Reaching New Heights with Remote Sensing
Remote sensing solves some of our most challenging problems.
Make no mistake:
Remote sensing is reaching new heights because it saves you money from doing field work.
If you’re looking to upgrade your knowledge, then this remote sensing guide is a must read.
Your Body Uses Remote Sensing
In fact, you’re using remote sensing by reading this right now…
Remote sensing means your acquiring information from a distance. Your body is equipped with three remote sensors:
1. Your eyes see the reflected electromagnetic light.
2. Your ears hear sound, which are mechanical waves.
3. Your nose smells aromas, which is more of a chemical reaction.
With the sense of taste, your tongue physically touches food. With the sense of touch, your hand physically touches an object.
So we can’t classify taste and touch as remote sensing.
Sensing Wavelengths in the Electromagnetic Spectrum
The Electromagnetic Spectrum is the range of all possible wavelengths.
It’s composed of thousands of wavelengths of light. It spans from short wavelengths (like X-rays) to long wavelengths (like radio waves).
Remote sensing enables you to see the invisible (and visible).
You read this post. Light bounces off the screen into your eyes as three channels: red, green and blue.
The incident energy source could be the sun, lights, candles or a flashlight. Our eyes see reflected energy in the visible spectrum (390-700 nm).
What if you were a goldfish or bumble bee?
- If you were a goldfish, you would see light a bit differently. A goldfish sees infrared radiation (700 nm to 1mm) which is invisible to the human eye.
- Bumble bees can see ultraviolet light (10 nm to 380 nm). Humans don’t see ultraviolet radiation with our eyes and (UV-B harms us.)
We, humans made up these wavelength regions (spectral bands) for our own purpose – to conveniently classify them.
Visible (red, green and blue), infrared and ultraviolet are descriptive regions in the electromagnetic spectrum.
Each region is categorized based on its frequency (v) /wavelength ().
Each Object Has Its Own Unique Spectral Signature
Why even care about the electromagnetic spectrum?
The EM spectrum is important because each object reflects, transmits and absorbs light differently, depending on its chemical composition. Objects reflect light in bands of light we cannot see with our eyes – but sensors can. Spectrometer record light that objects reflect into bands.
Plants are the color green because they reflect more green light. Healthy vegetation reflects more near-infrared light and we use an index called NDVI to help classify vegetation.
Each object has it’s own unique chemical composition.
This is in tune with saying each object has it’s own spectral signature. Differences in spectral signatures is how we tell objects apart.
Spectral signatures using different wavelengths in the EM spectrum gives us the ability to learn more information about Earth’s features that we may have not known.
What’s the Difference Between Hyperspectral and Multispectral?
Multispectral and hyperspectral imagery gives the power to see as humans (red, green and blue), goldfish (infrared), bumble bees (ultraviolet) and more. This comes in the form of reflected EM radiation to the sensor.
The main difference between multispectral and hyperspectral is the number of bands and how narrow the bands are.
Multispectral imagery generally refers to 3 to 10 bands that are represented in pixels. Each band is acquired using a remote sensing radiometer.
Hyperspectral imagery consists of much narrower bands (10-20 nm). A hyperspectral image could have hundreds of thousands of bands. This uses an imaging spectrometer.
An example of a multispectral sensor is Landsat-8. Landsat-8 produces 11 images with the following bands:
Band 1: Coastal aerosol (0.43-0.45 um)
Band 2: Blue (0.45-0.51 um)
Band 3: Green (0.53-0.59 um)
Band 4: Red (0.64-0.67 um)
Band 5: Near infrared NIR (0.85-0.88 um)
Band 6: Short-wave Infrared SWIR 1 (1.57-1.65 um)
Band 7: Short-wave Infrared SWIR 2 (2.11-2.29 um)
Band 8: Panchromatic (0.50-0.68 um)
Band 9: Cirrus (1.36-1.38 um)
Band 10: Thermal Infrared TIRS 1 (10.60-11.19 um)
Band 11: Thermal Infrared TIRS 2 (11.50-12.51 um)
The TRW Lewis satellite was meant to be the first hyperspectral satellite system in 1997. Unfortunately, NASA lost contact with it.
But later NASA did have a successful launch mission. The Hyperion imaging spectrometer (part of the EO-1 satellite) is an example of a hyperspectral sensor. The Hyperion produces 30-meter resolution images in 220 spectral bands (0.4-2.5 um).
NASA’s Airborne Visible / Infrared Imaging Spectrometer (AVIRIS) is an example of a hyperspectral airborne sensor. AVIRIS delivers 224 contiguous channels with wavelengths from 0.4-2.5 um.
Multi means many bands (more than 3). It’s usually collected at a lower spectral resolution. Hyper means hundreds of bands. It’s usually collected at high spectral resolution.
Atmospheric Windows and Absorption Bands
Not all of the EM spectrum hits the Earth’s surface. Atmospheric absorption prevents specific types of EM radiation.
Think of atmospheric windows like a curtain with holes:
The cloth from the curtain blocks specific wavelengths. In reality, the atmosphere contains water vapor or carbon dioxide that absorbs x-rays, gamma rays and other EM spectra. This is known as “absorption bands”.
