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.