Introducing: Nearmap for Post-catastrophe Response
Post-catastrophe imagery and AI-derived property damage and condition data unite to help insurers process customer claims more efficiently.
Post-catastrophe imagery and AI-derived property damage and condition data unite to help insurers process customer claims more efficiently.
At a time of uncertainty in response to the pandemic—whether it’s a reduction of field visits to comply with lockdowns or a shift to digital project delivery—insights derived from aerial imagery with geospatial intelligence can help project teams stay ahead of the curve. When tasked with streamlining a project, aerial imagery can help reduce the need for site visits, saving time and cost. Further, the aerial imagery of today offers an immersive 3D environment with the addition of oblique multi-directional perspectives, 3D textured meshes and, more recently, AI-derived, planimetric vector data. These readily available insights can help with evaluating urban planning, engineering, transportation and telecom projects. Some common uses are accurate scenario evaluation, cost estimates, community engagement and change detection over multi-year projects.
Actionable 3D aerial imagery—particularly advanced AI-enabled solutions—enhance construction workflows with applications across a project’s lifecycle, from pre-construction planning and design to construction and maintenance, thus improving productivity and fostering better communication and engagement amongst the project team, with stakeholders and with the public.
Aerial imagery comes in a variety of forms: vertical, oblique, 3D and AI. These can be accessed from the office, or even remotely from the road, and provide a clear orthographic view of your jobsite. With Nearmap, engineers and project managers can see 2.2-3-in. resolution of over 1,740 urban areas across the nation, covering more than 80% of the population—all from their desk or mobile device. Then with Mapbrowser, Nearmap APIs or offline datasets, combined with CAD and GIS platforms and workflow applications such as Autodesk, Esri or Bentley, project teams are able to remotely view, measure and create project winning visualizations and designs.
The advantage of AI data in aerial imagery is quickly evident when it comes to quantifying the number or size of key map features. Case-in-point, Nearmap AI is a regularly updated, vectorized map with true location insights derived from machine learning which turns Nearmap imagery into quantifiable features and insights. Dr. Rob Newman, chief executive officer and managing director of Nearmap, explains, “What’s unique about Nearmap AI is that it combines the best of both worlds—data analytics and high-definition, frequently updated aerial imagery. And when you add Nearmap tools for measurement and location identification, businesses get a solution that will exponentially help scale up their insight-gathering efforts, with richer and more accurate data.” The image and object recognition product enables the user to look deeper into areas and parcels in seconds.
When asked about market specific areas such as the construction space, Dr. Michael Bewley, senior director of AI Systems at Nearmap, adds, “When you go from once-a-year execution of an AI system to multiple times per year, particularly in major cities, the value to the construction industry increases significantly. What we found with our early construction customers is that they want to see that greater frequency and also understand more about the stages of construction; so we responded.”
Aerial imagery with geospatial intelligence helps engineers, designers, project managers and other construction professionals focus on critical areas of concern. Tools such as 'AI Packs' unlock data about infrastructure assets. This information helps contractors, architects, engineers, utilities, telco, city planners and GIS professionals, identify and analyze assets, asset conditions and detect change over time. These data sets include: building footprints and characteristics, roof characteristics, solar panels, construction sites, surfaces, vegetation, roof condition and light and power poles, to name a few.
Using the AI Pack for Construction as an example, engineers can see AI layers such as construction sites, buildings under construction, construction cranes and vehicles to meet a broad scope of needs. These attributes can help with creating a site map to set up safety protocols, quickly identify areas of interest in the surrounding locations, identify tree overhangs on the site, and see other construction happening in the area that may cause supply chain interruptions. They can even identify poles within the area that may impact heavy machinery trying to move within the space. “The user can actually highlight the buildings that are somewhere between walls going up and roof being completed. They can see construction cranes and the machines working the site. With Nearmap AI, users move from assessing change after the fact to understanding what’s happening right in the middle of the progress,” Bewley concludes.
Power your decision-making with Nearmap AI—a regularly updated, vectorized map with true location insights, derived from high-resolution imagery.
Editor’s note: This article was initially published in the December 6/13, 2021 issue of ENR Magazine.
