If you've ever used a camera then you know something about spectral remote sensing. Spectral related to the electromagnetic spectrum, which includes light that is both visible and invisible to human eyes, and remote sensing which involves measuring the properties of objects without directly touching them. The typical camera that you use measures and records visible light that objects like trees and rock reflect. This light might come from the sun, but it also might come from other sources, like light bulbs. While we often use cameras to take selfies and silly pictures of our furry friends, scientists use high-powered cameras called imaging spectrometers to measure changes in things that impact our environment, like water quality or vegetation cover in health. Image-expectrometers mounted on airplanes and satellites help us create maps, like this vegetation cover map for the entire United States. But how exactly do scientists measure changes to our environment using reflected light energy? To answer this question, let's have a look at the electromagnetic spectrum, which is composed of thousands of wavelengths of energy. Visible light, what we see with our eyes, is contained in the blue, green, and red portions of the spectrum. The rest of the spectrum is not visible to human eyes, but can be detected and recorded by sophisticated camera-like sensors called imaging spectrometers. Now, there are thousands of wavelengths to record in the electromagnetic spectrum. To deal with all these wavelengths, imaging spectrometers divide the spectrum into groups of wavelengths called bands. For example, a band in the near infrared region of the spectrum could include energy from 800 to 850 nanometers. This band is useful to map healthy vegetation. The width and number of bands is what we call the spectral resolution of an image. Higher spectral resolution means more bands that are spectrally more narrow. Lower spectral resolution means fewer bands, each of which covers more of the spectrum. Now, imaging spectrometers measure reflected light energy. You see, different objects reflect, absorb, and transmit light differently, depending on their chemical and structural characteristics. For example, plant leaves are green because they reflect more green light than blue or red light. On the other hand, fighter the dog reflects more light in the red portion of the spectrum because of the chemical and structural makeup of his fur. If fighter's chemical and structural makeup was the same as a plant, then he would look green. Now, when you point your camera towards your favorite canine doing something silly, the camera records the amount of light reflected from the dog in its surroundings, in the visible or red, green, and blue bands of the electromagnetic spectrum. The camera creates what's called an RGB image, which is composed of millions of pixels. Each pixel in the image contains a value representing the amount of red, green, and blue light reflected. We can break the image out into its red, green, and blue bands, too. Here's the red band on its own. Brighter pixels mean that more light was reflected by objects in the image, and recorded by the camera in the red part of the electromagnetic spectrum. The darker parts are areas where less light was recorded. When we combine the red, green, and blue bands together, we get an image that looks similar to what we see through the camera lens. We can plot the amount of red, green, and blue light recorded in each pixel to create what's called a spectral signature. In this signature, the amount of energy reflected in a particular wavelength is shown in the y-axis, and the full range of wavelengths that were measured by the camera. In this case, blue, green, and red is on the x-axis. The spectral signature for phyto is quite different from the spectral signature for a plant. This makes them appear visually different to our eyes, too. Differences in spectral signatures can help scientists identify different types of services and objects within images. Most cameras record light in the visible or red, green, and blue bands. However, plants, dogs, and other objects on the earth also reflect light that we can't see with our eyes. For example, plants reflect up to 60% more light in the near-infrared portion of the electromagnetic spectrum than they do in the green portion of the spectrum. This is why differences in reflected light in the near-infrared portion of the spectrum are important for mapping vegetation on the ground. To measure these differences in the non-visible portion of the spectrum, we use imaging spectrometers, which record light in both the visible and non-visible parts of the spectrum. Imaging spectrometers produce what are called multi- and hyper-spectra remote sensing data. Multi- meaning many bands, more than three, and hyper- meaning up to hundreds of bands, collected at very high spectral resolution. We use these multi- and hyper-spectra remote sensing data sets to measure light energy reflected from objects on the earth's surface, and to estimate many physical and chemical properties of objects that we wouldn't see with our own eyes. We then use those measurements to classify what's on the ground. For example, pixels that have a spectral signature with a lot of near-infrared light energy are often vegetation. To review, different objects reflect, absorb, and transmit both visible light and light energy that we can't see differently. Imaging spectrometers record the amount of light that these objects reflect. The amount of light energy reflected by an object throughout the electromagnetic spectrum is called its spectral signature, which is driven by the physical structure and chemical makeup of the object. We can use that signature to identify different objects in both the photograph and across the earth's surface. And that, my friends, is how we use reflected light energy to both map what's on the ground and measure changes in our environment.