Mapping the Invisible: Introduction to Spectral Remote Sensing

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 camera is
called imaging spectrometers to measure changes in things that impact our
environment like water quality or vegetation cover and health. Imaging spectrometers 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 humanize 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 spectrometer is divided 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 transmitted 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, Fido the Dog reflects more light in the red portion of the spectrum because of the chemical and structural
makeup of his fur. If Fido’s chemical and structural makeup was the same as a
plant then he would look green. Now when you point your camera toward
your favorite canine doing something silly the camera record the amount of
light reflected from the dog and 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 the signature the amount of energy reflected in a particular wavelength as 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 Fido is quite different from the
spectral signature for our plant this makes them appear visually different to
our eyes too. Differences and spectral signatures can help scientists identify different types of surfaces 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 sixty percent 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 the 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 visible and non visible parts of the spectrum. Imaging spectrometers
produced what are called multi and hyperspectral remote sensing data. “Multi” meaning many bands, more than three, and “hyper” meeting up to hundreds of bands
clicked at very high spectral resolution. We use these multi and hyperspectral
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 uses 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 a 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 environments.

25 thoughts on “Mapping the Invisible: Introduction to Spectral Remote Sensing

  1. This is the best video so far I've seen explaining remote sensing to a broader audience.

  2. This video was well constructed, concise, and entertaining! A much sought after and seldom realized result which you have achieved. Congratulations!

  3. I want to reiterate what I see a lot of others saying. I just took a course on Remote Sensing, and this is pretty ace material. You guys have great outreach and education programs. Subbed

  4. It is mentioned that most of Green emitted from plant falls in the non visible light spectrum. Then how does plants appear green to our eyes.?

  5. Imagery (Remote Sensing) and GIS
    Best Practices for Extracting Information from Imagery

    Download: Write down your email address under this video (above), download link will be shared through "mega cloud". You have to check email from your Junk or Spam folder, if not found in inbox folder of email.

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  6. I request you to post videos on photographic process, optics and lens related to geo informatics physics, please. This was very useful.. Thanks a lot

  7. This is probably one of the best videos I've seen on YouTube about multispectral cameras, you explained it very well! Thank you! Thank you!

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