Remote Sensing

The sky is ablaze with pink and orange clouds, as the sun begins to dip below the horizon stretched out in front of you. You take out your phone to snap a picture and capture the moment. You may not realize it, but you just used remote sensing to record electromagnetic data in the form of a photograph. Since the invention of the camera, remote sensing technology has developed into an increasingly important and expansive field of research that spans across many disciplines. 

Remote Sensing Remote Sensing

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    In the world of geospatial data, remote sensing allows us to view, measure, and record Earth phenomena at a distance. Using a variety of techniques, scientists can measure everything from the temperature of the ocean’s surface to the amount of water held in a plant’s leaves -all without ever actually coming into contact with what is being measured. How does it work, and how is it transforming the way we learn about the Earth? Read on to find out!

    Definitions of Remote Sensing

    The term “remote sensing” was coined in the 1950s by Ms. Evelyn Pruitt, a geographer in the U.S. Office of Naval Research. At this time, technology was rapidly evolving to record information about the Earth from aerial and satellite sensors. Today, with thousands of satellites in orbit, remote sensing has undoubtedly become a foundational research tool across many disciplines.

    Remote sensing is the process of detecting and measuring electromagnetic energy at a distance to obtain geospatial data.

    Remote Sensing satellite image of volcano StudySmarterFig. 1 - False color composite satellite image of the Nabro Volcano in Eritria. With remote sensing, temperature measurements can be displayed visually.

    How Does Remote Sensing Work?

    You might be wondering -what is actually being remotely sensed? That would be electromagnetic radiation or EMR.

    Buckle up for a quick physics review about the electromagnetic radiation spectrum!

    The sun emits shortwave EMR in the form of photons. Shorter wavelengths have higher frequencies and higher energy, while longer wavelengths have lower frequencies and lower energy. The Earth's atmosphere absorbs some of the sun's incoming energy and slowly releases it back out as long wave EMR.

    We see this energy as visible light on Earth, and we feel this energy as heat in the air, depending on the wavelength of the photons.

    Remote Sensing electromagnetic radiation spectrum StudySmarterFig. 2 - Remote sensing detects and records electromagnetic radiation.

    All incoming radiant energy is either absorbed, reflected, or transmitted through an object, depending on its wavelength and the object's material. Remote sensing works by recording values of EMR that reach a satellite or aerial sensor after being emitted or reflected from Earth.

    For example, snow on a mountain top will reflect a very high percentage of incoming visible light (that's why it appears so bright and white). In contrast, a nearby stand of trees on the mountain will appear darker and thus does not reflect as much visible light. Remote sensing satellites can record these differences in reflectance values, and they can be interpreted to identify land cover types from afar.

    A green leaf appears green to our eyes because it is reflecting green light wavelengths and absorbing blue and red light wavelengths. The way vegetation reflects light energy will look different from how soil or a body of water reflects light energy.

    Spectral signatures are displayed by plotting EMR reflectance values on the Y axis and wavelength values on the X axis. Spectral signature plots help to identify different objects or surface areas. They can even reveal differences between healthy and unhealthy vegetation due to the way pigments and water in leaves react with light energy!

    Remote Sensing spectral signature plot StudySmarterFig. 3 - Spectral signatures of three land cover types reveal different patterns of reflectance.

    Remote Sensing Techniques

    Remote sensing technology is diverse and includes various techniques tailored to obtain and interpret the different spectral signatures of objects. However, all remote sensing techniques rely on three principal components.

    The Three Components of Remote Sensing

    1. Target: an object, surface, or area that is to be measured.

    2. Electromagnetic Energy: this can be one or many parts of the electromagnetic spectrum.

    3. Sensor: a device that detects and records electromagnetic information.

    Types of Remote Sensing

    The two types of remote sensing refer to differences in how sensors obtain EMR data.

    Passive remote sensing relies on electromagnetic radiation energy that is being reflected or emitted from an object. This energy would be present regardless of the sensor.

