When the Map Starts Thinking

For more than two decades, Elbit Systems has been advancing digital mapping - turning it from drawing the world to understanding it.

Omer, who has been part of this evolution almost since the beginning, now leads a multidisciplinary team of software, data, and AI engineers that serves as the execution arm of the C4I and Cyber Division's CTO organization, developing Elbit’s GIS core and toolkits.
“At Elbit, every project uses a map,” he says. “Aircraft, land systems, command centers - if there’s a spatial component, it’s built on our layer.”

At the center of that layer lies MAPCORE, a software library that underpins Elbit’s mapping ecosystem. It supports 2D and 3D visualization, geolocated video and imagery, sensor alignment, and spatial calculations. Whatever the data source - UAV, ground sensor, or border camera, MAPCORE keeps everything precisely aligned.

Over time, the ambition has grown from displaying the world to teaching systems how to interpret it.
 

From Seeing Terrain to Understanding It
 

Even the most realistic 3D maps stop short of true understanding - they look real but know nothing about what they show. Smart Reality bridges that gap. It adds a semantic layer that gives meaning to what’s on the map: a building is recognized as a building, a tree as a tree, a road as a road. The result is terrain that’s both visual and intelligent.

“Until now there were two worlds,” says Omer. “3D models that look real but know nothing, and databases full of data that have no image. Smart Reality unites them.” This creates a living, evolving model of the real world, one that not only looks like reality but understands what it’s made of.

Commanders can now analyze areas not just by geometry but by risk: which specific buildings pose a threat, which routes are exposed, even what happens if a structure is removed. "It lets you ask ‘what‑if’ questions that weren’t possible before,” Omer explains. “You start to see the environment in a completely new way.”

Teaching Machines to Read the Ground
 

As operational needs grew, Elbit expanded beyond visualization to Smart Terrain - a system and dataset that automatically interprets aerial imagery at national scale.

Using AI and cloud‑based processing, Smart Terrain identifies buildings, trees, vegetation, dirt paths, and even soil types. One unique capability is recognizing unpaved tracks - a feature developed entirely in‑house.

Working with military geologists, the system can also assess ground composition - information once reserved for experts. “A tank commander doesn’t need to be a geologist,” Omer notes. “But the ground makes all the difference. Smart Terrain delivers that insight instantly.”

This data powers a maneuver engine - think of it as a version of Waze built for off‑road movement. Instead of calculating traffic and speed, it evaluates terrain passability and suggests optimal paths for vehicles and troops.
 

Training Humans and Machines

Smart Terrain also supports hyper‑realistic training environments. Real areas, buildings, and vegetation can be digitally recreated, enabling forces to practice missions in exact virtual replicas of the field.

The same data fuels machine learning. Autonomous systems need large, labeled datasets to learn - something that’s often expensive or impossible to collect. Smart Terrain solves this by creating synthetic, photo‑realistic, and fully labeled environments at scale. “If you’re developing AI for a robot that will eventually process real imagery,” says Omer, “Smart Terrain gives you the data you need to train it.”
 

Looking Outward

Smart Reality, Smart Terrain, and MAPCORE are now ready for the next step - reaching global markets. “The technology is mature, and the demand is there,” Omer concludes.

After years of building the digital layer under modern defense systems, Elbit’s mapping technology isn’t just showing the world anymore, it’s helping us understand it.