FAIRBANKS — You may have seen a simple Alaska fire map making the rounds on Facebook and the Internet lately. This is a Google map I made of all the fires in Alaska, color-coded by the size of the fire. When you mouse over them, you get information about each fire — its name, when it was discovered and how many acres it covers. The map updates every hour from the latest available data.
As a former software engineer, I know that information needs to be user-friendly if you want people to use your product. As a University of Alaska Fairbanks Ph.D. candidate who studies active fires in Alaska through satellite imaging, I also know the importance of getting real-time information to people. I am working towards my doctorate in geophysics at the Geosciences Department and the Geophysical Institute.
The active fires map is based on the master fire map the Alaska Interagency Coordination Center uses and maintains. I used my background in computer programming to feed the AICC’s information into a user-friendly map in Google. Yet you may wonder, where does all the information on the map come from and how does it get made into a fire map in the first place?
The task: Mapping fires
During an active fire season, everyone wants precise and up-to-date fire maps as fast as possible: to manage the fires, monitor air quality and inform those who live in the affected areas (right now, that’s nearly all of us). The fire services can fly the perimeters using GPS, but for a map of the whole state, satellites are ideal tools. The information they provide is used in the maps AICC publishes as well as the maps I create in my research. But it takes a number of steps to get from a satellite to a map that’s usable by an agency or the public.
Step 1: Start with a satellite that has the right altitude … and attitude
You have probably heard about geo-stationary satellites, which are critical for tracking large weather systems and producing the animations you see on TV. These satellites stay put over the same spot on the Earth’s surface and provide images of a whole hemisphere. But they orbit very high above the Earth — about 22,200 miles. That is 10 percent of the distance to the moon! So the signal is too blurry and faint for mapping a wildfire.
The information I use to make fire maps comes from satellites designed to observe the earth at about 440-560 miles above the Earth. There are several such Earth-observing satellites that travel in slightly different inclined orbits around the Earth, with all their orbits intersecting daily around the North and South Poles. Because of that, ground stations that receive the satellite data via radio are often placed in northern regions. There are several such facilities around Fairbanks, with two at UAF: the Geographic Information Network of Alaska (GINA) and the Alaska Satellite Facility. Think of these when you see big satellite dishes around town.
Step 2: Use the right instrument
Space agencies from the U.S. and other countries operate a number of Earth-observing satellites. They carry many different kinds of equipment that complement each other: RADAR, LIDAR, trace gas sensors, gravity sensors and many more.
Some of the most versatile sensors are a cross between a digital camera and an infrared thermometer. Examples are the sensor MODIS on NASA’s Terra and Aqua satellites and the VIIRS sensor on the newer NPP/Suomi spacecraft from the National Oceanic and Atmospheric Administration. Like a camera, the MODIS and VIIRS sensors can capture light in the visible spectrum (what we see), and a little bit beyond it. Like a thermal camera, these sensors also detect heat on the surface, which is especially helpful in locating and mapping wildfires.
Step 3: It’s all about the pixels
Because the sensors are so far away and there’s an atmosphere in between them and the Earth, the images from those sensors need to be interpreted. The sensors collect and average information, such as temperature, over a certain area of Earth that becomes one pixel element that makes up a picture (like the pixels on your computer screen). Most fire hotspot maps you see use “fire pixels” that represent 5/8 mile (1 km) in size — or larger. But the new-generation VIIRS sensor has a much better resolution, down to about ¼ mile (375 m), and that means we can even trace the front where the fire is moving through the forest.
But there is still more detailed data about the fire’s structure hidden within the pixel. Using image processing, I open the pixels up and try to get information that will help me understand the nature and size of the fire within that ¼ or 5/8 mile. And even though NOAA and NASA provide pre-packaged products that can be used for global fire mapping, by looking in detail at Alaska fire pixels, we can extract more information that is relevant in our region.
Step 4: You must choose — fast, cheap or high quality
As a former software engineer, I know the saying: “You can’t have fast, cheap and high-quality at the same time — you must pick two.” With Earth-observing satellites, it’s similar: You can take wide, less-detailed images several times per day; or you can focus your optics tightly to get a more detailed image, but only get a new image every few weeks — and it might be on a cloudy day. For daily fire mapping, MODIS and VIIRS give me several images per day, but at a cost of low resolution, which means a bigger pixel area.
Step 5: The data goes the distance (to me)
The data arrives at the satellite facilities a few hours after the satellite passes overhead. The main challenge of the data is managing it. A single sensor generates a slew of data files and geolocation data with the latitudes and longitudes for each pixel. From GINA (at UAF) alone, I get about 5 gigabytes and maybe 200 files six to eight times per day. Good thing it’s a local transfer! All this data has to be catalogued, sifted and selected for the image slices that are actually located over Interior Alaska instead of the Bering Sea, Russia, the Arctic Ocean or Canada. I’m also using a data portal from NASA over the Internet.
A lot of the time that goes into building fire maps is spent shuffling all that data around. But it’s worth the effort, because we get better maps than anyone else can provide us with.
Christine Waigl is a Ph.D. student in geophysics at the UAF College of Natural Science and Mathematics’ Geosciences Department and conducts research at the Geophysical Institute.