Google today launched Kartta Labs, a scalable system on the open source Google Cloud and Kubernetes that reconstructs the city’s past from historical maps and photos. Available as a suite of tools, Kartta uses a searchable timeline to create maps, allowing users to enter historically accurate information on dates.
Kartta Labs was first introduced last year at an international workshop on AI for geographic knowledge discovery. According to the author, the motivation is to organize historical maps of the world and make them accessible and useful. Historical maps, which help identify cultural and social trends, are a valuable resource not only for citizen research, but also for planning and outreach. More than a decade ago, former Vice President Al Gore used past images from Google Earth to show that the polar ice cap was melting.
While there are other efforts to collect maps of the past into digital archives, Kartta goes beyond simple data collection to register maps in space and time. The Temporal Map Server shows how your map changes over time. Crowdsourcing platforms, on the other hand, allow users to upload a historical map of a city to match the actual coordinates. Another platform runs on the map and uses AI to rebuild the building to create a 3D experience.
The entry point is Warper. Warper allows users to modify uploaded images by finding points on the history map and corresponding points on the basemap. When a user uploads a map, Warper best guesses the location of the map by extracting textual information from the map. This first guess is used to place the map in an approximate position and allow the user to geographically reference the map pixels. After manually placing a pair of control points on the history map and reference map, the app uses geographic reference points to warp the image and align it well with the reference map.
Image credit: Google
The editor complements the warper. This tool supports time dimensions and integrates with other apps in the Kartta suite. This allows users to load modified historical maps and track geographic features such as footprints and road construction in vector format. At the front end of temporal maps, Kartta visualizes vector tiles, allowing users to navigate past maps in space-time.
The Karttas front end works like Google Maps, but it has a time slider to select the year on the map. Move the time slider to see how the features in the map change over time. According to Google, the next module, properly called a 3D model, reconstructs the detailed complete 3D structure of a historic building, associates images with map data, organizes these 3D models in a repository, and maps. Render on.
Raimondas Kiveris, senior software engineer at Google Research, wrote in a blog post that he developed the tools outlined above to facilitate crowdsourcing and address the main challenges of inadequate historical data. We hope Kartta Labs will serve as an active community of developers, map enthusiasts, and casual users who not only leverage historical datasets and open source code, but also actively contribute to both.
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