Rosreestr, Russia’s federal agency responsible for state registration of real estate and cartography, is preparing to integrate artificial intelligence into its workflow for updating maps using satellite imagery. The move is designed to speed up the processing of data obtained through remote sensing of the Earth and minimize the need for time-consuming manual interventions.
The agency has already begun shifting toward distant Earth observation technologies for mapping the country’s territory. Now it wants to enhance this approach by adding generative and analytical AI tools that can automatically identify changes on the ground. This follows the signing of a roadmap between Rosreestr and Roscosmos on the use of space-derived data for cartographic purposes.
As part of the new initiative, Rosreestr is launching a pilot project focused on monitoring terrain changes based on orbital photographs. Satellites will capture images from space, while AI algorithms will analyze them to detect modifications on the Earth’s surface. The resulting information will then be used to update cartographic materials much more rapidly than before.
According to Deputy Head of Rosreestr Maxim Smirnov, the introduction of AI is expected to significantly raise the speed of map updates, increase overall labor productivity, and make government budget expenditures more efficient. The project is viewed by the agency as one of the most breakthrough developments in modern Russian cartography.
To advance the technology, Rosreestr intends to engage IT companies. These organizations will be offered access to space imagery together with vector and registry data at different scales. After evaluating the submitted solutions, the agency plans to select the most effective monitoring technology for nationwide implementation.
The ultimate goal is to move away from slow, complex, and manual map-updating processes. Instead, Rosreestr aims to rely on continuous satellite observations combined with automated change-detection algorithms. For a country as large as Russia, this space-based and AI-assisted method offers a practical and scalable alternative to traditional ground surveys.
