Neale shared that Nearmap are now able to capture at just 1.5 cm resolution, even higher resolution than the already very detailed 4.4 cm resolution images a testament to Nearmap’s investment in R&D and ownership of the complete technology pipeline.
But the real breakthrough lies in automation. “If we can bring imagery, AI data and terrain models together, we can automate entire workflows,” said Neale. “Like modelling the spread of sound along a new motorway in minutes.”
“That’s what geospatial intelligence looks like: using data to measure what we can’t physically see.”
This greater clarity means greater confidence. The ability to detect features more precisely, classify them automatically and feed them into digital engineering models is accelerating project timelines and reducing error. In other words: efficiency equals profitability.
Reducing risk and rework
The impact of that intelligence can already be seen.
Ausgrid has built a fully-modelled digital twin of the electricity network that now integrates LiDAR, aerial imagery and asset data for 25,000 km of lines. By using AI to detect vegetation encroachment and structural defects, engineers can predict faults before they happen, preventing outages and costly emergency callouts.
“It’s about turning pixels into prevention,” said Alex Watters, Manager of Asset Insights. “It lets us do [things like] vegetation risk analysis, structural modelling, even predictive maintenance.”
At Jemena, location intelligence has become central to both safety and savings. “Recently it was discovered that a homeowner had built a structure over a high-pressure gas main,” said David Morgan, Geospatial Operations Lead. “By using the timeline feature in Nearmap we identified when it was built and confirmed there was no approval in place. The owner removed the structure, reducing the hazard, and Jemena avoided significant relocation costs.”
The same platform now supports AI-powered analysis of vegetation patterns and encroachments. Nearmap enables Jemena to prioritise maintenance more accurately and reduce site visits. “Nearmap helps us see risks and issues early,” he said. “That visibility lets us act sooner and optimise our field workforce planning.”
Powerful oversight
Over at WSP, Henry Okraglik, Global Director of Digital is using spatial data tools to identify dangerous historical mineshafts in Victoria.
“We used AI to determine where the shafts might be and matched them with known records at a very high degree of accuracy,” Okraglik explained. “It’s hard to believe, but we mapped more than 200,000 undocumented shafts. The same methodology is soon to be used in the US.”
What’s striking about projects like these is how far they extend the traditional bounds of mapping. Geospatial data is not a passive record, it is now an analytical tool.
“We’re combining AI with digital engineering to solve problems you couldn’t even visualise before,” said Okraglik. “From energy storage siting to flood route analysis, the intelligence is in the relationships – topography, proximity, transmission, noise, zoning – and how they interact.”
Building resilient networks
For Diana Zagora, Director of Civil Infrastructure at Transport for NSW, the most powerful outcome of location intelligence is resilience.
“We’ve been using spatial tools and drone technology to inform our road resilience plans” she said. “By fusing AI with imagery, we can detect structural and environmental issues early. It’s safer, faster and gives us real-time condition data.”
Her team’s bushfire-risk assessment tool combines vegetation analytics and cultural landscape mapping to prioritise works. “Every dollar invested in proactive resilience saves between two and eleven in recovery,” she said. “Location intelligence makes that possible.”
At Victoria’s Department of Transport, the next leap is integration.
“We’re using AI and geospatial data to automatically identify road asset condition,” said Amy Lezala, Chief Engineer – Rail. “Vehicles capture high-definition imagery and AI pinpoints defects. It’s faster, more objective and far safer than traditional inspection methods.”
She said the benefits of this digital-engineering approach extend far beyond efficiency. “Being able to see the assets, understand what’s out there, their age and condition, it’s really rich data,” Lezala explained. “That benefits the economy because we can be more efficient in our design processes. We’re not wasting money flattening 3D models into 2D drawings only to build them back into 3D model. It reduces a significant amount of time and effort.
This integration of AI and location intelligence now feeds directly into Victoria’s Digital Engineering framework, ensuring that asset health, location and performance are unified across projects. “It’s about creating a connected view,” Lezala said, ”and it reduces a significant amount of wasted time and effort. It also benefits society and the environment, because we’re looking at more sustainable solutions for all of this technology.”
Shared intelligence
Though use cases are diverse, there was one common thread across both panels: geospatial data should be a shared asset – not a specialist tool.
“It’s about integration,” said Damien Cutcliffe, WSP. “Bringing environmental data, asset intelligence and digital twins together – that’s where you get scale.”
Watters agreed: “The value comes when design engineers, maintenance teams and planners are all looking at the same reality.”
For Nearmap’s Rob Malkin, that’s central to the company’s mission.
“We’re not just here to capture imagery – we’re here to enable better decisions,” he said. “What matters is giving engineers and planners intelligence they can act on – to build safer, smarter, more sustainable infrastructure. That’s the future we’re building together.”
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