And this was an issue-buildings are more than just buildings-they’re landmarks and a key part of how someone knows where they are when looking at a map. Previously, an algorithm that tried to guess whether part of an image was a building or not resulted in what we dubbed “fuzzy buildings”-amorphous blobs that didn’t look like real buildings when you draw them on a map. Let’s look at how we map building outlines as an example. Machine learning allows our team to automate our mapping processes, while maintaining high levels of accuracy. To increase the speed of our mapping, we turn to machine learning. Imagery, authoritative data and human input have gotten us to where we are, but we want to make our maps more useful to more people even faster. Thanks to our newest trekker that is equipped with higher-resolution sensors and increased aperture, we’ve significantly improved the quality of imagery we capture. In the 12 years since then, our Street View car and trekker operations have collected more than 170 billion images from 87 countries. In 2007, Street View launched to help people virtually explore the entire world, from the depths of Antarctica to the top of Mount Kilimanjaro. Street View and satellite imagery have long been an important part of how we’re able to identify where places are in the world-it shows us where roadways, buildings, addresses and businesses are located in a region, in addition to other important details-such as the town’s speed limits or business names. Today, we’ll start with an overview of the basics. In a series of posts over the coming months, we’ll give you a closer look at how we build our map-diving deep into each of the elements we use to help more than one billion people navigate, explore and get things done. The answer is, it takes a number of different steps, and the right mix of people, techniques and technology.

Our role on the Google Maps team is to accurately model and reflect this ever-evolving world, and we’re often asked how we make a map that does that. The world is a beautiful, messy, constantly changing place-roads are added, buildings are built, and new businesses are opened all the time.

Google map world