Complete Transcript

Complete Transcript

Narration:

Transcript:

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My name is Compton James Tucker,

and I am a scientist at the

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Goddard Space Flight Center.

We're very interested to improve

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our knowledge of the carbon

cycle globally. Where is carbon

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going in vegetation? And how

long does it persist? In the

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study, we use a large volume of

commercial satellite data,

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hundreds of thousands of

commercial satellite images at

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the 50 centimeter scale, to map

trees to identify trees in a

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semi-arid region, from the

Atlantic Ocean to the Red Sea in

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Africa, what we actually mapped

were tree crowns.

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We then use our tree crown data

to make predictions from the

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allometry, which was also

collected on the same region.

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And the data are very important.

The the processing code is

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important, the training data is

important. The allometry is

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important. And then

understanding the results that

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come out of those four

components. In the study, the

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study has been in the works

since 2015, or 2016. I started

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five or six years ago, draining

the archive of all of the data

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from Africa. This has taken me

three or four years to get all

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the data. Secondly, Ankit, who's

one of our team members, as a

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graduate student in computer

science, he wrote our processing

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code. And it's a highly

optimized neural net code, it

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works very well. He worked on

that for two or three years,

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then you need the training data

to go with the processing code.

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When you use machine learning or

artificial intelligence, you

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need to train on something so

you have confidence that that's

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what you're measuring. Training

data is where you go out and you

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select all different types of

trees. And they have to have a

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green tree crown and an

associated shadow to be a tree.

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And Martin Brandt did this over

three or four months, and

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selected 89,000 or 90,000

individual trees, it's a heroic

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effort. Now there are people

like Pierre Hiernaux, one of our

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co-authors who go out and they

sample trees and they measure

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the tree crown, they then cut

the tree down, they then measure

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the volume of leaves in the tree

crown. The same for the wood and

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the same for the roots. And so

we then convert the tree crown

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data which we measure into the

predicted leaf mass or carbon,

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the root carbon and the wood

carbon of every individual tree.

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You know, individual tree crown

is probably the highest

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resolution you're gonna get. And

like knowing the exact number of

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trees, and also when they have

leaves throughout the year is

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going to be really, really

important for improving our

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climate models.

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Then you put all this together,

and you run out on a

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supercomputer. So we would run

the data of this way, run it

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that way, then you take the

results. That's really the fun

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part of seeing what you did, how

well you did it, and what it can

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be used for.

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So the viewer is an important

tool for NGOs that are

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interested in understanding if

the tree restoration programs

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have paid off, but it can also

be used for the local farmer who

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would be interested in knowing

how many trees are standing on

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the fields, and are they alive,

are they dead,

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etc. With a viewer you can zoom

into individual trees and see

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how much carbon is there and the

leaves and the wood and the

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roots and the specific location

of that tree. Or you can

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aggregate the data up to an area

of 100 meters by 100 meters or

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one hectare. We plan to expand

our work next to Australia and

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then maybe to Eastern Africa,

Southern Africa, Central Asia,

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and possibly other arid and semi

arid areas.