In this episode, I talk with Patrick Leung, Co-founder and CTO of Earthshot Labs, about using machine learning to help predict and restore forests and our ecosystem. Earthshot Labs is building the technology and expert guidance to develop and finance nature-based carbon projects globally. Patrick and I talked about how Earthshot Labs gathers and annotates data, the challenges in working with remote sensing and other forms of data, the importance of collaboration across disciplines, and how machine learning tools can help save our ecosystems.
QUOTES:
"We are able to actually bridge that financing gap and unlock a whole bunch of new projects that can then be in the carbon marketplace, and also bring a host of benefits to both the ecosystem, as well as, the communities that live around the ecosystem."
"Machine learning is really essential because what we're trying to do here is predict the future. We're trying to predict the next 30 years of a forest regrowing in a tropical region."
"We must look at the past. We must look at whatever data we can gather from the past state of the ecosystem and use various machine learning methods to predict the future in order to provide a view on what's gonna happen on this land in the future when we do this project."
"These are actual mathematical simulations that take into account the current conditions of the ecosystem and actually forecast them by using a kind of simulation that incorporates photosynthesis and evapotranspiration and other forms of ecological processes."
"They would look at historical flood maps and essentially combine them with flood forecasting models i order to generate what is a given area going to look like if it gets flooded in the future because of climate change or for other reasons. And I was very enamored with that. I thought that was a very, very clever use of a technology."
"I think what we're doing definitely encompasses biodiverse native ecosystems and just restoring as many of them as we can throughout the most critical parts of the biosphere, that there are in this world. And also helping to switch our societal systems into more of a harmonious, and regenerative relationship with those ecosystems."
LINKS:
Earthshot Labs
Patrick Leung
QUOTES:
"We are able to actually bridge that financing gap and unlock a whole bunch of new projects that can then be in the carbon marketplace, and also bring a host of benefits to both the ecosystem, as well as, the communities that live around the ecosystem."
"Machine learning is really essential because what we're trying to do here is predict the future. We're trying to predict the next 30 years of a forest regrowing in a tropical region."
"We must look at the past. We must look at whatever data we can gather from the past state of the ecosystem and use various machine learning methods to predict the future in order to provide a view on what's gonna happen on this land in the future when we do this project."
"These are actual mathematical simulations that take into account the current conditions of the ecosystem and actually forecast them by using a kind of simulation that incorporates photosynthesis and evapotranspiration and other forms of ecological processes."
"They would look at historical flood maps and essentially combine them with flood forecasting models i order to generate what is a given area going to look like if it gets flooded in the future because of climate change or for other reasons. And I was very enamored with that. I thought that was a very, very clever use of a technology."
"I think what we're doing definitely encompasses biodiverse native ecosystems and just restoring as many of them as we can throughout the most critical parts of the biosphere, that there are in this world. And also helping to switch our societal systems into more of a harmonious, and regenerative relationship with those ecosystems."
LINKS:
Earthshot Labs
Patrick Leung
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