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Let me tell you how differently you’ll soon see the world, how it will change much of the way you work and live – and how optimistic I am about what we’re all going to see.
Over the past few years, we’ve seen the start of a new kind of information system; one that combines a stunning amount of remote sensing, both from satellites and on the ground, with the ability to manage and compute an unprecedented amount of real-time data. It’s like we’re holding a mirror up to our world, and for the first time seeing nature and society in all its glorious, real-time complexity.
It’s hard to overstate what a big deal this is. It will likely affect the way we manage the world’s agriculture and fisheries. It will mean a better understanding of supply chains, transportation, human migration and the way cities work.
Most importantly, it will be a key way we come to grips with the greatest challenge of our generation: climate change.
The people, governments and businesses that learn to use this system of technologies, collectively a new kind of tool involving global scale sensing, data management and computation, will have an important advantage in years to come.
It is what important new tools and technologies do: The invention of the telescope and the microscope (similar kinds of tubes and glass, viewed through opposite ends) spurred the Scientific Revolution. Standardized measurement arose in the late 18th century and enabled the Industrial Revolution’s construction of identical factories and products anywhere. The telegraph and telephone collapsed the time and space of communication.
The mirror of the world is still young and rapidly scaling. Just 50 years ago this July, three U.S. government agencies jointly launched Landsat 1, an orbital satellite capable of photographing the entire planet every 16 days in shades of red, gray and white. Landsat 9, launched last February, delivers 750 images a day in over 16,000 shades (the satellite it’s replacing could do just 256 shades). While there were just a handful of satellites in space 50 years ago, today there are over 6,500, measuring the Earth’s surface, magnetism, gasses and more.
That is only part of the transformation. Around the same time as Landsat, we saw the evolution of relational databases, where companies were formed to advance the efficient and useful organization and extraction of data. At the turn of the century, distributed systems for large data storage and analysis, like Dremel, opened the aperture to crunching petabytes of information in globe-spanning cloud computing systems. Many of these tools are critical to analyzing and modeling the world in ways undreamt of in our parents’ time, with near-100% uptime.
Today we see these elements come together in platforms like Earth Engine, a multi-petabyte catalog of satellite imagery and curated geospatial datasets capable of planetary-scale analysis capabilities used by academics, researchers, NGOs and now commercial organizations. Launched over a decade ago, the U.S. Forest Service uses it to study the effects of climate change, forest fires, insects and disease, creating new insights and strategies for success.
With the remarkable progress in the field of artificial intelligence (AI), we are seeing a growing field of applications of AI to the field of Earth observation. Last year, researchers at U.C. Berkeley introduced ways to use machine learning on the abundance of satellite images to generalize across diverse prediction tasks like forest cover, road length and house prices. Others have found ways to use deep learning to improve image recognition.
Marrying Earth observation capabilities with public, commercial and corporate data, analytics tools, and AI, companies are tackling business imperatives related to climate change and climate action. From climate risk modeling to sustainable sourcing, companies need tools and capabilities that enable them to better measure, monitor and improve their sustainability performance and those tools are evolving rapidly.
Even at the start of this new age of awareness, we’re seeing enterprises able to discern more effects of what they do, spot more connections, and fix more problems faster. Companies like Unilever are working to help end deforestation in their supply chain and improve both biodiversity and water usage.
There are hundreds of companies and institutions involved in these new technologies. Planet Labs operates a constellation of low-orbit, high-resolution satellites, to access terabytes of images from and to any point on Earth. NASA has an “Eyes on the Earth” download to measure water movement, volcanic eruptions, sea level height, atmospheric carbon dioxide concentrations, and more. There are many remote-sensing software packages available as open-source software, indicating much future innovation.
Putting it all together, the proliferation of satellites, rich data, and massive computation is a means to a new understanding of the natural world, complementing the way satellite systems already enable such things as global communications, driving directions, global inventory and payment systems, mining, even archeology. More images, more sensors, and more computation mean we’ll have a new understanding of soil moisture, watersheds and habitat health. We’ll be able to predict changes, and limit harm. We’ll have insights into how the world works, and what we can do to make it better.
Changing our environment for the better begins with understanding our environment better. There is no technology that will have more impact for this important goal.
Jenn Bennett, head of sustainability in Google Cloud’s office of the CTO.
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