Home News EarthDefine announces National Building Map for building footprint data

EarthDefine announces National Building Map for building footprint data

The National Building Map footprints include detailed building outlines, unique ids, coordinates, street addresses and source metadata for millions of structures.

USA: EarthDefine, a provider of high-resolution spatial data products, has released its National Building Map product that precisely maps over 137 million building outlines across the contiguous US. The dataset also includes accurate locations and addresses to support enhanced routing and rooftop-accurate geocoding for millions of properties across the country.

The National Building Map product is powered by state-of-the-art deep neural networks. These are a class of artificial intelligence (AI) algorithms that enable accurate extraction of ground features like building footprints from high-resolution aerial imagery across large scales and highly diverse geography. This AI-based approach allows EarthDefine to repeatedly extract building footprints from newer imagery that removes older buildings and adds newer construction to create a consistently updated snapshot of the built environment in the US. The building polygon data has an average accuracy of 98% and is updated every 3 months.

EarthDefine’s GIS-ready building footprints will help support better decision making in applications like insurance risk assessment and 911 response and routing that need accurate location data on built-up areas.

Besides providing universal addresses and geographic coordinates for all structures, EarthDefine can also extract additional property attributes on-demand like roof form, building elevation, eave height etc. through exploiting available Lidar for most regions in the US. “Our goal is to create and maintain state/national level building data with a unique and consistent attribute set,” said EarthDefine CEO, Vikalpa Jetly.

“We are achieving this best-in-class building footprint dataset through applying advancements in artificial intelligence (AI) to high-resolution aerial imagery. By constantly refining our algorithms and applying them to newer imagery every few months, we are able to provide building location intelligence that will remain current and useful for a range of GIS applications. For example, in our upcoming quarterly update, we will revise and re-map the majority of the buildings in the country using aerial imagery flown within the last 12 months.”