The occurrence of fires across the globe has steadily increased over the last 20 years.
From 2001 to 2023, the area burned by forest fires has increased by about 5.4% annually, with record-setting fires becoming more and more prevalent as time goes on.
In the United States in 2022, this ramping up of fires resulted in 3,790 deaths and an estimated loss of about $18.1 billion in damages.
As these fires become more common, traditional methods of fire monitoring and detection have become more difficult to maintain.
Firewatch towers are often undermanned and only provide detection in a limited capacity.
Aerial observation is limited by flight paths and fuel constraints.
With the numbers of fires increasing, the physical detection and monitoring of fires has evolved into a monumental task.
Fire response planners and first responders have looked to Geographic Intelligence Systems (GIS) to address these gaps.
A GIS is a technology that is used to create, manage, analyze, and map all types of data.
With GIS, disaster response organizations can process data collected to create maps, products, and resources that inform and enable the public.
Multiple organizations have developed GIS resources for government and public use to include NASA, ESRI, and FEMA.
Remote sensing is a key source of data for the effective use of GIS in fire planning.
Remote sensing is the process of detecting and monitoring the physical characteristics of an area by measuring its reflected and emitted radiation at a distance.
In fire response, this typically revolves around the measurements of fires collected by satellite systems.
By utilizing GIS with remote sensing data collected via satellite, persistent coverage of fire areas has become feasible on a global scale.
So how do satellites detect fires from orbit? A fire has three properties that affect a sensor’s ability to detect it: size, temperature, and radiative power.
Based on the size and temperature of a fire, it will emit radiative energy in the form of heat that can be picked up by powerful sensors on board a satellite system.
This radiative energy creates a spectral signature across a set of wavelengths and frequencies that is different from its surroundings.
A satellite collects data across multiple ranges or bands of wavelengths allowing for the detection of these differences and the identification of a fire.
Fires primarily emit radiative energy within the infrared bands, so if a remote sensor can collect data within this range, there is a good chance it will be able to detect a fire as it orbits the planet.
This data is often combined and manipulated with data collected in the visible light bands to create imagery and products that responders and the public can easily use and understand.
Satellites can classify the type of data collected by its timeliness.
More powerful satellites with higher spatial resolution such as LANDSAT9 and Sentinel-2 collect fire data in standard format, which requires extensive processing and will often take hours or days to create effective imagery.
This will typically be used for research purposes or long-term analysis.
With regards to immediate fire response, real-time or near real-time (NRT) data is the preferred format.
This type of data is often collected at a lower spatial resolution, but has the benefit of requiring minimal processing to enable understanding of current situations as they arise.
NASA’s MODIS and VIIRS remote sensors currently provide publicly available near-real-time data tracking fires.
The Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) work hand in hand to provide NRT fire-tracking data across the United States.
Both operate in a similar manner at different spatial resolutions, with MODIS at a resolution of 1 kilometer and VIIRS at a resolution of 375 meters.5 First, the sensor will identify a hotspot with increased radiative energy signal in a square area matching its spatial resolution.
This will generate a fire pixel data point, which can then be mapped based on the pixel’s coordinate.
If there are multiple fires within the resolution space, it will only generate one fire pixel but the intensity of the emitted signal will likely increase as well.
For example, if MODIS identifies multiple hotspots in a 1-kilometer square area it will only generate one fire pixel at that coordinate but that one pixel will likely have a higher value for emissive radiation.
By overlaying these fire pixels on a map, disaster response planners and first responders can track a fire’s location and areas of intensity from start to finish.
This in turn enables better situational awareness for responders on the ground and allows for the development of more effective strategies to combat larger fires.
GIS resources use the data collected by these sensors to create better products for responders and the public.
Multiple agencies, both government and commercial, have created free software that provides a variety of information regarding current fires and at-risk areas.
Esri, an American GIS software company, created their Wildlife Aware application to display current fires across the globe and provide assessments of containment effectiveness.
The Federal Emergency Management Agency (FEMA), has multiple GIS products to include real-time tracking using their Wildfire Hazard Overview Dashboard and preventative resources using their National Risk Index Map.
Raw data is also directly available for public access through NASA’s Fire Information for Resource Management System (FIRMS).
MODIS and VIIRS data can be downloaded as NRT, 24-hour, 48-hour, and 7-day packages to create new GIS resources if a previously developed product doesn’t fit current requirements.
As GIS continues development, new techniques can be applied to enhance timeliness of analysis such as machine learning and automation through artificial intelligence.
Extended collection periods of data feed into these automation processes and increase their ability to predict and detect fires over time.
GIS is a major asset to fire response planning and allows for enhanced capabilities previously unattainable through traditional means.
It is a force multiplier, and allows responders to develop situational awareness in a disaster area faster and more comprehensively than ever before.
As the technology evolves, disaster response decisionmakers continue to recognize the importance of GIS applications and push for its adoption by local agencies.
Blumenfeld, J. (2024). Wildfires Can’t Hide from Earth Observing Satellites. Earthdata. https://www.earthdata.nasa.gov/learn/articles/wildfire-articles/wildfires-cant-hide-from-earth-observing-satellites
MacCarthy, J. (n.d.). The latest data confirms: forest fires are getting worse. World Resources Institute. https://www.wri.org/insights/global-trends-forest-fires
Statistics. (n.d.). U.S. Fire Administration. https://www.usfa.fema.gov/statistics/
What is GIS? | Geographic Information System Mapping Technology. (n.d.). Esri. https://www.esri.com/en-us/what-is-gis/overview?srsltid=AfmBOooP3FoLn1JFI4J6LUo9kWwxtvG53QiILgizGTjvTP_kLfgREoHM
What is remote sensing and what is it used for? (2018). U.S. Geological Survey. https://www.usgs.gov/faqs/what-remote-sensing-and-what-it-used
Wong, M. (2024). VIIRS I-Band 375 m Active Fire Data. Earthdata. https://www.earthdata.nasa.gov/learn/find-data/near-real-time/firms/viirs-i-band-375-m-active-fire-data
