Okay, I am here in Northern California
at home where objects like this air quality meter,
and this respirator have sadly become
pretty common household objects.
The fires have been raging in California
and the West more broadly for many weeks
and destroying homes and people's lives,
and ruining the air quality for the rest of us
in the process, which is what led me
to the company we're gonna talk about today,
which is called SALO Sciences.
The CEO is a gentlemen named David Marvin.
What this company is trying to do,
is apply satellite imagery,
computer vision technology and algorithms,
and just hardcore cloud computing, data crunching
to give us a much better idea of the health
of our forests, and whether they may pose a fire risk
in specific regions.
In the bigger picture, the idea is that this technology
could be used to really take care of our forest better,
and reduce the risks of fires,
and other climate problems moving forward.
So with that, let's head to SALO Sciences,
and figure out how their technology works.
Well tell me a little bit about the background
of this company, and what you guys are up to.
So SALO Sciences is a conservation technology company.
My co-founder Chris Anderson and I,
we both come from academia.
We're both forest ecologists by training,
and we both met at a lab where we saw
the need to be bringing cutting edge technology and science
out of the academic realm and operationalizing it
for organizations that are working to scale up
what's called the nature based solutions to climate change.
And so these are activities like reforestation,
or forest restoration, land conservation,
really anything that leaves more carbon
on the earth's landscape
than lets it back into the atmosphere.
We're trying to build the tools and solutions
that let governments, or non-profits,
or even corporations,
we're trying to implement these solutions at scale
that can really help make a meaningful difference
in the fight against climate change.
So we just launched the forest observatory a month ago.
This is our first trip to the field to do this,
and we'll want to come out here much more times
over the next year,
across different parts of California,
to do the validation.
What you're seeing here is US Forest Service land
in the Tahoe National Forest that was thinned recently.
If you were to instead leave it in its previous state,
where you had dense trees growing near each other,
much smaller, branches much lower to the ground,
what would happen as a fire burned through,
it could begin catching on the lower branches,
catching on the smaller trees,
and begin laddering up into the canopy of these trees,
and once that happens,
they can, the fire can jump from crown to crown,
and become catastrophic, killing off a lot of the trees
and causing a lot of damage to the forest.
This is a really dense forest stand
that probably pre-thinning would be this entire area.
So the trees are much closer together.
They're smaller in diameter for the most part.
You see a lot of understory buildup of the
what we call ladder fuels.
What we're trying to do with the forest observatory
is be able to map over the entire state
all of the areas that are still
in this kind of really dense, highly stocked state.
From there, the Forest Service, State of California,
part landowners, can begin planning how to restore
the forest back to a fire resilient state.
You know one of the areas I've been tracking
for a long time, or for a decent amount of time,
is using satellite imagery
as sort of like this accounting system of the earth.
You know, we can track deforestation now,
we can like literally kind of make counts
of all the trees on the planet,
and how these things are changing.
I know you guys use some of these tools,
but I mean, I have to assume for this type of work,
the advances in technology that have taken place
over the last five years is kind of like
what's opening up this opportunity
to modernize how this type of stuff gets done?
We see there's three key advances
in the last, you know, decade or so
that has really allowed us to exist as a company,
and a lot of really amazing scientists do a lot
of great work at the scale of the entire earth.
These are the advent of satellite constellations,
those like Planet Labs and Capella Space
that are launching these, you know,
really amazing high res sensors that capture
the entire surface of the earth every day,
combined with a really cheap cloud computing.
So to process the insane amounts of data coming down
from space every day, you got to have a lot of computers,
and you've got to be pretty cheap to run those.
And then the third major advance
is really artificial intelligence,
and the different kind of branches of AI
that are now out there.
We're mostly working with what's called deep learning,
and this is a really great technology that allows you
to extract really subtle complex multi-dimensional patterns
from these satellite images,
and turn them into information that's really valuable.
In our case, this is patterns of ecological attributes,
or ecological change, that we can use
to understand our earth in a much better way.
And just to kind of help make this clear for people,
I mean, give me like one or two very specific examples
of projects that you guys have done.
We just released our first major product.
This is called the California Forest Observatory.
And so this is a system we built
with all those tools I just mentioned,
you know, cloud computing, high res satellite imagery,
and deep learning to be able to map all
of California's lands in high resolution,
in the current year, and do this over time,
so we can begin monitoring how the landscapes
of California are changing.
And we did this specifically in the context of wildfire.
So California, as many folks are aware,
is going through an extraordinary wildfire season right now.
We're just halfway through.
We've already burned more than 4 million acres of land.
Now, not all of that is destructive and catastrophic fire.
A lot of that is fire we need to have on the landscape,
but there are a lot of areas that
have experienced catastrophic mega fires
that have burned homes, destroyed communities.
We're trying to be able to build a system,
and we have at least a system that lets us understand
the fuels buildup across California
to get a better sense of where future wildfires
might get out of control.
And more importantly,
where to go and do the restoration work
across California to reduce the potential
for those wildfires to make a catastrophic impact
on our natural resources, and our communities of the state.
If you try to build one of these models,
I mean, so you guys have focused on California so far,
so if like Australia comes to you and they say,
we want a model, you know,
for the entire country, what would that entail for you guys,
and like how long would it take to build something
that was fairly detailed?
One of the great things about this technology,
deep learning, it takes a lot of time, and energy,
and money to be able to train these algorithms
to the point where they can recognize things
like the height of trees in satellite images.
Once you've done that, it's learned the basic patterns
in the satellite imagery
that can relate to the height of that tree,
and there isn't such variation in trees and in imagery
to the point where if you were to take a trained model
in California and apply it to a forest in Australia,
it will start predicting like negative tree height
or something, right?
You know, it's gonna generally recognize
what it means to be a tall tree,
so all you have to do at that point
is then tweak it just a little bit more,
transfer the knowledge it took out in California,
and tweak it to work in Australia.
It still seems like you're optimistic about,
you know, that this sort of technology actually
can make a significant difference,
not just like in 50, 100 years,
I mean, the way you were talking, it sounds like,
I mean, we could actually use this practically
in the, you know, the next two,
five, 10 years to have some significant effect on things.
So yes, I'm optimistic that, you know,
the technology can play a role,
but it really doesn't work
without the policy to implement the technology.
It doesn't work without the funding that we need
to do the actual work on the ground.
You know, just because we're experiencing
a once in a lifetime pandemic
that, you know, it was destroying a lot of budgets
around the country,
doesn't mean we don't have to still think
about the larger problem of climate change.
That isn't going away,
and as we saw from the decline in emissions
during the early parts of the lockdown,
even stopping driving cars,
and not going to work anymore,
only caused a small blip in our emissions.
There's much bigger systemic changes
that have to occur globally
for us to really tackle this issue,
and it's not gonna be a simple decision
that we can each take.
It's gonna be a collective decision
across nations, across communities,
and we've got to start working on that now,
but I do think we can do it.