How Satellites Are Supporting Farmers Across Africa | Catherine Nakalembe | TED
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DownloadIf farming was your primary source of income,
and if you can't grow anything,
there's not much you can do.
It's very demoralizing.
It's very overwhelming.
A lot of the countries where I work, farmers face fires, pests,
diseases, droughts and floods.
If crops fail, no food is available for a lot of people
who depend on what they produce.
It translates into, you know,
sometimes an entire generation being undermined.
My name is Catherine Nakalembe
and I'm a satellite food security specialist.
I use satellite data to map and monitor crops,
and then work to make sure
that information can be used by decision makers
and organizations that support farmers.
I primarily focus on Africa:
Uganda, Kenya, Tanzania, Zambia,
Mali, Senegal.
Last time I checked,
there were over 8,000 satellites observing our Earth.
They take pictures every day.
You can use those images
to map what crops are growing where,
how much it's going to rain,
where weather system might be coming from,
where it might be impacted
and how badly it might be impacted.
I can just sit on my computer and tell you anywhere in the world,
rainfall, drought, floods, name it.
I can tell you where it is.
We have tons of information, tons of data about what's happening.
We're living in a fantastic age.
We have huge advances with AI.
We're able to process a lot more data and information.
The problem is,
when you look deeply at any place,
you start to see problems with a lot of the existing products.
They're not tailored to the on-the-ground contexts.
Sometimes it's simply that the data is just wrong.
A lot of the models are trained very well
to predict for European or US agriculture.
In Europe, most of the farms have like, a single crop.
They're really big and it's very easy to model.
In Kenya, in Uganda, in Rwanda, however,
the fields are so tiny,
they have so many different crops in them,
and farmers do things so differently.
It's like a tapestry.
With those images fields are misrepresented.
So there are places where there are no crops
but are labeled as crops.
There are places where there should be crops and people
that are completely missing.
When you go and try to assess something for the ministry
and you use that as input,
you're basically feeding them garbage.
You want to make sure that what you're feeding in is really good,
and that actually requires work.
To train a model to understand that complexity,
you need a lot of examples.
You have to go on the ground.
What we did is we use GoPros.
You wear a GoPro as you're driving
on a motorcycle, or you can do it in the car.
And as you drive we take pictures.
Basically Google Street View,
not for streets but for crops.
So the camera is actually facing towards the field
and then adapt basically what would be face detection
but instead of detecting faces, cats, dogs, etc.,
we modified it to detect maize, beans, cassava.
We covered all of western Kenya in two weeks with just two teams,
collected over five million images.
A lot of them with volunteers every day,
mototaxi drivers, students.
This would allow us to build a more complex model
that can learn from all these different examples,
from all the different contexts.
There was a flood in Kenya in 2024.
It happened really, really rapidly.
And, you know, the entire country was affected, pretty much.
I got an email from the Ministry of Agriculture asking to do an assessment,
using satellite data to look at where floods happened,
where were crops,
and give an estimate of what the total area of cropland
that's been affected was.
And then what the ministry does with the information
is they make their response programs,
which is where do we need to go to provide seeds so people can replant.
It's an example of an action that was taken.
It's really powerful to be able to do that.
True innovation is not about high-tech systems,
but about making the technology fit the problem.
We have to provide really good information to the people
who can do something with it.
If we do this correctly, we can save time,
we can save money,
we can save livelihoods.
Key Vocabulary (50)
toward
"Go to school."
belonging
"Cup of tea."
also
"You and me."
inside
"In the house."
specific
"That book."
A third-person singular pronoun used to refer to an object, animal, or situation that has already been mentioned or is clear from context. It is also frequently used as a dummy subject to talk about time, weather, or distance.
Used to show who is intended to have or use something, or to explain the purpose or reason for an action. It is also frequently used to indicate a specific duration of time.
A function word used to express negation or denial. It is primarily used to make a sentence or phrase negative, often following an auxiliary verb or the verb 'to be'.
A preposition used to indicate that something is in a position above and supported by a surface. It is also used to indicate a specific day or date, or to show that a device is functioning.
A preposition used to indicate that people or things are together, in the same place, or performing an action together. It can also describe the instrument used to perform an action or a characteristic that someone or something has.
A conjunction used to compare two things that are equal in some way. It is most commonly used in the pattern 'as + adjective/adverb + as' to show similarity.
Used to refer to the person or people that the speaker is addressing. It is the second-person pronoun used for both singular and plural subjects and objects.
A coordinating conjunction used to connect two statements that contrast with each other. It is used to introduce an added statement that is different from what has already been mentioned.
Used to indicate the starting point, source, or origin of something. It can describe a physical location, a point in time, or the person who sent or gave an item.
A third-person plural pronoun used to refer to two or more people, animals, or things previously mentioned. It is also commonly used as a singular pronoun to refer to a person whose gender is unknown or to someone who identifies as non-binary.
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Description
More than 8,000 satellites orbit Earth, taking photos every day. Food security specialist and TED Fellow Catherine Nakalembe shows how she uses this imagery to help smallholder farmers across...
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