TECHNOLOGY

Technology

With the frequency and severity of wildfires increasing at an alarming rate in California, remote sensing has become essential to developing effective and time-critical plans for wildfire prevention, protection, mitigation and response. New high resolution LiDAR and imagery data are also instrumental in the study of fuels and fuel regrowth models. 

Through the use of advanced data mapping techniques, the ALERTCalifornia program is creating a virtual dashboard to inform fuel reduction efforts year-round and more efficient firefighting during peak fire season to save lives as well as protect habitats and infrastructure.

Monitoring From the Ground

Fire Cameras
ALERTCalifornia’s high-definition cameras are able to pan, tilt, zoom and perform 360-degree sweeps approximately every two minutes with 12 high-definition frames per sweep. The cameras also provide 24-hour monitoring with near-infrared night vision capabilities. Each can view as far as 60 miles on a clear day, and 120 miles on a clear night. Using the cameras and associated tools, first responders with the California Department of Forestry and Fire Protection (CAL FIRE) can rapidly confirm fire ignition, quickly scale fire resources, support evacuations through enhanced situational awareness and monitor fires through containment.

Infrared FLIR Camera Technology 
This advanced camera technology allows firefighters to see fire through smoke, enabling better real-time resource allocation and enhancing firefighter safety. FLIR stands for “Forward Looking Infrared,” and refers to the thermal imaging technology used to create an infrared image of a scene without having to “scan” the scene with a moving sensor, an advancement over older models. FLIR technology is typically used on military and civilian aircraft, and is now being incorporated into ALERTCalifornia’s network.

Artificial Intelligence (AI)
ALERTCalifornia collaborated with the California Department of Forestry and Fire Protection (CAL FIRE) and industry partner Digital Path to create a fire detection AI tool with the goal of improving firefighting capabilities and response times. The value of this public-private partnership is the development of AI to aid firefighters, mitigate watchstander fatigue, reduce false positives, and confirm fire incidents in the incipient phase.

When the AI spots a potential fire on ALERTCalifornia’s network of cameras, the system alerts firefighters and provides a percentage of certainty and estimated location for the incident. If the incident is vetted and confirmed by trained watchstanders, firefighters respond quickly to extinguish the fire at the incipient phase. The camera network is also used to provide actionable real-time data to quickly scale fire resources, help evacuations through enhanced situational awareness, and monitor fire behavior.

Early detection and rapid response allow firefighters to combat fires before they grow. The AI tool became available to all 21 CAL FIRE 911 Dispatch Centers in September 2023. This new tool is especially effective in spotting anomalies in remote locations and is proven effective at night, even alerting firefighters before 911 calls.

Sensing from The Air

Aviation Technology
ALERTCalifornia is working with the CAL FIRE Aviation Program to incorporate the newest technology for scanning terrain. These new fuselage ports and surveillance pods have been approved by the Federal Aviation Administration (FAA) and the European Union Aviation Safety Agency (EASA), and can be used for mapping, LiDAR sensors, drop-hatch and other missions.

LiDAR

LiDAR, which stands for “Light Detection and Ranging,” is a type of data collection that uses light in the form of a pulsed laser to measure distances to the Earth. Airplanes and drones equipped with scanners flying precise transects generate equally precise, three-dimensional information about scanned surfaces. LiDAR remote sensing allows ALERTCalifornia to examine fire-prone environments (both natural and manmade) with greater accuracy. ALERTCalifornia combines LiDAR scans with other data to create a more complete view of California’s habitats to understand the causes of wildfires, active fire behavior and post-fire impacts such as landslides.

Biomass and Carbon Estimation 
ALERTCalifornia combines LiDAR scans with the physical characteristics of different tree species, to gain a better understanding of California’s forest biomass and carbon content. In tandem with ground plot measurements, ALERTCalifornia researchers are developing regression models to estimate forest production parameters, including but not limited to tree diameter at breast hight, tree height, and total leaf area, of large forested areas. These forest parameter data improve our understanding of the relationship between remotely sensed observations and important biological and physical parameters in forests.

Wildfire Modeling 
Forest metrics from LiDAR scans and imagery provide valuable information for land use and management practices, fire suppression planning and wildfire fuel calculations. High-resolution LiDAR is instrumental in mapping a landscape’s terrain and accessibility. Measurements include the steepness and angles of slopes, as well as the directional—north to south and east to west—orientations of landscape features. These precise measurements directly inform wildfire response and recovery.

Change Direction and Landslide Analysis
With the aid of recurring surveys and temporal comparisons, ALERTCalifornia analyses can quantify changes in vegetation growth/removal or in geomorphology to better monitor forest dynamics, and to evaluate and mitigate forest management risks associated with erosion and more catastrophic events like landslides.

Forest Metrics

There are hundreds of possible metrics to be studied when diving into California’s forests. By toggling out specific metrics, the ALERTCalifornia team is working to characterize and quantify potential wildfire fuel loads based on different forest measurements. These measurements,  taken in the field, record data related to forest canopy base height, canopy bulk density, fuels on the forest floor and many other forest characteristics. These field data become key inputs for fire simulation modeling and help improve models over time.

Terrain Modeling

Using new advanced scanning technologies, ALERTCalifornia’s teams scan forests and “see” beyond what is visible to the human eye. Multispectral imaging captures image data within specific wavelengths, even from frequencies beyond the visible light range. Once these data are processed, ALERTCalifornia scientists characterize the different vegetation types in diverse habitats. These scans are highly accurate and, when combined with other data, enable the team to identify specific types of trees and other vegetation. Researchers can also use these multispectral data to understand the impacts of fire and climate change to habitats over time. For example, the team is scanning rivers to estimate their depth and the temperatures of flowing or standing water, and assessing the health of forests over time to determine fire risk.

ALERTCalifornia is a
UC San Diego Program

Live Camera Feeds

Neal Driscoll

Principal Investigator

Dr. Neal Driscoll is the principal investigator of the ALERTCalifornia program at the University of California San Diego, where he is a professor of geology and geophysics at Scripps Institution of Oceanography.

Driscoll’s background in natural hazard research traces back more than 35 years. He has published more than 120 manuscripts in high impact peer-reviewed journals, including Science, Nature Geoscience, Geology, and the Journal of Geophysical Research on subjects ranging from earthquake hazards to devastating wildfires., He has received multiple awards during his career, including the Heezen and Storke Awards for excellence in research and UC San Diego’s inaugural Undergraduate Teaching Award. Driscoll has also appeared in articles published by The Associated Press, The New York Times, CBS News, The Los Angeles Times, KGTV, KPBS and other notable news outlets.

Driscoll received his Ph.D. in geology and geophysics from Columbia University and worked as an associate research scientist at the Woods Hole Oceanographic Institution in Falmouth, MA before joining UC San Diego in 2000. His research interests at Scripps Oceanography include landscape and seascape evolution in response to tectonic deformation, sea-level fluctuations, climate, neotectonics, and geohazards.