate change.”

Valia Ventures, Earthshot Ventures – backed by Lauren Powell Jobs and Tom Steyer – Cisco and Halogen Ventures also took part in the round. The startup’s previous sponsors include Meta Product Director Chris Cox and Netflix. former Chief Product Officer Neil Huntwho later joined Vibrant Planet in the same role.

Vibrant Planet offers access to a range of datasets centered on the California lidar map. Lidar incredibly useful when it comes to mapping forests in 3D and determining their fire risk, but it’s no panacea. Dense forests, which often pose the greatest fire risk, are difficult to map from top to bottom, so the team trained a machine learning algorithm to fill in any gaps.

And because lidar is expensive to fly, the company is using a different AI tool to update it with cheaper satellite imagery. (All of this comes with the caveat that the data generated by the AI ​​tools is speculative – you can’t “improve” with 100% accuracy, no matter what the cops say.)


Credit: techcrunch.com /

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