A Plastic Story
Using Earth observation to stop plastics before they enter the ocean.
Measured Not Modeled.Each year, it is estimated that over 20 million tons of plastics finds its way into our oceans, directly causing over 10% of marine animal deaths.
Mismanaged plastic waste stems
from sources throughout the globe.
Models suggest that 122 river sinks contribute to over 90% of our oceans’ waste.
Once these plastics enter the oceans via rivers, they ride marine currents, making it nearly impossible to clean-up, impacting the lives of every animal along the way.
The scientific models show that the scale of the problem is immense. But the tools we have to fight it are outdated and imperfect, based on assumptions.
We need better information.
We need a clearer picture of these plastics
before we lose track of them.
After all, we can’t manage what we can’t measure.
We’ve built a reliable, scalable solution.
With the power of global, near real-time satellite imagery,
paired with data science and machine learning, we built
a first of its kind technology to identify terrestrial plastics waste from space.
Using it, we can now stop plastics at the source.
We started in Bali.
We know that there are 10 legal landfill (TPA) sites across Bali.
Using satellites, our technology is monitoring how these sites are changing day by day.
With known TPAs as a source of truth, we have trained our algorithms to scour satellite imagery across all of Bali to find dozens of illegal or informal plastics dump sites across the island.
Here's how it works...
This is Temesi, a known TPA site.
Here, we have trained machines to find needles in a global haystack.
Our technology assesses a growing library of multispectral satellite
imagery - analyzing thousands of combinations for each and every
pixel throughout a massive
geographic target area.
In doing so, we leverage a number of powerful views on the data, including...
Linear projection of all 12 bands to 3 dimensions preserving the most information. Principle component axes mapped to RGB color channels.
Non-linear mapping of 12-band signal embedding to 3-dimensional color channels. Closest visual representation of how a neural network might project the data.
Highlights vegetated vs. urban regions. Combination of 2186nm, 1610nm, 665nm bands.
Clearly delineates boundaries between land and water and captures soil moisture. Combination of 833nm, 1610nm, and 665nm bands.
Longwave imaging minimizes the influence of atmospheric absorption, but at a lower resolution.
Emphasizes chlorophyll concentration for vegetation health monitoring. Combination of 833nm, 1610nm, and 492nm bands.
Identifies geological features like faults, lithology, and formations. Combination of 2186nm, 1610nm, and 492nm bands.
Natural color representation of the scene. Data is not atmospherically corrected. Combination of 665nm, 559nm, 492nm bands.
Highlights vegetated vs. non-vegetated regions. Combination of 833nm, 665nm, and 559nm bands.
Identifies vegetation, forest, and bare soils. Combination of 1610nm, 833, and 665nm bands.
Used for monitoring drainage and soil moisture, as well as stages of crop growth. Combination of 2186nm, 864nm, and 665nm bands.
Useful for distinguishing agricultural varieties and health as well as barren lands. Combination of 1610nm, 833nm, and 492nm bands.
Leveraging the data hidden in each of these bands, our computers can interpret information that the human eye cannot.
We break down the satellite imagery into individual pixels of hyperspectral data. This creates a map of unique spectral signatures for each 10x10 meter pixel.
Next, we employ a neural network that is trained to pull out meaningful information from these spectral signatures.
Based on what the algorithm sees, it then assesses the likelihood that the pixel contains plastic.
Finally, we recompile all of the findings to assess the potential of plastics in a given area.
And the results are accurate.
Collectively, this space-borne data is more than just pixels on a screen - its actual plastic on the ground and it can be verified by researchers on motorbikes.
This is also Temesi, as recorded by Google Street View.
Temesi is just one TPA and Bali is just a small part of the world.
We have found 373 waste sites across Indonesia.
But this technology is extensible for the entirety of the globe.
It can be used to