Plan for risk with an intelligent view
Jan 2025
Asset managers can meet new fulfilment benchmarks with easy-to-use geospatial intelligence — accurate, shareable insights at a click.
Jan 2025
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Managing diverse asset portfolios across large geographic areas — from single suburbs through to entire states and even nationwide — eats up up valuable time and labour.
Now, automated asset management is possible with remote inspections powered by the most up-to-date and accurate aerial imagery and location intelligence.
Without that technology, on-the-ground asset managers will stay stuck with time-consuming manual inspections leading to higher asset management costs.
While drones can form part of an asset management plan for smaller inspections on single buildings or across small areas, once you take into consideration flight restrictions, infrequent surveys, and the expensive logistics of data processing, the economic viability of drone imagery falls short.
If you have asset portfolios spread across large areas needing frequent updates, you need a low-touch option. Aircraft-captured imagery delivers clarity at scale, putting you ahead of the competition.
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Aerial image clarity is measured by a factor known as ‘ground sample distance’ or GSD: the lower the number, the better the clarity. Satellite imagery generally offers around 30cm GSD, and drones approximately 1.5–2.5cm GSD. Nearmap imagery hits the sweet spot, with GSD of 5.5–6.5cm per pixel, giving you more workable clarity and economies of scale.
Not just high-res images: verifiable insights
Every Nearmap survey is published as a high-resolution aerial map that includes rich geospatial intelligence, ready-to-use in MapBrowser, our web app, or exportable into your existing systems using an API.
The image of the warehouse above shows some of the features that can be identified, with a click, at scale, with Nearmap AI:
Asphalt = yellow
Concrete slab = pink/purple
Metal roof = orange
Medium & High Vegetation = green
Tree overhang = red
Concrete slab = pink/purple
Metal roof = orange
Medium & High Vegetation = green
Tree overhang = red
The Nearmap AI machine-learning model automatically detects more than 130 different property and environmental features in every Nearmap survey published. These features include pavement markings, yard objects, construction sites and more. Nearmap AI can even differentiate commercial or residential roof objects, and whether a rooftop solar panel is photovoltaic (PV) or hot water. Such insights save time and reduce error rates.
See what’s changed – and predict what’s likely to...
Geospatial AI makes it easier to identify changes that have occurred since previous inspections. You’ll be able to see changes in the condition of buildings and roofs, track construction progress, and see how vegetation has changed.
Nearmap AI is trained to detect not only varying density of vegetation — from very low to medium-high — but also areas of vegetation overhang in relation to surrounding buildings and assets — essential knowledge to set you up for more effective condition monitoring for risk management.
And with a library of past high-resolution surveys, it’s easier to accurately track the condition of assets over time, for more accurate predictive risk management.
The imagery below shows the course of construction at Barton Park in Banksia, NSW, Australia.
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Map out maintenance early
Proactive asset risk management with aerial imagery involves far fewer site visits than traditional on-site inspections. With Nearmap you can easily spot issues before damage escalates and and costs blowout. For expensive components like roofing materials or rooftop assets such as solar panels, water tanks and air-conditioning condensers that are susceptible to damage by severe weather, being able to see damage and act quickly helps minimize the financial impact.
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Save hours on risk audits
Gain new perspectives on obstacle surface limitation (OSL) around airports and transportation assets with the ability to see and measure vegetation, assets, and pavement (runway) markings, knowing which assets need priority attention.
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Empower lease negotiations
Enter lease renewals and agreements with greater confidence, armed with the full high-res picture. With a clear, measurable view, you can spot any changes or deterioration over time since previous surveys. With output from an API managed by your in-house GIS team, this process can be automated to send alerts as soon as the AI identifies changes to flagged assets.
The image below shows Nearmap AI being used to automatically identify roof ponding – the staining of a flat roof caused by residual rain water not draining properly.
Some of the other 130+ features detectable by Nearmap AI include rooftop materials, pervious/non-pervious surfaces, asphalt, concrete, roof ponding and rusting (as shown above and below), temporary repairs and vegetation which may affect the long-term condition of your assets and properties.
The image below shows Nearmap AI identifying areas of roof rusting in red.
De-stress asset management
Reduce risk today: take a look at how Nearmap can help you work with a clearer view of your asset portfolio.