Welcome back to our first educational series, Expand Your Perceptual World with Remote Sensing! In this series we’re covering some of the remote sensing basics with a special focus on the information that remote sensing allows us to see that we otherwise would be unable to access. In the first piece of the series, we took a brief look at the history of remote sensing and how remote sensing mimics the animal world.
In this second piece of the series, we’re getting a bit more technical. Remember learning about the electromagnetic (EM) spectrum in high school physics? Me neither. We’re going to give a quick review of the EM spectrum and how it relates to remote sensing. Spoiler: it’s pretty foundational to how satellites capture images and to understanding falsecolor and index layers.
EM radiation is just a fancy name for specific types of energy that travel in waves at the speed of light. EM radiation is around us all the time in the form of radio waves, microwaves, visible light, and more.1 EM radiation is characterized by wavelength, frequency, and amount of energy. Wavelength is the length of one wave cycle and is often measured in micrometers. Frequency, typically measured in hertz (Hz), is the number of wave cycles at a specific point within a specified unit of time. One hertz would be one cycle per second.2
EM radiation exists ~on a spectrum~. If we put the shortest wavelengths on one end of the spectrum and the longest wavelengths on the other end, we have a spectrum encompassing all types of EM radiation. The image below shows how shorter wavelengths (like gamma rays and x-rays) correspond with higher frequency and higher energy. Conversely, longer wavelengths (like microwaves and radio waves) have lower frequency and lower energy.1 Visible light makes up a pretty small portion of the overall spectrum and this is where remote sensing can come in to ‘expand our perceptual world’ by showing us information about radiation outside of visible light.3
Most remote sensing relies on EM radiation from the sun. All passive sensors measure energy reflected from the earth (originally coming from the sun). Different objects or types of land cover absorb and reflect wavelengths across the EM spectrum in varying amounts. For example, healthy vegetation typically absorbs red and blue light, but reflects green light - making it appear green to our eyes! Water, on the other hand, will usually absorb more red light and reflect more blue light.4 These differences in the amount of energy sensed in different areas of the EM spectrum are essentially how we are able to identify objects and land cover in remotely sensed images. Our atmosphere also absorbs and scatters radiation, particularly in certain sections of the EM spectrum.5 Remote sensors, then, are typically designed to measure energy that can more easily travel through our atmosphere, including visible light and portions of infrared.
Remote sensors can capture EM radiation with varying levels of granularity, referred to as spectral resolution. Specific windows (or ranges of wavelengths) of the EM spectrum are measured by these sensors and each window that is measured independently is referred to as a band. So for example, black and white imagery captures all visible light together in one band, making it a relatively coarse spatial resolution. Truecolor imagery has a higher spectral resolution as it captures visible light in three bands: red, green, and blue. There are even hyperspectral sensors that can capture hundreds of bands at very fine spectral resolutions.6 Different spectral resolutions can provide us with different information about the earth’s surface. Additionally, which bands we’re looking at can provide us different insights: truecolor imagery shows us the red, green, and blue bands, but falsecolor imagery shows us different bands including infrared - this is what we’ll turn to next in the series!
Whew! Great job on making it through this quick and technical recap on the EM spectrum. This information should provide a deeper understanding of how remote sensors collect and measure information. Next up in this series we’ll take a deeper dive into falsecolor imagery followed by index layers; your newfound understanding of the EM spectrum and different wavelengths will serve as an important foundation for these topics.
If you’re wondering why the three bands of truecolor are red, green, and blue rather than red, yellow, and blue you are not alone. I may not remember high school physics, but I DO remember elementary school art class: I was taught that red, yellow, and blue are the primary colors. Mixing paints, though, works a little bit differently from mixing light. When mixing light, red, green, and blue actually are the primary colors meaning you can get any color by mixing a combination of these colors of light. Surprisingly, mixing red and green light gives us yellow! Mixing red, green, and blue light will give us white light. Our computer screens work this way by mixing red, green, and blue light; think of using RGB color codes - we can display any color by changing the amounts of red, green, and blue light that the computer is displaying.7
1 “The Electromagnetic Spectrum.” NASA, March 2013. https://imagine.gsfc.nasa.gov/science/toolbox/emspectrum1.html
2 “Electromagnetic Radiation.” Government of Canada. https://natural-resources.canada.ca/maps-tools-publications/satellite-imagery-air-photos/remote-sensing-tutorials/introduction/electromagnetic-radiation/14621
3 “The Electromagnetic Spectrum.” Government of Canada. https://natural-resources.canada.ca/maps-tools-publications/satellite-imagery-air-photos/remote-sensing-tutorials/introduction/electromagnetic-spectrum/14623
4 “Radiation - Target Interactions.” Government of Canada. https://natural-resources.canada.ca/maps-tools-publications/satellite-imagery-air-photos/remote-sensing-tutorials/introduction/radiation-target-interactions/14637
5 DiBiase, David, & Dutton, John. “Electromagnetic Spectrum.” PennState Department of Geography. https://www.e-education.psu.edu/natureofgeoinfo/node/1883
6 “Spectral Resolution.” Government of Canada. https://natural-resources.canada.ca/maps-tools-and-publications/satellite-imagery-and-air-photos/tutorial-fundamentals-remote-sensing/satellites-and-sensors/spectral-resolution/9393
7 Young, Andrew T. “Introduction to Color.” San Diego State University. https://aty.sdsu.edu/explain/optics/color/intro.html