    Active remote sensing involves a device capable of producing its own electromagnetic radiation energy and directing that energy at an object. The reflectance or back-scatter of the energy can then be recorded by the sensor.

    Passive sensors are useful for capturing satellite imagery of the Earth's surface, especially within the visible and infrared portions of the spectrum. These sensors are optimized to detect the sun's shortwave energy as it is reflected out. However, shorter wavelengths are more susceptible to atmospheric scattering because they are small enough to collide with gas particles. That's where active remote sensing comes in.

    By emitting energy directed at an object, active sensors can detect a clearer spectral signature with less scattering. Weather radars rely on active remote sensing because long wave lengths can pass through the atmosphere's gases and clouds with less scattering than shorter wavelengths. The returning reflected energy can be detected with less "noise" created by scattering.

    Based on what you know about the atmospheric scattering of shorter vs longer wavelengths, do you think blue or red visible light scatters more? Hint: what color is the sky? 1

    Recording and Visualizing Remote Sensing Data

    Energy arriving at a satellite's sensor is recorded within a grid. You can think of this grid as pixels in an image. A value is assigned to each pixel in the grid, and this value represents the intensity of the arriving energy.

    Many satellites used to study Earth can detect a wide range of wavelengths. Wavelength types are grouped into bands, which allow ERM data to be stored in separate grid layers.

    In remote sensing, a band represents a range of wavelengths. Incoming electromagnetic radiant energy is recorded separately for each band.

    The visible spectrum is typically split into three separate bands: blue, green, and red. Other common useful bands include near and mid-infrared.

    Humans see visible light as a combination of red, green, and blue light. When we assign the blue band to be represented visually with blue color, the green band with green color, and the red band with red color, we get a true color composite image with the appearance of natural colors.

    Remote Sensing true color composite StudySmarterFig. 4 - True color composite image of the San Francisco Bay Area.

    If we want to better distinguish areas of vegetation in the San Francisco Bay Area, we can instead utilize the near infrared band and represent its values with red color. This is called a false color composite image. Notice how areas with vegetation stand out more in the second image.

    Remote Sensing false color composite StudySmarterFig. 5 - False color composite image of San Francisco Bay Area.

    There are many possible combinations of remote sensing bands in false color composites. Researchers choose band combinations based on their abilities to better distinguish between targets of interest.

    Remote Sensing and GIS

    Remote sensing allows for the collection and recording of EMR data, while geographic information science (GIS) systems are used to store, visualize, and interpret the data.

    GIS systems transform grids of reflectance values into visual representations with pixels. This raster data can then be manipulated in GIS software for countless types of analysis.

    Raster data is composed of rows and columns of data stored in cells or pixels and is a primary data format used in GIS software.

    The grid of geographic data supplied by remote sensors can be analyzed in its raster format or transformed to other formats used in GIS to answer spatial questions.

    Remote Sensing Examples

    With spatial analysis in GIS, remote sensing has become a powerful tool for learning about the Earth. Below are several examples of how remote sensing is used in GIS to answer important questions.

    Quantifying Deforestation with Landsat Satellites

    NASA's Landsat program began with the launch of the first Landsat satellite in 1972. Landsat satellites have passive sensors that detect and store ERM within a variety of bands.

    To understand how deforestation has progressed in the Amazon Rainforest, Landsat imagery throughout the years can be added into GIS software for spatial analysis. Notice the differences between the satellite image of Rondônia, Brazil on the left from 1975, and the image of the same area taken in 2012.

    Remote Sensing deforestation in the Amazon on Landsat image StudySmarterFig. 6 - Landsat Images of Rondônia, Brazil from 1975 and 2012. The left shows dense forest cover in 1975, and the right shows settlement patterns and signs of deforestation.

    In this example, GIS was used to classify land cover types and quantify their change in area over time. Researchers found that over 70,000 km2 of Rondônia's forest has been removed since 1975.

