# How to See (and Stop) Deforestation from Space | Tasso Azevedo | TED

## Метаданные

- **Канал:** TED
- **YouTube:** https://www.youtube.com/watch?v=S_GuLdbMveQ
- **Дата:** 16.12.2025
- **Длительность:** 9:47
- **Просмотры:** 15,093

## Описание

Nearly 20 trees are cut down every second in the Amazon rainforest, as authorities struggle to monitor millions of acres and stop illegal clear-cutting. But land reformer Tasso Azevedo and his team at MapBiomas have changed the game, transforming satellite imagery into precise, real-time maps that make every clear-cut visible — and every actor accountable. Learn how they're helping slash deforestation in the Amazon, proving that transparency is a forest's strongest defense. (This ambitious idea is part of The Audacious Project, TED’s initiative to inspire and fund global change.) (Recorded at TED Countdown Summit 2025 on June 18, 2025)

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https://youtu.be/S_GuLdbMveQ

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## Содержание

### [0:00](https://www.youtube.com/watch?v=S_GuLdbMveQ) Segment 1 (00:00 - 05:00)

(Chainsaw buzzing) (Tree crashing) 20, 40, 60, 80, 100. In every second on the last 12 months, almost 20 trees were cut down in the Amazon. See, deforestation and degradation is a kind of a disaster for the only country in the world that is named after a tree. Brazil is the fifth-largest greenhouse gas emitter on the planet, but different from the top four, the bulk of our emissions do not come from burning fossil fuels. It actually comes from the way we use the land. That's 75 percent of our emissions. The majority of that results from forests being cut down. You see, tropical forests are like the lungs of the Earth. You heard something like that before, right? When we cut them down, they essentially exhalate the carbon that has been stored for over many decades, and they no longer exist to absorb the carbon and to maintain the evapotranspiration that keeps the cooling system of the planet. In 2024, the countries with the largest areas of tropical forests, like Brazil, Peru, Congo, Indonesia, lost an area of forest the size of Rwanda. And this forest has been converted to pasture, croplands, urban areas, mining and also suffering degradation from logging, increased droughts and wildfires. So we need to fight this degradation, and in order to do so, we have to understand what's happening on the ground. So digital mapping can be a key role on that. Because maps, maps have power, but only if you can understand really what's going on the ground. So global satellite technology allows us to see the world in the palm of our hands. But these are just images. In order to understand what's happening with the land use, you need to capture the context of what we are seeing so we can understand the transformations across the time. And then we can act. So take a look at this pair of images in the Amazon in 1985 and 2023. On the first one we see a lot of this green and on the second, more of this light pink. But what is going on? We don't really know. Now look, this is the same piece of land, but now we have a map that shows that forest, in green, has been converted into pasture, which you see in yellow, or some croplands like soybean, sugarcane, which you see in these different shades of pink. You also see a kind of a blue color, which is a hydropower lake, and also some urban areas growing on red. Until very recently, a detailed map like that for an entire country like Brazil was almost impossible to make because it was too costly and too slow to produce. So back in 2015, we put together a group of experts in remote sensing, computer science and land use to reinvent the way we produce and publish maps. We call it MapBiomas network. And now we can produce 40 years of map in six months. We do it by creating a mosaic of all the existing satellite images that we have for every year since 1985. Then we apply machine-learning algorithms that allow us to classify each pixel and make a layer for every land use class that we want to map, like forests, mangroves, cropland and water. Then we put all those layers together and produce a time series with one integrated map for each year. Now we have this kind of time machine where you can see every pixel and see the history of those pixels of 30 by 30 meters, there are 9. 6 billion of them, that makes up Brazil. So, for example, on this blue dot there, you see like something that was a forest in '85, then in '95 was converted to pasture, then in 2005 was converted to soybean, and so on. So now we can see the history of everywhere in the country in any time in the last four decades. But how [could this] lead to change? Have you ever crossed the red light and received, like, a penalty by email

### [5:00](https://www.youtube.com/watch?v=S_GuLdbMveQ&t=300s) Segment 2 (05:00 - 09:00)

showing the license plate of your car? No, because TED people don't violate the law. (Laughter) Yeah, but that's me. (Laughter) Yeah, it's a clear evidence that I violate the rule. And, you know, like, I can't deny, right? So something very similar can be done with deforestation using remote sensing. Every time there is a deforestation detected in Brazil, we use high-resolution satellite imagery to validate precisely when and where the deforestation has occurred. Then we cross this information with the land cover maps, the registry of the land properties, the catalog of protected areas and even the authorizations for clear cut so we can produce very detailed reports like this one. In 2018, all the environmental agencies in Brazil together produced less than 1,000 reports in one year. Last year in MapBiomas, we produced 2,000 of those reports per week. Those reports have a level of granularity and precision that can literally be used in the court of law. So in fact, between 2019 and 2024, the actions from the environmental agencies in Brazil against illegal deforestation increased from five to 54 percent of all deforestation. (Applause) It's also happening in finance. So in the last two years, the major banks in Brazil denied 1. 5 billion dollars on finance for 30,000 farms that have deforestation detected by MapBiomas. And this money went to more sustainable operations. So this, together with several other actions, allows Brazil to decrease the amount of deforestation in the Amazon by 54 percent in the last two years. And this -- (Cheers and applause) Which saved all of us 500 million tons of CO2 emissions. So this goes much beyond deforestation. In fact, in the last year, over 600,000 users access our data and apply on hundreds of applications like, for example, preventing tropical disease, regulating the use of water, assessing climate change impacts, designing soil conservation practices and protecting Indigenous land rights. And actually, there's a good example here. You know, illegal gold mining is a huge problem in the Amazon. It destroys the land, it pollutes the water and poisons Indigenous people. So back in 2023, the Brazilian government decided to take action to remove 30,000 gold miners from Indigenous lands. And one of the key strategies to do so was to shut down the airstrips that were close to the mines in remote areas, so the miners could not take the gold out of the forest so they have to leave. So in order to do so, you have to find out where are those airstrips, right? So in just three weeks, our team was able to find out and map almost 3,000 airstrips across the entire Amazon, which is an area the size of Europe. So as of today, the number of gold miners in Indigenous lands has dropped 90 percent. (Cheers and applause) So none of that would be possible if we're not applying a kind of collaborative approach. So MapBiomas network is a group of over 100 organizations working across South America and Indonesia. And now, with the support of TED community, through The Audacious Project, we aim to increase our reach to cover 70 percent of the world's tropical forests by 2030. We believe that this, you know, the ability and the power to produce locally your maps for action should be present in every tropical country. And then we can exchange the sounds of destruction -- (Chainsaw buzzing) [With] the sounds of life. (Birds chirping) (Cheers and applause)

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*Источник: https://ekstraktznaniy.ru/video/565*