California police adopt WingtraOne drone for wildfire damage assessment

LAFAYETTE, California – The Lafayette City Police Department and an interagency task force joined a survey firm to deal with extensive damage caused by California wildfires that were raging in August and September. One of these, “the CZU lightning complex fire” caused a massive evacuation before destroying 86,509 acres (35,009 ha) and nearly 1500 structures across four communities and two state parks. To assess the worst-hit areas of this particular fire, a WingtraOne drone was used to collect aerial data used to generate  2D and 3D maps of the area.

“The mapping not only helps search and rescue and damage assessment, but it also helps us see immediately what’s destroyed and what hazards need to be taken care of before we let people back into the area,” said John Cornell, assistant to the chief of police at the City of Lafayette Police Department.

The Lafayette Police Department worked as part of an interagency task force and in partnership with GeoAcuity, a geospatial consulting firm, to produce a public-facing portal for stakeholders. The aerial maps provide a form of support for victims of the fire—offering them the information they need, the data their insurance companies need, and, in some cases, the proof they need to raise funds.

“I’ve seen like half a dozen GoFundMe website fundraisers that have our maps associated with them,” said Dr. Greg Crutsinger, Director of Applied Research at GeoAcuity. “The WingtraOne drone data is important to a range of people, from the public agencies involved to the residents who are desperate for information.”

Through massive forests and undulating terrain, they covered more than 1500 acres (600 ha) in one day and four flights.

“Redwoods are some of the biggest trees in the world, and there aren’t a whole lot of areas to launch from in a disaster area like this,” Cornell said. “You can’t just go onto somebody’s property and launch on top of their burned-out house. There are also a lot of crews working. So we needed to be as safe as possible and be able to predict precisely where the drone would land.”

 

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