Building Rural Wildfire Resilience through GIS mapping and UAV Verification of High-Risk-Lightning Strikes

PROJECT SUMMARYTitle:Building Rural Wildfire Resilience through GIS mapping and UAV Verification of High-Risk- Lightning StrikesPI: Dr. Istvan KereszyLightning ignitions are responsible for over 70% of the area burned in the American Westtotaling 5.5 million acres of land burned annually. These major wildfires significantly impactvulnerable communities causing between $120 to $190bn of economic damages each year.However less than 10% of all lightning strikes contain Long-Continuing-Current (LCC) neededto start a wildfire; these are called High-Risk-Lightningâ„¢ (HRLâ„¢). Currently it can take 24hours or more to find lightning-ignited wildfires by which time they are often burning out ofcontrol. Quick and reliable detection and verification of such wildfires are especially critical forthe safety and security of vulnerable remote and rural communities where firefighting resourcesare limited and socioeconomics are fragile.Fire Neural Networkâ„¢ (FNNâ„¢) has developed proprietary technology that can identify thesmall number of lightning strikes likely to cause a wildfire. The next important step is to quicklyand accurately verify these likely lightning-ignition spots. In this USDA SBIR project FNNâ„¢will develop a method to protect vulnerable rural communities from lightning-initiated wildfiresby creating a functional operating model for (a) pinpointing and monitoring a wildfire byverifying the High-Risk-Lightningâ„¢ strikes via Unmanned Aerial Vehicles (UAVs) (b)integrating the live fire data into a GIS layer used by emergency management authorities andCommunity Wildfire Protection Plans (CWPPs). This will strengthen rural community resilienceby reducing fire verification times from 24 hours to 20 minutes and it will empower communityleaders with situational awareness on lightning-initiated wildfires along with the assessedvulnerabilities within the local community.