SMoLDER: Situational awareness, ModeLing, and Decision support Engine for wildfire Response

PROJECT SUMMARY Title: SMoLDER: Situational awareness ModeLing and Decision support Engine for wildfire Response PD: Koplik Gary J. Institution: Geometric Data Analytics Inc. In 2020 58950 wildfires burned 10.1 million acres one of the highest acreage impacts in recorded history. Wildland firefighters particularly those in remote environments often rely on basic tools such as paper maps compasses and two-way radios providing limited communication and situational awareness. In addition the value of wildfire modeling efforts to responders is still inhibited by runtime and lagging input data. Geometric Data Analytics proposes the development of a situational awareness data augmentation of wildfire modeling and intervention decision support tool coupled with real-time data collection to support wildfire management. Leveraging national wildfire data and satellite-communication enabled devices collecting data on-site we will employ these data and communication systems to improve current situational awareness data-driven near-term wind models and intervention scenario models for managing wildfires. The anticipated result of the proposed effort is a proof-of-concept version of SMoLDER: Situational awareness ModeLing and Decision support Engine for wildfire Response (Figure 1). SMoLDER will both enable advancement of modeling efforts in the research community and help firefighting crews manage wildfires more effectively saving lives reducing resources spent on control and significantly reducing loss of property and natural resources. Near-term potential commercial applications include a situational awareness and decision support platform for wildfire responders as well as the wildfire monitoring and modeling community. Once efforts in wildfire applications are underway we anticipate exploring similar applications for other emergency response to severe weather events the military and environmental monitoring.