Google Labs product called Google Earth Engine at the International Climate Change Conference in sunny Cancun, Mexico. Google Earth Engine is a new technology platform that puts an unprecedented amount of satellite imagery and data—current and historical—online for the first time. It enables global-scale monitoring and measurement of changes in the earth’s environment. The platform will enable scientists to use our extensive computing infrastructure—the Google “cloud”—to analyze this imagery. Last year, we demonstrated an early prototype. Since then, we have developed the platform, and are excited now to offer scientists around the world access to Earth Engine to implement their applications.
Why is this important? The images of our planet from space contain a wealth of information, ready to be extracted and applied to many societal challenges. Scientific analysis can transform these images from a mere set of pixels into useful information—such as the locations and extent of global forests, detecting how our forests are changing over time, directing resources for disaster response or water resource mapping.
The challenge has been to cope with the massive scale of satellite imagery archives, and the computational resources required for their analysis. As a result, many of these images have never been seen, much less analyzed. Now, scientists will be able to build applications to mine this treasure trove of data on Google Earth Engine, providing several advantages:
•Landsat satellite data archives over the last 25 years for most of the developing world available online, ready to be used together with other datasets including MODIS. And we will soon offer a complete global archive of Landsat.
•Reduced time to do analyses, using Google’s computing infrastructure. By running analyses across thousands of computers, for example, unthinkable tasks are now possible for the first time.
•New features that will make analysis easier, such as tools that pre-process the images to remove clouds and haze.
•Collaboration and standardization by creating a common platform for global data analysis.
