Consumer-grade maps only work if their vector data—the 2D and 3D building footprints, road centerlines, and land cover features that consumers interact with—reflects the world as it exists today.

But producing accurate, interoperable building footprints at national scale has traditionally required a tradeoff between quality, cost, and speed. Not anymore.

Vantor and Ecopia AI recently delivered more than 300 million 2D and 3D building vectors across India to a global mapping customer in just three months. Normally, delivering that many individual features would take years.

The coverage spans virtually all non-urban regions of the country, representing 3 million sq km of land, roughly 3% of the Earth’s habitable landmass. This milestone illustrates what automated mapmaking looks like when built on a precise, continuously updateable spatial foundation.

The scale of the mapmaking challenge

India’s landscape is changing faster than most countries in the world. The nation is home to more than 1.4 billion people, and its cities and towns are expanding rapidly to meet the demands of that growth. India’s built environment is transforming not just in its mega-cities, but also across smaller cities, rural towns, and growing peri-urban zones.

From a mapmaking perspective, this means constantly shifting built environment is difficult to keep up with. Drone or aerial surveys across millions of square kilometers are prohibitively expensive, manual feature extraction is too slow, and legacy imagery without precise alignment can yield vector data that shifts over time as new sources are added.

The challenge for our project was not simply to extract buildings. It was to do so across nearly all of India with consumer-grade accuracy without introducing vector instability over time. That’s a scale and pace that demands automation, precision spatial alignment, and tightly integrated AI workflows—the very capabilities that Vantor’s Vivid™ Features powered by Ecopia product is designed to deliver.

Automating mapmaking starts with an interoperable spatial foundation

The workflow began with Vantor’s high-resolution satellite imagery and automated spatial fusion capabilities. Drawing from our archive and newly tasked satellite imagery, we anchored all relevant data to Vantor’s globally consistent 3D spatial foundation, delivering a unified dataset with 3-meter CE90 absolute accuracy.

That specification ensures downstream interoperability. When imagery is consistently co-registered to a single spatial datum, every extracted feature inherits that alignment. When new imagery is processed later, it aligns to the same foundation. Buildings remain in place. Vectors don’t drift.

AI-driven extraction for automated production

With imagery precisely aligned, Ecopia AI applied its computer vision models to automatically extract building footprints. In just three months, the joint system generated more than 300 million building vectors across India’s non-urban regions and delivered the dataset to the customer for integration into production mapping workflows. With manual methods, this would have taken many years.

Because the source imagery was already spatially fused, the resulting vectors were geometrically consistent, interoperable with other map layers, and immediately ready for operational use.

This level of production at this scale and accuracy would traditionally require hundreds of analysts working manually over extended timelines. Instead, the system operated through automated, AI-driven workflows anchored to a trusted spatial foundation.

Redefining national-scale mapmaking

The India milestone is part of a broader trajectory for Vivid Features. For years, the mapping industry has operated under a constraint: quality, cost, and speed are competing forces. Optimize for two, and you compromise the third.

But by combining Vantor’s industry-leading satellite collection capacity, authoritative global-scale spatial foundation, and automated spatial fusion capabilities with Ecopia AI’s feature extraction capabilities, we can deliver consumer-grade building vectors across millions of square kilometers in months without compromising accuracy or interoperability.

As customers scale national mapping programs, the broader Vivid product suite also helps connect these workflows to Vivid Mosaic basemaps and Vivid Terrain 3D data for richer mapping and digital twin applications.

The India project represents one of the largest single national-scale implementations to date. More importantly, it demonstrates that automated vector production can operate at planetary scale without sacrificing accuracy or stability. Three hundred million buildings. Three million square kilometers. Delivered in three months.

When you pan out, the potential is even more clear. Since launching Vivid Features last fall, Vantor and Ecopia AI have produced billions of vector features globally—spanning buildings, road centerlines, and land cover layers—across North America, Europe, the Middle East, and Asia.

The is the future of automated mapmaking at national scale. This is the future of mapping, period.

To learn more about Vivid Features, reach out.