    Areas of bare soil appear pink because this is a false color composite. This band combination was chosen for its ability to clearly distinguish between forest and bare soil.

    Mayan Ruins Discovered with LiDAR

    Light detection and ranging or LiDAR is a form of active remote sensing, and it can be used to create 3D models. A strong pulse of light is first emitted at a target, and the returning energy's location and intensity are recorded. This type of sensing occurs relatively close to Earth's surface, typically with sensors attached to planes or drones.

    LiDAR can capture fine details and can even penetrate forest canopy to reveal what is hidden below dense vegetation, so researchers have been using this technology to search for ruins across the world.

    Remote Sensing LiDAR 3D model StudySmarterFig. 7 - 3D topographic model of the Aguada Félix ruins site discovered with LiDAR.

    One such discovery involving LiDAR revealed a large Mayan ruin of a ceremonial site called Aguada Félix in Mexico2. The slight variations in topography from the ruins were not detectable by far away orbiting satellites.

    Remote Sensing - Key takeaways

    • Remote sensing is the process of detecting and measuring electromagnetic energy at a distance to obtain geospatial data.
    • Incoming radiant energy from the sun is either absorbed, reflected, or transmitted through objects or surfaces on Earth, and remote sensing works by recording reflected electromagnetic radiation in a grid pattern.
    • The two types of remote sensing are active and passive sensing.
    • GIS software is used to visualize remote sensing data in a raster format as satellite imagery.
    • Remote sensing data is commonly used for analyzing land cover, weather and atmospheric processes, and many other Earth phenomena.

    References

    1. SCIENTIFIC AMERICAN, a Division of Springer Nature America, Inc., 2003. https://www.scientificamerican.com/article/why-is-the-sky-blue/
    2. Inomata, T., Triadan, D., Vázquez López, V.A. et al. Monumental architecture at Aguada Fénix and the rise of Maya civilization. Nature 582, 530–533 (2020). (https://doi.org/10.1038/s41586-020-2343-4)
    3. Figure 1: Volcano Satellite Image (https://www.flickr.com/photos/gsfc/5880575519/in/album-72157678715062653/) by NASA Goddard Space Flight Center (www.flickr.com/photos/gsfc/) licensed by CC BY 2.0 (https://creativecommons.org/licenses/by/2.0/)
    4. Figure 3: Spectral Signature Graph (https://seos-project.eu/classification/classification-c01-p05.html) by Science Education through Earth Observation for High Schools (SEOS) licensed by CC BY-NC-SA 2.0 (https://creativecommons.org/licenses/by-nc-sa/2.0/)
    5. Figure 7: LiDAR 3D map of Aguada Félix (https://en.wikipedia.org/wiki/Aguada_F%C3%A9nix#/media/File:Aguada_F%C3%A9nix_1.jpg) by Alfonsobouchot (https://commons.wikimedia.org/wiki/User:Alfonsobouchot) licensed by CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0/deed.en)
    Frequently Asked Questions about Remote Sensing

    How are remote sensing data commonly used?

    Remote sensing data are commonly used for analyzing land cover, weather, oceanic processes, and other natural phenomena on Earth. 

    What are examples of remote sensing?

    Examples of remote sensing include the collection of satellite imagery and weather data obtained by remote sensing radars.

    Is GPS an example of remote sensing?

    GPS is different from remote sensing because it requires a receiver on Earth to establish a location. Remote sensing functions independent of a ground receiver, but it does rely on GPS data to record the location of incoming energy.  

    What are the two types of remote sensing?

    Passive and active sensing are the two types of remote sensing. Passive remote sensing relies on electromagnetic radiation energy that is being reflected or emitted from an object. Active remote sensing involves a device capable of producing its own electromagnetic radiation energy and directing that energy at an object.  

    What are 4 applications for remote sensing?

    Applications for remote sensing include analyzing land cover changes like deforestation, collecting weather and natural disaster data, and analyzing plant health in agriculture. 

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