Evaluating the Need for Automated Wildfire Detection Systems


It is nearly impossible for preventative measures to eliminate the occurrence of wildfires. Despite the efforts of fire prevention campaigns, wildfires are increasing in duration, intensity and frequency worldwide. Although humans carry their share of blame for the majority of wildfires each year, other natural causes still pose threats to the people and landscape of a given area. Given the difficulty to consistently prevent wildfires, early detection is paramount to controlling damage and minimizing the overall cost.

Automated wildfire detection technology has evolved into an efficient tool to identify the first sign of a wildfire (smoke) and alert personnel so that they can swiftly suppress the fire and mitigate the damage. This technology is useful in a variety of settings where the lack of early fire detection has the potential to cause injury, death or widespread financial losses.

Why the Need for Automated Detection?

Wildfire can be defined as the uncontrolled burning of grass, bushes or forests. They are prevalent in areas around the world, but are most damaging where valuable assets and human presence comes in contact with these undeveloped areas.  The National Interagency Fire Center (NIFC) reports a disturbing increase in wildfires over the past three years with an average number of U.S. wildfires at 87,004 and destroying over 8 million acres.  This average number of fires is an increase of 13% over the average of previous "worst years" and an 8% increase of acres destroyed.

Additionally, although humans often directly cause wildfires, the most destructive fires of 2012 were caused by lightning and are entirely unpreventable.  For example, a 2009 study conducted by the California Department of Forestry and Fire Prevention revealed that half of the 20 largest wildfires in California were either caused by lighting or power line damage, both unpreventable.  The NIFC reports that in 2012 in the United States, lightning was responsible for 9,443 fires, damaging 6,825,989 acres.  In the same year humans were responsible for 58,331 fires, but damaged far less acreage (2,500,249).  But wildfire destruction is not limited to burned land; wildfires can cause secondary disasters including landslides, mudslides, flashfloods and smoke haze that threaten aircraft visibility and engine safety.  They also often threaten urban areas that have encroached on many natural settings. 

Wildfires can double in size every five minutes in dry and windy conditions, necessitating early detection to minimize damage.  The increasing number of fires, the widespread potential for damage and the inability to prevent a significant portion of the problem requires that government and private entities at risk allocate resources not only to fire prevention, but also focus heavily on fire response systems.  Automated wildfire detection technology arose from the attempt to control the devastating losses from these increasingly inevitable disasters.

  The Benefits of Automated Wildfire Detection

Government and private entities seek automated wildfire detection systems to replace direct human observation that they suspect to be unreliable or inefficient in fire detection programs.  A pilot program from Deutsche Luft-und Raumfahrt (DLR), the German Aerospace Agency, conducted from 1995 through 2003 revealed that automated optical detection decreased wildfire acreage destruction by over 90% compared to that of manned lookouts . The study found that early detection minimizes damage, and automated technologies, especially those utilizing lower cost visual spectrum range cameras, can greatly assist in fire identification.  Studies like these suggested an automated system can be more effective than past detection approaches for a variety of reasons:

Nighttime Detection- Many wildfires occur at night, which complicates their detection and the emergency response by human observers.  Smoke is more difficult to spot at night.  Additionally, night fires are potentially more destructive than daytime fires because many firefighting agencies rely on civilians to report smoke sightings and many are sleeping and unaware of these pending disasters.  Darkness can also delay emergency dispatch, which can allow fires to spread and increase their impact.  
Distance- Video cameras can spot fires at farther distances than conventional fire detectors (i.e. temperature or particulate -based sensors).  Traditional point smoke and fire detectors only detect particles in the air generated by smoke and fire, limiting their detection ranges.  Video monitoring can detect smoke from a 1 meter square fire at a range of 10 km in less than 30 seconds.
Peripheral Spotting Features- These systems can sometimes be used for other, related purposes than wildfire detection. For example if infrared cameras are deployed, the same camera infrastructure employing different software can be used to detect vapor from leaks in gas, oil or chemical pipelines that may be routed through remote areas. Other software can be used for automated recognition of intruders or lost/missing persons.
Cost- A lot of money is spent each year on responding to the damage caused by fire.  But an investment in automated fire detection systems can save companies time, money and resources.  The daily cost to monitor a square mile is estimated as low as .05, including deployment, hardware, software, power and personnel.  Detection software can be integrated into existing security cameras, eliminating the need for purchasing expensive, new equipment.  Finally, automated systems lower the technical levels of operators, only requiring them to confirm a system alarm and deploy the appropriate response teams.

Evaluating the Need for Automated Wildfire Detection

Appropriate fire prevention planning should begin with a risk assessment.  Fire potential mapping allows managers to assess which areas are at risk for fire or widespread destruction and prioritize deployment resources in an effort to minimize damage.  Fire potential is measured by the amount of dead and live vegetation and the amount of moisture in each.  High-resolution sensors can create a high-quality land cover map that estimates the amount of dead and live vegetation.  Then low-spatial and high-temporal resolution satellites monitor changes in the vegetation, which is compared with the moisture of the live vegetation.  Knowledge of local weather conditions dictates the amount of moisture in dead vegetation.  Knowing an area's fire potential will help determine the regions needing to be monitored with an automated wildfire detection system.  Entities will then need to determine whether the cost of monitoring each square mile with an automated detection system matches the fire potential and accuracy of the system.  As noted above, with some companies claiming automated detection can cost as low as .05 per square mile, many high-risk areas are investigating how integrating this technology can help reduce their losses.

In some cases, the damage caused by fire is too great to risk, thus any determined fire potential will make an automated system fiscally appropriate.  Automated systems are often used in places where the lack of quickly identifying a wildfire can cause serious injury or death. The accuracy and convenience of these systems makes them desirable, and companies that use existing surveillance cameras for optical detection can offer this technology at reduced costs, which makes automated detection more accessible for a number of areas around the world.

Who Can Benefit from an Automated Wildfire Detection System? 

Automated wildfire detection can be used in natural parks or grasslands, forests, logging sites, electric transmission lines, pipelines, research and observation facilities, places where homes or buildings are surrounded by grass or forested lands or anywhere where public safety perception is important. 

The widespread building and land destruction from wildfires has an emotional and financial impact.  Automated wildfire detection systems identify fires and dangerous fugitive emissions faster than humans can, saving government and private entities time, money and the need for additional personnel responsibilities.  Businesses considering acquiring this technology should find a company that can estimate the surveillance cost per square mile of coverage and certify their accuracy with measures taken to minimize or prevent nuisance alarms. Surveillance integration options now exist that offer cost-effective automated detection, creating the potential for more land protected and more lives saved.