But these are special types of holes that allow only specific types of sunlight to freely pass. Radio waves can pass through quite easily. But x-rays cannot.
Holes in the curtain are the atmospheric window with specific bands of EM spectrum can freely pass.
The cloth from the curtains block sunlight.
The point is:
Some types of light doesn’t reach Earth so engineers design sensors to measure specific wavelengths.
What’s the Difference Between Passive and Active Remote Sensing
Passive sensors measure reflected sunlight that was emitted from the sun. Active sensors have their own source of light or illumination and its sensor measures reflected energy.
- Active sensors like the Radarsat missions create their own source of illumination. It measures the energy that bounces back to the sensor.
- Passive sensors like the Landsat missions collects reflected energy that was emitted by the sun emits. Passive sensors measure the reflected energy at a specific frequency (v) (i.e. wavelength ).
Think of cameras as a passive AND active sensor:
You hold your camera in your hand. Flash turned on. You take a picture.
What’s exactly happening here?
The camera sends light to the target. The light reflects off the target back to the camera lens. This is the light that your camera measures.
You can think of active remote sensing like a handheld camera with the flash turned on. But active remote sensing can be spaceborne satellites orbiting the Earth or airborne on an aerial unit.
- Cameras are active sensors when the photographer uses flash. It illuminates its target and measures the reflecting energy back to the camera.
- Cameras are passive sensors when the photographer does not use the flash. The camera is not providing the source of energy. It uses naturally emitted light from the sun or lamp.
READ MORE: Passive vs Active Sensors in Remote Sensing
How Often Do Satellite Orbits Revisit?
Stare up 705 kilometers into the atmosphere at the right time and you can see Landsat-7 or 8 satellites. This is a typical altitude of a satellite.
The height of the satellite above the Earth surface will determine the time it takes for the orbit to take one complete orbit of the Earth. Orbital period increases with satellite height.
But how do satellites orbit the Earth?
Geostationary orbits is a circular orbit Earth’s equator with a radius of approximately 42,164 km intentionally matching the Earth’s rate of rotation. (Example GOES satellites)
Sun Synchronous orbits is a geocentric orbit which combines altitude and inclination keeping the angle of sunlight on the surface of the Earth as consistent as possible. (Example Radarsat)
Polar Orbits passes above or nearly above both poles of Earth, but possibly another body such as the Sun with an inclination of approximately 90 degrees to the equator. (Example SPOT)
READ MORE: Geosynchronous vs Geostationary Orbits
Spatial and Spectral Resolution Properties
Spatial resolution is the detail in pixels of an image. Higher spatial resolution means more detail and smaller pixel size. Lower spatial resolution means less detail and larger pixel size.
Spectral resolution is comprised of spectral bands that are groups of wavelengths. High spectral resolution are bands that are more narrow – such as hyperspectral. Low spectral resolution are broader bands covering more of the spectrum.
Temporal resolution refers to the measurement with respect to time of image acquisition. A faster satellite revisit period means higher temporal resolution. A slower revisit period refers to lower temporal resolution.
Remote Sensing Energy Mechanics
Some electromagnetic energy (EM) is absorbed in the atmosphere before hitting the Earth’s surface. The EM radiation that actually makes it to Earth is called incident energy (Ei). But, now what happens?
There are three interactions that can happen with electromagnetic energy:
1) Electromagnetic waves bounce off the surface. This is called reflected energy (Er). Think of flashing a light in a mirror.
2) Electromagnetic waves are absorbed and cease to exist. This is absorbed energy (Ea). Think of why black shirts absorbs more light than white shirts.
3) Electromagnetic waves goes through the object. This is called transmitted energy (Et). Think of transparent objects.
Incident energy is a combination of reflected, absorbed and transmitted energy.
Incident Energy Formula:
Ei = Er + Ea + Et
Incident energy interacts differently for different features on Earth. Earth’s features have different proportions of energy being reflected, absorbed and transmitted. These differences give our eyes and sensors the capability to differentiate objects on Earth at different wavelengths. Sensors detect reflected energy:
Reflected Energy Formula:
Er = Ei – Ea – Et
Just like how our eyes see colors. We see things because of the way electromagnetic energy bounce off objects into our eyes. Sensors are similar in that they detect reflected energy at specific wavelengths (visible, infrared, ultraviolet). The energy reflected that a sensor measures is equal to the energy incident minus the energy absorbed and transmitted.
What is the proportion of reflected energy back to the sensor compared to the incident energy from the sun?
This proportion is called spectral reflectance (p). Spectral reflectance is different at specific wavelengths and is the main principle of remote sensing
Spectral Reflectance Formula:
p = Er / Ei
Remote Sensing Applications
There is no shortage of how remote sensing is being implemented in different industries:
Satellite and other remote sensing information is fundamentally important if we are going to solve some of the major challenges of our time.
From navigating through the Arctic to measuring soil moisture – there is a remote sensing solution for almost every world issue. Remote sensing puts a wealth of information into the hands of decision makers.
If we are going to take on some of the biggest challenges of Earth in the near future, we need remote sensing to cover that much ground.