Page 130 - GIS for Science, Volume 3 Preview

118
GIS for Science
Planetary Computer
Humans still do not know enough about species, biodiversity, and ecosystems that are vital to our health and prosperity. Simply understanding the locations of where the world’s forests, fields, and waterways remains a daunting task of environmental accounting. Understanding what species call those ecosystems home and why they thrive or decline is largely unknown. We can’t solve a problem we don’t fully understand.
The UN launched the first worldwide assessment of natural systems in 2000, and it took nearly five years and more than 1,300 experts to complete. A more recent assessment by the UN Intergovernmental Platform on Biodiversity and Ecosystem Services, (IPBES), intended to close the gap between simple scientific insight and more effective policy implementation, and was published in 2019. As our environmental challenges intensify, the world needs greater access to better and better environmental data to assess, diagnose, and treat the natural systems that society depends on. Data powered by machine learning will make that possible.
Assessing the planet’s health must become a more sustained, integrated practice that allows us to understand what is happening in time to enable smart decision- making. Fortunately, technology potentially can revolutionize our environmental assessment practices, so they are are faster and cost efficient on a global scale. It should be as easy to learn about the environmental state of the planet as it is to search the internet for driving directions. We must use the architecture of the Information
Age—data, compute, algorithms, application programming interfaces and end- user applications—to accelerate a more environmentally sustainable future. Several years ago, we took our first step in this direction by launching Microsoft’s AI for Earth program to put AI technology into the hands of the world’s leading ecologists, conservation technologists, and organizations that are working to protect our planet. Yet for all the great work of our AI for Earth community, we have also learned it still needs much greater access to data, more intuitive access to machine learning tools, and a greater ability to share work and build on the work of others than our program currently provides.
Our community needs a new kind of computing platform—a Planetary Computer platform that can provide access to trillions of data points collected by people and by machines in space, in the sky, in and on the ground, and in the water. One that would allow users to search by geographic location instead of keyword. Where users seamlessly go from asking about what environments are in their area of interest to asking where a particular environment exists globally. A platform that allows users to provide new kinds of answers to new kinds of questions by providing access to state-of-the-art machine learning tools and the ability to publish new results and predictions as services available to the global community.
The Planetary Computer connects myriad data sources and AI analysis of Earth’s condition and what can be done to accelerate meaningful changes on how humankind manages the planet’s finite resources.