In telecommunications, precision isn’t optional. It’s the difference between success and setback.
Telecom networks are only as strong as the data they’re built on. Whether you’re deploying 5G, expanding broadband access, or planning fibre routes, poor data leads to poor outcomes. Missed connections. Budget overruns. Delays. Frustrated customers. The most costly mistakes often start with something as avoidable as an incomplete building footprint or an outdated terrain model.
At ONEGEO, we build geospatial data products that help you overcome these challenges, or avoid them from the outset.
By merging datasets from different sources—building footprints, building heights from LAS data, terrain models (DTM and DSM), and more—we eliminate the heavy lifting of data preparation. The result? Clean, ready-to-use data that saves you time and delivers the clarity your team needs.
How much time do you spend looking for and preparing data instead of using it? If the answer is too much, it’s time to rethink the source.
Let’s explore how accurate geospatial and 3D building data transforms network planning. And how you can try it yourself with sample data from ONEGEO.
5G Network Planning - Build Better 5G Networks with Real World Context
5G brings faster speeds and lower latency. But the signals are fragile. They don’t travel far, and they don’t handle obstructions well. Trees, rooftops, and even window tint can weaken or block a signal entirely.
That’s why high-resolution 3D building data is essential. Planners can use it to simulate how signals interact with real-world environments, right down to roof angles and facade textures. It shows where coverage gaps might form, where antennas should go, and where interference will be a problem.
Miss a new structure? Overlook a subtle slope? That’s how rollouts get delayed or underdeliver. With rich geospatial data built from DSM, DTM, and LAS inputs, you build networks based on how the world actually works—not how it looks on old maps.
When planning is backed by reality, deployments happen faster, perform better, and cost less.
Broadband Expansion - Expand Coverage with Smarter Location Insights
Expanding coverage isn’t just about identifying underserved areas—it’s about knowing exactly which homes and buildings need service, and which ones don’t.
Generalized maps can’t answer questions like: Is this a block of duplexes or high-rises? Are there 15 potential subscribers or 150? Are these properties homes, businesses, or schools? That level of clarity requires building-level detail.
With precise building footprints, use types and building heights, planners can align infrastructure with real demand - and deploy infrastructure accordingly. No more wasting CAPEX on streets that don’t need it, or missing blocks full of potential subscribers.
It’s also the data regulators want to see. Many broadband grants now demand granular evidence. And we help you provide it—with clean, cross-referenced geospatial data products that hold up under scrutiny.
Bottom line: smarter data leads to smarter investment—and a faster path to adoption.
Site Selection - Choose Telecom Sites Based on Performance, Not Availability
Finding a location is easy. Selecting the right one is hard. Rooftops, trees, terrain, and even elevation changes within a few meters can compromise site performance.
With merged datasets that combine building footprint geometry, building height, DSM/DTM, and land use data, planners can simulate line-of-sight, flag interference risks and potential obstructions, and select placements that maximize coverage. Even in rural areas, small shifts in elevation or vegetation can make or break a deployment.
And because we do the prep—merging, validating, and enriching data from multiple sources—you spend your time planning, not cleaning spreadsheets.
Demand Analysis - Match Infrastructure to Actual Demand, Not Just Population
Where people live doesn’t always reflect how they use the network. It’s not just about population counts. It’s about context.
Are you looking at a residential block filled with students who stream content 24/7, or a commercial zone where demand spikes during business hours? Are there multi-dwelling units with hundreds of potential subscribers stacked vertically, or scattered single-family homes that require a different infrastructure approach? A one-size-fits-all planning doesn’t cut it.
By combining detailed 3D building footprints with demographic and behavioural data, providers can identify patterns in data consumption, peak usage times, and density-driven needs. This level of insight transforms forecasting from guesswork into strategy. Providers can plan rollouts that align with real usage trends. And avoid the costly trap of overbuilding in low-demand areas or under-serving zones that are already stretched thin.
Data-driven demand analysis leads to better design, improved network performance, happier users, and, ultimately, higher ROI.
Signal Propagation - Simulate Signal Behaviour With Accurate Terrain and Geometry
Once a signal leaves a tower, anything can happen. It reflects, refracts, and weakens based on its environment. Materials, rooflines, and vegetation all matter.
Flat 2D maps can’t model that. Our data products, built from DSM, DTM, and detailed building geometry, can. They allow you to simulate signal behavior with precision and place infrastructure with intent, not based on trial and error.
That means fewer dead zones, fewer complaints, and fewer costly fixes post-launch.
The Value of Getting It Right. And How To Get Started
Bad data delays projects and drains resources.It slows everything down before the first trench is dug.
At ONEGEO, we merge data from multiple sources so you don’t have to. Our building footprints include heights. Our elevation data is pre-aligned. Our LAS files, DTM, and DSM layers are harmonized—giving you clarity from day one.
You move faster. You model more accurately. And you avoid the churn of data prep that eats time and inflates costs.
Want to see it for yourself? Download a sample dataset and explore what ONEGEO can unlock for your network planning.
Smart networks start with smart data. Let’s build it right together.
