What’s the story
Google is set to revolutionize the way users explore history with its upcoming update for Google Earth.
This new feature will allow users to view satellite and aerial images from as far back as 80 years, effectively doubling the current time frame of available imagery.
Cities such as London, Berlin, Warsaw, and Paris will have imagery dating back to the 1930s.
New feature enables historical comparisons
The upcoming update will not only extend the historical reach of Google Earth‘s imagery but also enable users to compare how cities have evolved over time.
This can be done by placing images side-by-side for a detailed analysis of urban development and changes.
Additionally, Google is redesigning the home screen of Google Earth to facilitate easier use and collaboration for researchers and organizations working on various projects.
Historical transformation
San Francisco’s transformation showcased
Google has provided a glimpse into the past by sharing images of San Francisco from 1938 and its current state in 2024.
The comparison reveals significant changes in the region’s geography over time.
For instance, ports that were primarily used for shipping in 1938 are now bustling with restaurants and cruise ships, highlighting the city’s evolution.
Update to be accessible on multiple platforms
The new feature will be available on both mobile and web platforms, making it widely accessible for users.
The rollout of these updates is expected in the coming weeks.
This development is part of Google’s broader initiative to enhance user experience by providing more comprehensive and high-quality content on its platforms.
Google to expand Street View and improve image quality
In addition to the historical imagery, Google is also expanding Street View on Google Maps in nearly 80 countries.
This will allow users to explore more content captured by Google’s Street View cars and trekkers.
The tech giant has plans to enhance the clarity of images on both Google Earth and Maps using new AI models like Cloud Score+ that can identify elements that degrade image quality while preserving real-world elements.