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Wildfire Detection Technologies

2022 has been a challenging year so far. The world is still trying to recover from a pandemic turmoil, tackling inflation caused by energy and food supply-chain problems, all while fighting a global climate crisis.

Climate change is causing wildfires to become more frequent and intense. Failing to suppress fires before they get out of control makes the task of containing wildfires a more challenging and lengthy process. Today, the key to mitigate wildfire risks and damages is to detect fires shortly after their ignition and to take action as soon as possible to control their spread before there is widespread damage . Terrestrial, aerial, satellite remote sensing systems along with IoT based solutions are the commonly used technologies by different agencies and industries to monitor and detect wildfire events.

Figure 1: diagram showing common wildfire detection technologies

Terrestrial camera systems (visual and infrared sensors)

Terrestrial camera systems have been adopted in many regions to actively survey the landscape for new fires. They are equipped with near-infrared and/or thermal sensors which allow them to acquire information about objects seen from a far distance. Optical cameras offer both monochrome and color information through images. Visual sensors can provide color information by capturing red, blue, and green light. The presence of smoke or fire is then easily observable during daylight hours.

Using visual sensors alone is not enough to find fires in challenging light environments or during the nighttime, smoke may go unnoticed because the visibility of colors diminishes. This interferes with color detection and would fail to alert first responders of new fire ignitions. The benefit of installing infrared sensors in these

camera systems is the gaining the ability to acquire thermal information on radiated heat from objects that are within view. Combining infrared sensors with visual ones reduces the false alarm rates for fire detection and results in increasing the robustness of camera systems for wildfire detection. Cameras as a solution for early wildfire detection are the most mature and adopted technology.  Optical zoom functions are also available and provide fire managers to gain additional situational information. Visual camera systems are able to detect wildfires up to 60 km in good weather conditions. The optimal distance to detect small, early-stage wildfires is 15 km. With line-of-sight and LWIR (Long-wave infrared), thermal cameras detect 2 m2 fires at a distance of 5 km as well as burning surfaces of 9 m2 at a distance of 8 km.

Companies that have developed and deployed camera-based wildfire detection systems include Robotics Cats, EnviroVision Solutions, IQ Firewatch, and Pano AI. There is a new category of software-only solutions supporting installed camera networks such as AlertWildfire and HPWREN, which provide real-time video  to first aid responders and other members of the public.


Although most satellites were designed primarily for purposes other than detecting fires, satellite ability to cover large regions does make them most useful for large-scale monitoring and for possible fire detection in remote areas. They have been employed for fire management to detect active burning fires and hotspots, and to track the movement of smoke. Geostationary satellites, located at an altitude of 35,785 km, are fixed above Earth’s equator. Moving with a speed equal to Earth’s, these satellites provide a constant view of the same, large area. Every 15 minutes, they are continuously producing coarse, low resolution imagery of fire, smoke, and clouds. By contrast, polar orbiting satellites, namely NASA’s Terra and Aqua, are able to produce very detailed images of energy radiation along with smoke and aerosol properties, all of which belong to fire phenomenon.

Aboard geostationary and polar orbiting satellites might be any of these 3 types of sensors: VIIRS, MODIS, and AVHRR. All of which provide image data on smoke, hotspots, and fire. The VIIRS sensor is used widely for wildfire detection as it captures data from both visible and infrared light (Barmpoutis et al., 2020). This sensor can also map out fire perimeters and produces imagery with resolutions of 375 m and 750 m per pixel. Imagery with a resolution of 375 m is more detailed than those produced at 750 m. Such differences in spatial resolution affect the extent of fire spread that is shown in the produced imagery. Terra and Aqua satellites equip MODIS sensors which will cover the entire globe every 1-2 days. They collect even more atmospheric data than VIIRS, including detection of a larger range of infrared light. Visible imagery is helpful to point out any clear smoke and hotspots in broad daylight, but it isn’t effective during the night time or in weather conditions when visibility is low. This creates challenges as smoke data may be similar to those of other phenomena, namely clouds and haze. MODIS is equipped with thermal detectors which look for abnormal temperatures on Earth’s surface. For hotspots and other heat sources, exact locations are estimated, but never definitive. AVHRR sensors—supported by NOAA’s polar-orbiting satellite instruments—produce images with resolutions of 1km. Similar to a resolution of 700 m, a spatial resolution of this size does not provide enough detail to point out fires in their early stages of ignition.

