Hurricane Florence Imagery Incorporated in Esri ArcGIS - 26/09/2018
As Hurricane Florence slowly moved inland, The Geospatial Intelligence Center (GIC) began flying planes over the Carolinas, taking ultra-high resolution images of the damage and flooding. The resulting imagery, incorporated into Esri's ArcGIS cloud-based mapping platform, can be viewed here.
By typing in an address, the aerials of the property will appear with a slider that moves to show the before and after views. A dozen planes, each equipped with a $1.5 million UltraCam sensor from Vexcel, will be documenting the damage to provide insurers with vital information that will help them respond and pay claims faster to help victims get on the road to recovery. The imagery will also be provided at no charge to emergency personnel, first responders and law enforcement to assist in their response to the damage.
This effort is part of the massive data collection and processing system spearheaded by the National Insurance Crime Bureau (NICB), whose member companies write almost 80% of all property/casualty insurance and over 94% of all auto insurance in the country.
The GIC's service is available as a result of NICB's partnership with several public and private organisations, including Vexcel Imaging, the premier aerial imaging company worldwide; Esri, the global leader in location intelligence; and the Federal Geographic Data Committee, whose GeoPlatform is managed by the U.S. Department of Interior and provides hosting and discovery services for national geospatial data assets. Esri makes the service available to any organisation who needs it, free of charge, through its Esri Disaster Response Program.
On a regular basis, the GIC is in the process of collecting high-resolution ‘before’ benchmark imagery on the ground and in the air in some 100 markets. Through a network of aviation companies, the GIC is prepared to reach any disaster area in the U.S. within two hours and can begin imagery collection as soon as it is safe to fly and skies have cleared.Last updated: 14/11/2019