Within 3 hours of hot spot and fire event observations, first responders and land managers are alerted of active fires, but there are times when imagery doesn’t become available until 4-5 hours after detection. Although many of these satellite models were used to predict fire outbreaks and to track them, many satellites with long recapture times are becoming less applicable to new unprecedented fires that are igniting more frequently and are growing at faster rates.

As satellites continue to evolve and improve their capabilities, their dimensions are shrinking, easing their deployment and reducing the cost of launch. They are becoming more suitable for widespread wildfire detection and are monitoring Earth’s surface at sharper resolutions. Developments are being made to improve their latency as well. Companies deploying satellite instruments for wildfire and bushfire mitigation purposes are Ororatech and Exci.


Another product being adopted to aid fire management efforts are unmanned automated vehicles (UAV). They have been used as an alternative for crewed aircrafts to overcome challenges for observing and suppressing fires in low visibility. Similar to terrestrial cameras systems, drones may be equipped with infrared and optical sensors to map out active fires and hotspots that may be hidden by smoke.

There are two types of drones, rotary winged and fixed winged, both may be deployed with ease. Rotors spinning at high speeds allow for the automated vehicle to hover in place for hours at a time, some for 3 hours while some can hover for over 8. Rotary wing drones have lower endurance so they are able to observe and make inspections of the landscape for a shorter period of time than fixed wing drones which may have a flight time of up to 16 hours. While fixed wing drones are designed to travel distances at higher speeds and to have long flight times, rotary wing drones are more common because of their maneuverability, but for some, their flight time is limited as it only goes up to 30 minutes. A disadvantage is that some rotary winged drones have a small payload which may make them unsuitable for supporting hefty thermal and visual cameras or other sensors. Due to their maneuvering capabilities and swift change of direction, drones are able to cover large areas of the landscapes.

Observing fire events in remote and inaccessible areas have been made possible with the deployment of UAVs. They are able to fly up and down the terrain, making observations in areas with steep slopes, but navigating terrains with high variations in altitude or those that are covered by dense vegetation may be difficult to observe (Hristov et al., 2019). Aside from utilizing drones to closely inspect areas and to detect hotspots or firebreaks, they are frequently used in efforts to battle fires by slowing down their spread with fire-dropping methods.

Companies such as Northrop Grumman and Robotto are developing drone-based wildfire detection systems.


The internet of things (IoT) has made it possible for data to be collected, processed, and communicated in near-real time through networked devices and softwares. IoT devices are being utilized to monitor and protect biological and social ecosystems. Sensors that are being deployed detect environmental conditions like temperature, air pressure, moisture levels, and parameters including radiation, smoke, CO2, and other particulate matter. Weather characteristics of an area is critical information as it triggers the ignition of a fire and influences its growth and spread, while the detection of heat, smoke, and abnormal CO2 detection may indicate the start of a potential fire. IoT-based systems can send alerts to front-line users such as fire managers. Owing to the often low-cost and small nature of the devices, many sensors may be installed to cover large areas in both accessible and inaccessible places. To withstand high temperatures and harsh weather conditions, sensors are built with both weather and heat protective material. Heavy metals are used to increase the resistance and durability of these sensor devices. The only disadvantage is weathering may lead to these metals may find their way into our water supply and other parts of the environment.

To achieve productive monitoring in a forest area, it could take up to 10,000 sensors to reach adequate coverage. Installing clusters of sensors increases accuracy and reliability in the data and network communications. It is also possible to track patterns in the data such as the movements and spread of smoke or heat anomalies. Many IoT sensors may either be powered by batteries or solar energy. Certain battery power IoT sensors may slow down after a few years, ultimately making the IoT sensors ineffective. Once deployed, sensors with dead or defective batteries situated in remote areas may be difficult to reach.

Some IoT based systems are making it possible for hotspots to be detected by a cluster of sensor nodes that then trigger the flight of a drone to observe and gather more data in the area. Through connected networks, information that is collected by sensors, drones, and other detection systems is then processed and transmitted to the internet or to a data center. The network communicates detections to authorities as well as others who are connected to the network who can then take actions and make fire managing decisions.

EUREKA, and Dryad are IoT based systems that are being used to alert various communities of any detected wildfires.

Table 1. Product comparisons

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